Ask The Heat Treat Doctor® has returned to bring sage advice to Heat Treat Today readers and to answer your questions about heat treating, brazing, sintering, and other types of thermal treatments as well as questions on metallurgy, equipment, and process-related issues. In this installment, Dan Herring explores the optimal dew point for running an endothermic gas generator — comparing the low dew point practices of decades past with today’s modern operating range of +40°F to +45°F — and explains how dew point, temperature, and air/gas ratio affect catalyst life, generator maintenance, and the stability of the process gas.
This informative piece was first released in Heat Treat Today’sJuly 2026 Annual Super Brands Issue print edition.
A critical consideration in heat treatment is the type, consistency, and control of the furnace atmosphere. The purpose of a furnace atmosphere varies with the desired end result, so it begs the question if there is an optimal dew point to operate an endothermic gas generator to balance gas quality, performance, and maintenance life. Let’s learn more.
Purpose of an Endothermic Gas Atmosphere
In general, furnace atmospheres are used:
To protect the components being processed from chemical reactions that could occur on their surfaces (e.g., oxidation or carburization), that is, to be passive (chemically inert) to the metal surface.
To interact with the surface of the component (e.g., adding carbon, or nitrogen, or both), that is, to be reactive (chemically active) to the metal surface.
Table A. Common Types of Furnace Atmospheres
There are many types of furnace atmospheres available for use in heat treating (Table A). By far, one of the most common is endothermic gas.
Endothermic Gas Atmospheres
Figure 1. Endothermic gas generator schematic piping arrangement | Image Credit: The HERRING Group, Inc.
Endothermic gas generators are common equipment in the heat treat shop, with one of the most well-known generators being the RX®. The main components of an endothermic gas generator (Figure 1) are relatively simple, consisting of:
Heated reaction retort with catalyst
Air-gas proportioning control components
Pump to pass the air-gas mixture through the retort
Cooler to “freeze” the reaction and prevent soot formation
Table B. Compositional Ranges for Endothermic Gas
Endothermic gas (aka endo) is produced when a mixture of air and fuel is introduced into an externally heated retort at such a sufficiently low air-to-gas ratio that it will normally not burn. The retort contains an active catalyst, which aids in cracking the mixture. Leaving the retort, the gas is cooled rapidly to avoid carbon reformation (in the form of soot) before it is sent to the furnace. The endothermic gas composition (Table B), by volume, varies depending on the type of hydrocarbon gas feed stock.
Endothermic gas is typically used for applications such as neutral hardening gas carburizing and carbonitriding (as a carrier gas), and for certain types of brazing to name a few. It is generally produced so that its composition is chemically inert to the surface of the steel and can be made chemically active by the addition of enrichment (hydrocarbon) gas that is usually added at the furnace.
What is the Optimal Generator Dew Point?
A reader asked this important question: “I’m doing some searching on endothermic gas generation and the advantages/disadvantages of low/high dew point set points. We normally run a dew point of +50°F in our generator and have had success historically. We installed a new generator and were told to drop the dew point to +40°F as this would extend the life. Do you have any experience, or can you point me to any references listing some of the pros and cons of running lower and higher dew points?”
Past Thinking
The operating philosophy in yesterday’s heat treat shop was to run the generators at a low dew point, typically in the range of +30°F to +35°F, so that gas (or air) additions at the furnace could be minimized. The belief was that the furnace atmosphere was much more responsive at this range and controlling certain processes (e.g., carburizing) was easier.
The nickel content of the catalyst years ago varied by manufacturer but was typically in the 5–7.5% range. Given the operating parameters used, it was mandatory to run weekly air burnout cycles to minimize soot formation in the catalyst bed, which took place quickly at these low dew points. The catalyst also needed to be changed on average about every 12 months. This dew point range was considered a good compromise for heat treat shops that ran both carburizing and neutral hardening.
As a parenthetical note, the very first endothermic gas generators (which were charcoal fired) used 100% nickel balls as a catalyst.
Current Thinking
Today, and for roughly the last 20+ years, the “modern” thinking is to run endothermic gas generators at temperatures in the range of 1900°F–2000°F, depending on the manufacturer’s design and the materials and size (diameter and length) of the retort. Air/gas ratios (for natural gas) should be between 2.5:1 to 3.5:1 (Figure 2). Ratios as low as 2.0:1 can be run at higher generator operating temperatures. Gas and/or air additions are then done at the furnace for better process control.
Figure 2. Typical endothermic gas generator control panel | Image Credit: The HERRING Group, Inc.
Experience has shown that a generator running at 1900°F with an air gas ratio between 3.0:1 and 3.5:1 and an output dewpoint of +42°F provides the best combination of a stable process gas and maximum generator life.
A generator dew point range held between +40°F and +45°F reduces maintenance on the generator and decreases the frequency of performing air burnouts of the catalyst bed, which at these dew points only needs to be done approximately once a month. It also extends the life of the catalyst (upwards of 2+ years) and makes it easier for the modern controls to regulate the system. Remember, however, that gas transmission from the generator to the furnace can often raise the incoming furnace dew point by +5°F to +10°F.
The advantage of performing air burnouts less often is that the nickel coated catalyst lasts longer. A major reason for this is that today’s catalyst averages around 3% nickel. The catalyst is insulating firebrick dipped in a nickel sulfate bath to allow nickel absorption on the outer surfaces of the cubes or spheres.
Miscellaneous Remarks
One must be very careful when running dew points at +50°F or above. In the writer’s experience, the gas is much more unstable, the water (moisture) content of the gas can rise quicker than one might anticipate, and you can literally start “raining water” inside the furnace or in the transmission lines. In literally minutes, the endo dew point can rise from +50°F to +70°F if one is not careful.
In Summary
The subject of endothermic gas generators never grows old. The key to their success is finding an operating dew point that provides both a stable process gas and little maintenance downtime. However, planned preventative maintenance is still required and should be performed on a schedule determined by the number and type of problems that arise.
A future column will discuss specifics of generator control, and we will broaden the subject by providing a guideline to the selection of furnace atmospheres in heat treating, brazing, and sintering. Look for it in next month’s publication.
References
Herring, Daniel H. 2015. Atmosphere Heat Treatment, Volume II, BNP Media Group.
Herring, Daniel H. 2009. “Furnace Atmosphere Considerations During Heat Treating”, Furnaces International, March/April.
Herring, Daniel H. “Understanding Furnace Atmospheres, Atmosphere Operation and Atmosphere Safety,” Heat Treating Hints, Vol. 1 No. 7. Manuscript forthcoming.
About the Author
Dan Herring “The Heat Treat Doctor®” The HERRING GROUP, Inc.
Dan Herring has been in the industry for over 50 years and has gained vast experience in fields that include materials science, engineering, metallurgy, new product research, and many other areas. He is the author of six books and over 700 technical articles.
Machine learning is poised to become a powerful tool for modern heat treatment, transforming decades of production data into actionable process intelligence. In this Technical Tuesday installment, Zachary C. Menard, CEO and co-founder of HRC Labs, draws on real-world case studies in carburizing and tempering to explore how predictive models can accelerate recipe development, optimize operations, and support more consistent decision-making. Rather than replacing metallurgical expertise, data-driven tools offer a pathway to continuous improvement, greater efficiency, and stronger competitive advantage.
This informative piece was first released inHeat Treat Today’sJuly 2026 Annual Super Brands Issue print edition.
Introduction
Heat treatment is one of the most operationally demanding and variable processes in modern manufacturing. It operates at the critical intersection of process design, material variability, and the strict performance requirements of industries as diverse as automotive, aerospace, and construction.
As a result, even highly experienced heat treaters must routinely make high-stakes decisions: how to converge on a new recipe without expensive trial-and-error; how to increase throughput without sacrificing quality; and whether a deviation warrants rework or scrap.
Heat treaters are uniquely positioned to benefit from advances in machine learning when confronting these decisions. Years of archived process data, hardness measurements, and quality records represent a largely untapped resource.
When systematically modeled, this data can power predictive models that map recipe parameters to metallurgical outcomes.
This approach is not without precedent. Similarly complex industrial processes — aggregates mining, cement manufacturing, and even steel casting — have increasingly adopted machine learning to reduce variability, optimize cycles, and proactively detect process drift. These gains have not replaced domain expertise; they have amplified it.
The following sections outline how machine learning, when thoughtfully integrated with metallurgical understanding and domain expertise, can serve as an enabling infrastructure for modern heat treatment.
What is Machine Learning?
Machine learning (ML) refers to computer algorithms designed to learn how a system behaves by leveraging that system’s data. Among the most relevant ML models for heat treatment are multilayer perceptrons (MLPs), which are designed to learn complex, nonlinear relationships between process inputs and observed outcomes.
Image Credit: HRC Labs
In heat treatment, outcomes such as surface hardness, effective case depth, distortion, or residual stress do not depend on any single variable. They emerge from the simultaneous interactions between variables like temperature, time, atmosphere composition, material composition, part geometry, and quench severity and uniformity, to name a few.
MLPs are well suited to modeling precisely this type of behavior. Rather than assuming a predefined relationship or physical law, they learn the mapping from process parameters to measured outcomes directly from historical production data. Layer by layer, the model captures increasingly subtle interactions among variables, enabling it to represent effects that are difficult to express with predetermined equations.
Importantly, once trained on sufficiently representative data, MLPs can:
Predict part properties for proposed recipes in milliseconds.
Evaluate hundreds of candidate parameter combinations rapidly.
Provide explicit uncertainty estimates alongside predictions.
Be tuned to individual furnaces, load configurations, or heat treatment techniques.
While MLPs are well suited to modeling the complexity of the heat treatment process, another class of machine learning models called decision trees are particularly effective for structured operational decisions. Heat treatment routinely requires categorical judgments, from rework decisions to detecting process drift to root cause analysis.
Decision trees can categorize heat treatment runs based on how they differ from historical runs. For example, the tree may organize a run based on its temperature deviations, fluctuations in carbon potential, or variation in effective case depth from the average. Each terminal node or “leaf” of the tree represents a cluster of historically similar runs.
Because these clusters are associated with prior corrective actions and results, the tree can provide probabilistic guidance grounded in historical precedent. For example, when analyzing a recent batch of parts that missed their target case depth, the tree might find that among comparable historical runs, 80% were successfully re-processed under a modified cycle, while 20% were scrapped. This enables faster root cause analysis and supports decision making.
Heat Treatment Applications
ML is particularly well suited to modeling and managing the many interacting variables that determine heat treatment outcomes. These capabilities translate into three practical applications: recipe development, process optimization, and auxiliary decision support.
Recipe Development
Heat treaters rely on operational experience, test coupons, and simulation tools to inform recipe design. However, new alloys, part geometries, or throughput demands often require iterative trial runs. Each additional load dedicated to experimentation represents furnace time removed from production.
Finite element simulations can narrow candidate recipes, but their accuracy depends on material properties, boundary conditions, and calibration to production conditions.
ML models such as MLPs offer a complementary approach to physical simulations. Trained on historical production data, they learn how a specific furnace, material, and process behave under real production conditions. Once trained, these models can rapidly evaluate candidate recipes against hardness, case depth, and distortion targets.
Importantly, predictions can be accompanied by uncertainty estimates, allowing heat treaters to assess risk alongside expected performance. By reducing the number of physical trial runs required to converge on a robust recipe, ML can accelerate the path from testing to production while preserving metallurgical oversight.
Process Optimization
Once a recipe has been demonstrated to meet specification, the focus shifts from feasibility to efficiency and robustness. The objective becomes reducing cycle time and energy consumption while maintaining process stability and required part properties.
In practice, optimization often proceeds through incremental parameter adjustments informed by experience. Soak times may be shortened or quench conditions modified in pursuit of efficiency gains. Yet the interdependence of heat treatment parameters makes it difficult to predict how such changes will affect process robustness.
ML models provide a structured framework for navigating this landscape. Once trained, they can:
Evaluate a multitude of potential changes to a recipe.
Estimate the impact of efficiency-driven adjustments on final properties.
Quantify uncertainty, identifying parameter sets that are not only efficient but stable.
Rather than relying solely on sequential physical trials, heat treaters can assess proposed modifications computationally before allocating furnace capacity.
Each additional production run further refines the model. As data accumulate across varying materials, geometries, and operating conditions, predictive fidelity improves. Over time, optimization transitions from periodic study to continuous, data-driven improvement.
Auxiliary Decision Support
Recipe design and optimization are only part of the operational challenge in heat treatment. A substantial portion of heat treaters’ time is devoted to diagnosing deviations, determining appropriate corrective action, and monitoring for process drift.
When a batch fails to meet specification, multiple correlated factors may plausibly explain the deviation. As a result, root cause analysis often requires time-consuming review of process logs and historical records.
Image Credit: HRC Labs
Decision-tree-based models provide a structured method for accelerating this analysis. By learning from historical runs and their documented outcomes, the model can classify a new deviation according to its similarity to past cases. For example, the model may determine that comparable historical runs were most frequently associated with temperature non-uniformity rather than alternative causes.
This approach offers three practical advantages:
Image Credit: HRC Labs
Faster root cause analysis and reduced diagnostic downtime.
More consistent, data-backed rework decisions.
Earlier detection of process drift and emerging equipment issues.
Importantly, these models do not override heat treaters’ judgment. Rather, they surface structured historical context that may otherwise remain fragmented across logs and institutional memory. Over time, this improves consistency, auditability, and knowledge transfer.
Machine Learning in Heat Treatment
The preceding sections have outlined several proposed applications of ML in heat treatment. The following sections examine documented cases of successful ML application in heat treatment.
Case Study 1: Carburizing
Jia et al. (2023) demonstrated the use of multilayer perceptrons to model the vacuum carburizing process for a low-alloy carbon steel cylinder. Using primarily simulation-derived data supplemented by limited experimental runs, the authors trained an MLP to predict case depth, surface carbon concentration, and surface hardness from process parameters including carburizing and diffusion temperatures, cycle durations, and carbon concentration levels.
Image Credit: HRC Labs
Once trained, the model rapidly identified parameter combinations that satisfied specified hardness and case depth targets while reducing computational cost relative to traditional simulation tools.
Zhang et al. (2025) took a similar approach but focused on atmospheric carburizing. The study’s goal was to train an MLP to predict post-carburizing carbon concentration across multiple part geometries for SAE AISI 3316 gear steel. Representative test coupons were used to validate the simulation-derived training data against production runs.
The model predicted post-carburizing carbon concentration with average errors near 2%. While limited in scope, both studies demonstrate that ML can replicate complex diffusion-driven behavior and accelerate recipe evaluation. These investigations focused primarily on carbon concentration and hardness prediction; the same modeling frameworks could be extended to distortion and residual stress prediction.
Case Study 2: Tempering
To further explore the performance of ML in heat treatment, publicly available tempering data from the classic study of Hollomon and Jaffe (1945) were analyzed. Their model combines temperature and time into a single tempering severity parameter, M. While effective within specific steels, prediction errors increased substantially as carbon contents varied. This model failed in particular to extrapolate to the behavior of lower carbon steels, with errors surpassing 10 HRC in some cases.
Image Credit: HRC Labs
To address this limitation, ML was used as a corrective layer on top of the traditional Hollomon-Jaffe model. The Hollomon-Jaffe equation provided baseline hardness predictions, while the ML model learned systematic corrections based on alloy composition and processing conditions. This approach reduced prediction error dramatically — from over 10 HRC in some cases to 2 HRC — while preserving the underlying metallurgical framework.
A common concern with ML models is that they behave like “black boxes.” However, modern interpretability tools allow engineers to examine how models arrive at their predictions. In this study, SHAP (SHapley Additive exPlanations) analysis was used to examine how the model corrected the Hollomon-Jaffe prediction. This revealed clear trends in how quantities like carbon concentration informed the model’s corrections. Rather than behaving like a black box, the model learned consistent metallurgical patterns in the data.
This case study illustrates how ML models can improve traditional approaches when they are limited by assumptions about physical parameters or cannot accommodate certain inputs. Unique furnace behavior, fixturing configurations, and part processing history are difficult to capture and calibrate using traditional simulation tools. Additional work should explore the integration of ML as a corrective layer for simulation software.
Strategic Implications and Competitive Advantage
The case studies presented here illustrate a broader principle: ML is most powerful in heat treatment not as a replacement for metallurgical understanding, but as a mechanism for formalizing and extending it.
When applied thoughtfully, ML can accelerate recipe development, reduce trial-and-error, and support structured diagnostics grounded in historical precedent. Unlike static optimization studies, trained models improve continuously as new production data become available. Over time, they become increasingly plant-specific, capturing nuances in furnace behavior, fixturing, material sourcing, and operating conditions that are difficult to encode with predefined equations.
Successful implementation will require high-quality process data and close collaboration between heat treaters and data scientists. ML is not a substitute for metallurgical expertise, but a tool for extending it.
The opportunity is substantial. Heat treatment has generated decades of process data that remain underutilized. Shops that convert this historical record into predictive intelligence will gain measurable advantages in efficiency, robustness, and process consistency. As competitive pressures increase and tolerances tighten, the ability to continuously learn from operations may become a defining differentiator.
Heat treatment has a rich history of innovation and experimentation. The integration of ML represents the next step in that progression.
Acknowledgements: The author would like to thank Dan Herring, The Heat Treat Doctor®, whose insight and guidance were instrumental in refining the direction of this work.
References
Hollomon, J. H., and L. D. Jaffe. 1945. “Time-Temperature Relations in Tempering Steel.” Transactions of the American Institute of Mining and Metallurgical Engineers 162: 223–49.
Jia, Hongliang, Dong Ju, and Jian Cao. 2023. “Machine Learning Based Optimization Method for Vacuum Carburizing Process and Its Application.” Journal of Materials Informatics 3: 9. https://doi.org/10.20517/jmi.2022.43.
Zhang, Y., Z. Tang, Q. Yin, et al. 2025. “Machine Learning Based Prediction of Carbon Concentration in Carburized Steel.” Scientific Reports 15: 33678. https://doi.org/10.1038/s41598-025-18531-8.
About The Author:
Zachary Menard CEO and Co-Founder HRC Labs
Zachary (Zach) Menard is the CEO and co-founder of HRC Labs, an industrial AI company focused on process optimization and decision support for heat treatment. He holds a B.S. in physics from Vanderbilt University with a background in computational physics and machine learning research.
Optimized heat treat performance starts long before parts reach the furnace. In this Technical Tuesday installment, Chris Tivnan of SAFECHEM North America Inc. highlights how SEW-EURODRIVE‘s switch to solvent-based cleaning enabled faster cycles, reliable residue removal, and consistent results.
This informative piece was first released in Heat Treat Today’sApril 2026 Annual Induction Heating & Melting print edition.
In the world of industrial motion systems, precision, durability, and efficiency are non-negotiable. SEW-EURODRIVE, a manufacturer of advanced drive solutions, focuses on delivering performance-driven gearboxes and industrial drives that power everything from airport walkways and roller coasters to heavy-duty conveyors in manufacturing plants. At the heart of this capability lies the careful heat treatment of steel components, specifically gears and pinions, processed to exacting standards for strength and longevity.
From Atmospheric Carburizing to New Demands
Since 2002, SEW-EURODRIVE had relied on a well-established process: aqueous cleaning, followed by atmospheric carburizing, oil quenching, and a second aqueous cleaning process. The approach was reliable but not without limitations.
Their gas-fired furnaces demanded costly maintenance, such as re-bricking the hot zone, replacing furnace rails, and frequently tuning the burners to ensure safety. Oil quenching created a messy environment and required an additional post-quench wash. For smaller parts, the process was also highly labor-intensive. Operators had to manually build furnace loads, then shot blast parts after heat treatment. Processing several hundred thousand gears and pinions per year in this way translated into significant time and manpower.
Figure 1. Advanced robotics drive SEW-EURODRIVE’s fully automated cleaning and vacuum carburizing line — delivering higher throughput, consistency, and precision. Image Credit: ECM & SEW-EURODRIVE
SEW-EURODRIVE maintained five atmospheric furnaces on site, but to improve efficiency they envisioned a new setup: continuing to run large parts in the existing furnaces while shifting smaller, higher-volume gears and pinions to a vacuum carburizing line with robotic automation.
Why Vacuum Carburizing and Why Cleaning Matters
The ECM NANO vacuum carburizing system, designed for small batch sizes, allowed SEW-EURODRIVE to integrate robotic loading and unloading, a crucial step toward automation. Vacuum carburizing also offered tighter process control, reduced distortion, and more consistent results than atmospheric methods.
However, vacuum carburizing is unforgiving when it comes to cleanliness. Unlike atmospheric furnaces, which can tolerate some surface contamination, vacuum furnaces demand perfectly clean parts. Any residue from machining oils, coolants, or metal shavings risks compromising part quality and furnace integrity.
This is where cleaning — often treated as a secondary or preparatory step — became the cornerstone of SEW-EURODRIVE’s process reengineering. The HEMO hybrid cleaning machine, capable of running both aqueous and solvent programs, was selected to provide maximum flexibility. The system runs on the modified alcohol solvent DOWCLENE™ 1601.
Overcoming Initial Concerns
For a company committed to environmental responsibility, introducing a solvent-based process was not taken lightly. Concerns about waste disposal, flammability, and worker exposure were thoroughly evaluated. However, the hermetically sealed HEMO cleaning system, designed for safe solvent handling and minimal emissions, provided the reassurance the Environmental Health and Safety (EHS) team required.
Beyond the demands of vacuum carburizing itself, another decisive factor for solvent cleaning is the use of carbon fiber composite (CFC) fixtures in the cleaning and heat treat line. Lightweight yet highly durable, these fixtures make automated handling of smaller batch sizes possible. However, their porous structure tends to absorb liquids during cleaning. Any residual moisture or oils can later release in the furnace, risking damage to the hot zone and compromising part quality.
Compared with aqueous cleaning, solvent cleaning evaporates completely and removes absorbed residues far more effectively, leaving both parts and fixtures perfectly dry. In this way, solvent cleaning makes automation with CFC not only feasible but reliable. Multiple test cycles, conducted both at HEMO’s and ECM’s facilities, confirmed the performance: only solvent cleaning reliably removed the oils and coolants that could otherwise lead to furnace fouling or part discoloration.
A Technical and Operational Leap Forward
By March 2025, the fully integrated cleaning and vacuum carburizing line was in full production. The new process — solvent cleaning, vacuum carburizing, gas quenching, and tempering — represented a dramatic leap forward, both technically and operationally.
Figure 2. Full integration of HEMO cleaning and ECM vacuum technology enables a streamlined, automated workflow. | Image Credit: ECM & SEW-EURODRIVE
Parts now exit the furnace bright and clean, with no spotting or discoloration. The smaller batch sizes of the vacuum furnace system enable robotic loading, helping to achieve a streamlined, automated heat treat flow, especially critical for high-volume parts.
Manual processes once needed to build and break down furnace loads, as well as to shot blast parts post-treatment, have been fully eliminated for small components. This shift has not only freed up significant labor hours for larger parts that still require traditional handling but has also eliminated roughly $6,000 per month in consumable abrasive costs.
“In the past, it would take us two weeks to process an order of 25,000 gears and 25,000 pinions through the manual steps. That manpower is no longer needed on a very large section of our product family,” explained Chris Rollins, SEW-EURODRIVE’s Heat Treat Supervisor.
The hybrid cleaning system, equipped with aqueous and solvent cleaning technologies, was selected to provide maximum flexibility in removing different types of machining soils. This versatility ensured that the system could adapt to any future cleaning requirements. In practice, after extensive testing, SEW-EURODRIVE determined that solvent-only cycles best matched the needs of their vacuum carburizing line, offering the shortest cycle times and most consistent cleaning results.
While hybrid programs run in about 30 minutes and aqueous cycles in around 50 minutes, solvent-only cycles achieve the same high cleanliness in just 18 to 22 minutes — fast enough to keep pace with furnace loading and optimize overall throughput.
Gas quenching has also replaced oil quenching, eliminating the need for a second aqueous wash and the associated challenges of soap concentrations, rinses, and tank maintenance. Beyond weekly solvent checks and routine discharges, maintenance requirements for the cleaning machine remain low.
“With aqueous cleaning, it’s always a delicate balance to get the right amount of soap for cleaning without leaving spots,” explained Rollins. “With solvent cleaning, we don’t see spotting, rust, or any contaminants. The vacuum process also helps reduce distortion, so we have more consistent parts.”
Cleaner Start, Cleaner Finish
Optimizing heat treat results meant looking beyond the furnace for SEW-EURODRIVE. With vacuum carburizing, cleanliness is no longer optional — it’s critical. The integration of the hybrid cleaning technology unlocked the full advantages of the vacuum carburizing furnace system: automation, speed, quality, and consistency.
This process reengineering experience demonstrated that heat treat success starts far earlier, in the cleaning phase, and that true optimization comes from understanding how each part of the system supports the others. In this case, the cleaner the start, the cleaner the finish. “The new system has made us faster, leaner, and more confident in every part that leaves the line. Solvent cleaning wasn’t just a switch — it was the key to making vacuum carburizing work,” concluded Rollins.
About The Author:
Chris Tivnan Sales Manager SAFECHEM North America Inc.
With two decades of experience in the chemical industry, Chris Tivnan of SAFECHEM North America Inc. counsels manufacturers on the right choice of cleaning agent and their parts cleaning operation. He also manages relationships with regional distributors as well as local OEMs/OEAs.
Manual loading and batch transfers are giving way to robotic material handling in modern heat treat operations. In this Technical Tuesday installment, Dennis Beauchesne, general manager of ECM USA, examines how automation improves repeatability, boosts productivity, and reduces operator exposure to hazardous conditions near furnace hot zones — and how robotics, vision systems, and mobile transport technologies are helping heat treat facilities build safer and more efficient production environments.
This informative piece was first released in Heat Treat Today’sApril 2026 Annual Induction Heating & Melting print edition.
Robotic material handling is rapidly transforming modern heat treat operations traditionally dependent on manual loading and batch transfer. As heat treaters face increased pressure to improve throughput and working conditions while maintaining strict quality standards, automation has become a strategic investment.
Figure 1. SEW-EURODRIVE (Lyman, SC) robotic integration by ECM Robotics features a rear robot and pallets on the left and open area on the right for dunnage storage and management | Image Credit: ECM USA
Heat treat material handling is more than simple part movement. Parts must first be positioned onto fixtures or loaded into bins which are transferred, placed into the furnace, and then moved again for quenching and/or tempering — sometimes under undesirable conditions depending on the installed technology. Additionally, a robot needs to store dunnage in the designated robot area during the processing of the parts in the furnace and then reuse it when the parts are unloaded from the furnace. Dunnage can also be stored in the heat treat area and handled by automation (Figure 1). Robotics and automation promote efficiency and repeatability in this process, which is difficult to achieve with manual operations.
Robotic Advantages
The most significant advantages of robotic material handling are repeatability, consistency, and reduction of work force. Robots execute the same motions cycle after cycle, which ensures uniform loading and proper spacing between parts within fixtures or baskets. For example, in vacuum furnaces, correct part placement is essential to achieving even heat distribution and minimizing distortion. Automated loading eliminates error caused by human fatigue or procedure changes, leading to more consistent and desirable metallurgical results and reduced scrap/re-work.
Improved throughput and increased productivity are other major justifications for robotic integration. Heat treatment can hold-up manufacturing due to cycle times and variable material flow. Robotic systems streamline loading and unloading, reduce wait time between cycles, and allow furnaces to operate at optimal capacity. In high-volume environments, robotics can be managed with upstream machining and downstream finishing processes to create a continuous, automated production line. This level of integration shortens lead times and supports just-in-time manufacturing.
Safety is equally if not more important, as handling baskets or fixtures near hot zones increases operator risk of burns and injuries. Integrating robotics improves workplace safety by removing operators from direct exposure to these hazards. This solution also addresses labor shortages by allowing skilled personnel to focus more on process optimization and quality control rather than repetitive physical tasks.
Specifically in vacuum heat treatment, robotic systems are particularly beneficial. Vacuum furnaces require precise loading to maintain thermal uniformity and protect sensitive components. Automated loaders can transfer loads between heating chambers, quench cells, and temper furnaces in a continuous process flow that minimizes temperature loss and handling delays. Metallurgical results (e.g., hardness, case depth, distortion) are also directly influenced. This is especially helpful for critical and sensitive applications, such as aerospace components and medical devices.
Robotic Components Explained
For manufacturers with in-house heat treat or commercial shops processing multiple part types, the flexibility to program and handle a wide range of part geometries, weights, and batch sizes is vital for efficient operations. Quick-change grippers, adaptive tooling, mobile transport, and vision systems are key robotic components to achieve this goal (Figure 2). Vision systems of today are far more advanced in assisting with the programming phase than those from just a few years ago.
Figure 2. ECM Robotics manipulating parts | Image Credit: ECM USAFigure 3. AGV (automated guided vehicle), a portable robot that follows a path, delineated physically (e.g. lines on the floor) or through other guide posts (e.g. radio waves, magnets, lasers) | Image Credit: ECM USA
After the load building, automated mobile robots (AMR) or automated guided vehicles (AGV) can also be used to transport loads to and from the furnace. These mobile robots are integrated into factories to automate the transport of loads between different areas without requiring fixed infrastructure (rails or magnetic strips). This system coexists easily with operators and other equipment and adapts well to production floor changes. Integration of AMRs and AGVs frees up operators for more value-added tasks and reduces manual labor time (Figure 3).
Quick-change grippers or end effectors are tailored to the specific application and conditions when in use. Their design focuses on optimizing part clamping, friction, and contact while considering part geometry, cycle constraints, and precision requirements. Gripping technologies are available as pneumatic, electric, magnetic, or vacuum and can handle even the most delicate or fragile components in soft (flimsy) or hard state. Heat treat specific robotics companies, like ECM Robotics, also provide robotic machine vision systems. Integration of these vision systems improves precision and handling to optimize pick & place, palletizing, bulk unloading, and assembly.
For example, by identifying parts based on the diameter or number of teeth on the gear, these systems can then sort and track them within a heat treatment cell through part marking, tray/fixture encoding (QR codes), and weight scenarios or simply virtually through software, which removes the need to use any hardware tracking. Vision systems go beyond the physical movement of parts; by checking for surface imperfections and integrity, they are advantageous for quality assurance purposes.
The most common issue in the heat treating industry when integrating with robots has been fixture warpage. Modern 3D cameras can detect bent or warped pins and alloy trays to allow for movement to a new position. This capability allows for much more robust loading and unloading using moderately warped fixturing, which is common in heat treat operations. While the best consistency typically comes with the use of carbon fiber composite (CFC) trays, it is not necessary to upgrade to all CFC fixtures to get consistent loading and unloading as the system can be designed to handle either alloy trays or CFC as well as some systems with both.
In a recent vacuum furnace installation, a heat treater automated their gear cutting operation to prepare the dunnage before low pressure carburizing. The robotics integration simplified part storage by specific location to allow the robot to “see” with its vision system. Parts were then scanned using QR coding by laser marking and automatically connected to the part’s recipe as stored in the system. Typically, in a modular system using low pressure carburizing, individual cells are utilized and production is recipe driven. In this case, after a part was scanned, the recipe was uploaded into the next available cell, and the scanned parts and heat treat fixture were moved to the cell.
Capital Investment
While the initial capital investment in robotics can be significant, long-term returns are quickly realized through process optimization, better working conditions, reduced re-work, higher up-time, improved quality, and reduced labor hours. Predictive maintenance features and diagnostic monitoring further reduce unscheduled downtime. As manufacturers evaluate total cost of ownership, robotic material handling often proves to be a strategic solution that supports both operational efficiency and competitive positioning.
Future Impact on the Industry
In an industry where precision, repeatability, and reliability are essential, robotic material handling is increasingly valuable for modernizing heat treatment operations. By combining automation with advanced furnace technology or upgrading material handling of older furnace equipment, manufacturers can achieve safer workplace conditions, higher metallurgical quality, and greater overall process efficiency.
Looking ahead, the role of robotics in heat treatment will continue to expand alongside industry trends. Data-driven automation, AI-assisted scheduling, and collaborative robots are opening new possibilities for smarter, more connected facilities. Rather than replacing human expertise, robotics complement it by providing process precision and efficiency to allow heat treat professionals to focus on process innovation and more value-added responsibilities.
References
International Federation of Robotics. 2023. World Robotics Report.
Dennis Beauchesne brings experience of over 200 vacuum carburizing cells installed on high pressure gas quenching and oil quenching installations. He has worked in the thermal transfer equipment supply industry for over 30 years, 24 of which have been with ECM USA where he is the General Manager.
For more information: Contact Dennis Beauchesne at DB@ECM-USA.com.
Ask The Heat Treat Doctor® has returned to bring sage advice to Heat Treat Today readers and to answer your questions about heat treating, brazing, sintering, and other types of thermal treatments as well as questions on metallurgy, equipment, and process-related issues. In this installment, Dan Herring continues his discussion on gear heat treatment, exploring vacuum and induction hardening methods for gears — from low-pressure carburizing for advanced materials to single shot and tooth-by-tooth induction techniques — and how each can be matched to the specific demands of any gear application.
This informative piece was first released in Heat Treat Today’sMarch 2026 Annual Aerospace Heat Treating print edition.
In Part One of this discussion (Air & Atmospheres Heat Treating, February 2026), we discussed various gear types, materials, and how they can be atmosphere heat treated. This month, we are focusing on vacuum and induction heat treating methods. Let’s learn more.
Vacuum Heat Treatment Processing Methods
Table A. Advanced Materials Processed by LPC
Vacuum processing can be used for most of the atmosphere treatments mentioned in Part One including carburizing (Figure 1). Low pressure carburizing (LPC) is a proven technology and the choice for many advanced applications in aerospace, automotive, off-highway, and motorsports markets, as well as the development of carburizing cycles for high-performance materials (Table A).
Figure 1. Typical commercial heat treat load of gears for vacuum carburizing (Otto and Herring 2007) | Image Credit: Photo courtesy of Midwest Thermal-VacFigure 2. Pyrowear 675 – LPC – anneal – double normalize – harden – anneal – deep freeze – double temper | Image Credit: The HERRING GROUP, Inc.
The range of effective case depths for most of these grades can range up to 2.0–3.0 mm (0.080–0.120 inches) without significant sacrifice of microstructure (Figure 2). Furnace variables, such as temperature uniformity (± 3°C or ± 5°F), control of cycle parameters (boost/diffuse times, gas flow rate, pressure, hydrocarbon type) and surface carbon optimize the microstructure, producing case uniformities of ± 0.05 mm (± 0.002 inches). Where permitted, the range of carburizing temperatures now includes the use of high temperature (> 980°C, or 1800°F) techniques.
All these advanced materials required extensive development testing to produce custom designed recipes to optimize cycle parameters. Also, quenching methods (Otto and Herring 2002) have improved, allowing us to achieve desired core properties with quenching parameter selection (high-pressure gas or oil) for distortion-sensitive and distortion-prone part geometries (Otto and Herring 2005, 2008).
Induction Hardening Methods
Various methods of hardening via applied energy are used in manufacturing gears, including flame hardening, laser surface hardening, and induction hardening.
Of the various types of applied energy processing, induction hardening is the most common. Induction heating is a process that uses alternating electrical current that induces a magnetic field, causing the surface of the gear teeth to heat. The area is then quenched resulting in an increase in hardness within the heated area. This process is typically accomplished in a relatively short time. The final desired gear performance characteristics are determined not only by the hardness profile and stresses but also by the steel composition and prior microstructure. External spur and helical gears, bevel and worm gears, racks, and sprockets are commonly induction hardened. Typical gear steels include AISI/SAE grades 1050, 1060, 1144, 4140, 4150, 4350, 5150, and 8650.
Figure 3. Patterns produced by induction hardening (Rudnev 2000)
The hardness pattern produced by induction heating (Figure 3) is a function of the type and shape of inductor used, as well as the heating method. Quenching or rapidly cooling the workpiece can be accomplished by spray or submerged quench. The media typically used for the quench is a water-based polymer. The severity of this quenchant can be controlled by the polymer’s concentration. Cooling rates are usually somewhere in between what would be obtained from pure water and oil. In some unusual situations compressed air or nitrogen is used to quench the part.
The most common methods for hardening gears and sprockets are by single shot (Figure 4) or the tooth-by-tooth method (Figure 5). Single shot often requires large kW power supplies but results in short heat/quench times and higher production rates. This technique uses a circumferential copper inductor, which will harden the teeth from the tips downward.
Figure 4. Typical single shot induction hardening operation | Image Credit: Photo courtesy of Ajax-Tocco-MagnethermicFigure 5. Tooth-by-tooth induction hardening of a helical gear | Image Credit: Photo courtesy of Ajax-Tocco-Magnethermic
The larger and heavier loaded gears (where pitting, spalling, tooth fatigue, and endurance are issues) need a hardness pattern that is more profiled like those produced by carburizing, which can be obtained by tooth-by-tooth hardening. This method is limited to gear tooth sizes with modulus 4.23–5.08 (6 or 5 DP) using frequencies from 2 to 10 kHz and about 2.54 (10 DP) using a range of 25 to 50 kHz.
The lower the frequency, the deeper the case depth. Tooth-by-tooth hardening is a slow process and usually reserved for gears and sprockets that are too large to single shot due to power constraints. The process involves heating the root area and side flanks simultaneously, while cooling each side of the adjacent tooth to prevent temper-back on the backside of each tooth. The induction system moves the coil at a pre-programmed rate along the length of the gear. The coil progressively heats the entire length of the gear segment while a quench follower immediately cools the previously heated area. The distance from the coil to the tooth is known as coupling or air gap. Any changes in this distance can yield variation in case depth, hardness, and tooth distortion. The gear is indexed after each tooth has been hardened, often skipping a tooth. This requires at least two full revolutions in the process to complete the hardening of all teeth. Straight, spur, and helical gears up to 5.5 m (210 inches) weighing 6,800 kg (15,000 lb) have been processed with this method. The entire process yields a repeatable soft tip of the tooth with hard root and flank. In other applications, the tip and both flanks can be hardened simultaneously and yield a soft root.
In Summary
Today’s design engineer has the good fortune of being able to choose from a number of heat treatment technologies for any given type of gear material and design. When selecting a gear hardening method, it is essential to specify not only the desired mechanical and metallurgical properties, but the critical dimensions that must be held and even the desired stress state of the gears themselves. The secret to success is understanding the advantages and limitations of each technology and taking these into consideration when determining the overall cost of gear manufacturing.
References
Herring, Daniel H. 2004a. “Gear Heat Treatment: The Influence of Materials and Geometry.” Gear Technology, March/April.
Herring, Daniel H. 2004b. “Reducing Distortion in Heat-Treated Gears.” Gear Solutions, June.
Herring, Daniel H. 2007a. “Oil Quenching Technologies for Gears.” With Steven D. Balme. Gear Solutions, July.
Herring, Daniel H. 2007b. “Heat Treating Heavy Duty Gears.” With Gerald D. Lindell. Gear Solutions, October.
Herring, Daniel H. 2012–2016. Vacuum Heat Treatment. Vols. 1–2. BNP Media Group.
Herring, Daniel H. 2014–2015. Atmosphere Heat Treatment. Vols. 1–2. BNP Media Group.
Herring, Daniel H., Gerald D. Lindell, D. J. Breuer, and B. Matlock. 2001. “Atmosphere vs. Vacuum Carburizing.” Heat Treating Progress, November.
Herring, Daniel H., Gerald D. Lindell, D. J. Breuer, and B. Matlock. 2002. “An Evaluation of Atmosphere and Vacuum Carburizing Methods for the Heat Treatment of Gears.” In Off-Highway Conference Proceedings. SAE International.
Otto, Frederick J., and Daniel H. Herring. 2002a. “Gear Heat Treatment: Today and Tomorrow, Part 1.” Heat Treating Progress, June.
Otto, Frederick J., and Daniel H. Herring. 2002b. “Gear Heat Treatment: Today and Tomorrow, Part 2.” Heat Treating Progress, July/August.
Otto, Frederick J., and Daniel H. Herring. 2005. “Vacuum Carburizing of Aerospace and Automotive Materials.” Heat Treating Progress, January/February.
Otto, Frederick J., and Daniel H. Herring. 2007. “Advancements in Precision Carburizing of Aerospace and Motorsports Materials.” Heat Treating Progress, May/June.
Otto, Frederick J., and Daniel H. Herring. 2008. “Improvements in Dimensional Control of Heat Treated Gears.” Gear Solutions, June.
Rudnev, V. 2000. “Gear Heat Treating by Induction.” Gear Technology, March/April.
About the Author
Dan Herring “The Heat Treat Doctor” The HERRING GROUP, Inc.
Dan Herring has been in the industry for over 50 years and has gained vast experience in fields that include materials science, engineering, metallurgy, new product research, and many other areas. He is the author of six books and over 700 technical articles.
Carbon emissions reporting is no longer optional for heat treaters — it’s becoming a competitive and regulatory necessity. In this Sustainability Insights installment, Heat TreatToday examines research from Professor Fu Zhao and PhD candidate Lakshmi Srinivasan of Purdue University’s Heat Treating Consortium, detailing a new python-based carbon calculator built specifically for heat treat operations, how it models Scope 1, 2, and 3 emissions from furnace geometry and process parameters, and how in-house heat treaters can use it to meet growing transparency demands with minimal manual effort.
This informative piece was first released in Heat Treat Today’sFebruary 2026 Annual Air & Atmosphere Heat Treating print edition.
Emissions reporting has become an essential step. Navigating the requirements in an influx political environment only adds to the challenge. How can heat treaters remain in compliance? A tool designed through Purdue University’s Heat Treating Consortium (PHTC) may be the answer.
The consortium has funded research across heat treat projects ranging from the efficacy of novel quenchants to improving materials hardness. Roughly two years ago, the PHTC member companies requested research to develop a tool that would make carbon estimation possible.
Lakshmi Srinivasan, PhD Candidate in the School of Mechanical Engineering at Purdue UniversityProfessor Fu Zhao, Faculty Member at the School of Mechanical Engineering and the School of Sustainability Engineering and Environmental Engineering at Purdue University
Professor Fu Zhao, faculty member at the School of Mechanical Engineering and the School of Sustainability Engineering and Environmental Engineering at Purdue, decided to take on this research request. He brought on PhD candidate Lakshmi Srinivasan, an astute researcher of energy systems modeling and life cycle assessment in the School of Mechanical Engineering, to research and develop the tool. “This project aims to model furnace energy requirements based on furnace geometry and heat treating input parameters,” Srinivasan explained. “From these modeling energy flows and furnace build inputs, we calculate Scope 1, Scope 2 and Scope 3 carbon emission associated with operating the furnace.”
Scope 1: Direct carbon emissions from energy consumption within the plan (e.g. combustion of natural gas or other fuels)
Scope 2: Indirect emissions from purchased electricity, steam, heat, or cooling
Scope 3: All other indirect emissions across the supply chain (e.g., suppliers, transportation, product use)
The tool is a python-based desktop application with scalability in mind. Since development targets the carburizing process for both market and regulatory reasons, it is highly focused on industry needs. Additionally, Zhao and Srinivasan built the tool for users to integrate additional features and data sets to align with new requirements or emerging technologies. They also underscored that the tool’s architecture is designed for growth as a web-based application.
Image of the digital carburization tracking tool | Image Credit: Srinivasan and Zhao
Ease of use is central. Zhao and Srinivasan have refined the tool to limit how much unique user input is required to generate an accurate output. The team explained this as particularly challenging, having examined alternatives to simplify the interface without oversimplify the “underlying physics.” They described how the final form of the tool will work, saying that once key parameters are entered (furnace type, processing temperatures, time, part geometry), the tool will automatically calculate energy usage and emissions with minimal manual intervention.
PHTC members, many of whom represent manufacturers with in-house heat treating, have shown great interest, providing feedback and resources to shape the development of the tool. Additional enthusiasm was found at IHEA’s annual SUMMIT in August 2025, where Srinivasan presented the tool’s development. When asked what inquiries have directed their research, Zhao and Srinivasan shared the following:
Versatility and functionality: How flexible is the tool in accommodating different furnace geometries, part geometries, furnace types, and heat treatment processes?
Part-based allocation: How does the tool allocate emissions accurately to individual parts or batches within a furnace load?
Location-specific emissions: How does it account for location-based variations in scope 2 and scope 3 emissions, such as differences in electricity generation or supply chain impacts?
Another challenge has been ensuring careful tool calibration and verification. To do so, the team has taken accurate, real-world natural gas and electricity consumption from heat treat operations, courtesy of PHTC members, to verify the model’s predicted energy consumption at defined furnace operating temperatures.
Eventually, some form of this tool will be made available to those outside the consortium. Currently, however, PHTC members are at the forefront of development and usage. The researchers underlined this, commenting, “This tool is particularly timely and essential for industry, as companies are increasingly expected to provide transparent and accurate emissions reporting.”
While the world of standards and regulations can feel like a minefield, benchmarked discussions of this tool reveal promising applications for in-house heat treaters in the near future.
El reporte de emisiones de carbono ya no es opcional para los especialistas en tratamiento térmico — se está convirtiendo en una necesidad competitiva y regulatoria. En esta entrega de Perspectivas de Sostenibilidad, Heat TreatToday examina la investigación del Profesor Fu Zhao y la candidata a Doctorado Lakshmi Srinivasan del Heat Treating Consortium de Purdue University, detallando una nueva calculadora de carbono basada en Python, desarrollada específicamente para operaciones de tratamiento térmico, cómo modela las emisiones del Alcance 1, 2 y 3 a partir de la geometría del horno y los parámetros del proceso, y cómo los especialistas en tratamiento térmico con operaciones internas pueden utilizarla para cumplir con las crecientes exigencias de transparencia con un mínimo de intervención manual.
Este artículo informativo se publicó por primera vez enHeat Treat Today’sFebruary 2026 Annual Air & Atmosphere Heat Treating print edition.
Si tiene comentarios o preguntas sobre este artículo, háganoslo saber en: editor@heattreattoday.com.
El reporte de emisiones se ha convertido en un paso esencial. Navegar los requisitos en un entorno político cambiante solo añade complejidad al desafío. ¿Cómo pueden los especialistas en Tratamiento Térmico mantenerse en el cumplimiento normativo? Una herramienta diseñada a través de Purdue University’s Heat Treating Consortium (PHTC, por sus siglas en inglés) podría ser la respuesta.
El consorcio ha financiado investigaciones en proyectos de tratamiento térmico que abarcan desde la eficacia de nuevos medios de temple hasta la mejora de dureza de los materiales. Hace aproximadamente dos años, las empresas miembros del PHTC solicitaron una investigación para el desarrollo de una herramienta que hiciera posible la estimación de carbono.
Lakshmi Srinivasan, Candidata a Doctorado en School of Mechanical Engineering at Purdue UniversityProfessor Fu Zhao, Miembro del Profesorado de School of Mechanical Engineering and the School of Sustainability Engineering and Environmental Engineering at Purdue University
El Profesor Fu Zhao, miembro del profesorado de School of Mechanical Engineering and the School of Sustainability Engineering and Environmental Engineering at Purdue decidió asumir esta solicitud de investigación. Incorporando a la candidata a Doctorado Lakshmi Srinivasan, una destacada investigadora en el modelado de sistemas energéticos y evaluación del ciclo de vida en School of Mechanical Engineering y la School of Sustainability Engineering and Environmental, para la investigación y desarrollo de esta herramienta. “Este proyecto tiene como objetivo modelar los requerimientos energéticos del horno en función de su geometría y los parámetros de entrada de tratamiento térmico”, explicó Srinivasan. “A partir de estos flujos energéticos modelados y de los insumos asociados a la construcción del horno, calculamos las emisiones de carbono del Alcance 1, Alcance 2 y Alcance 3 asociados a la operación del horno”.
Alcance 1: Emisiones directas de carbono derivadas del consumo de energía dentro de la planta (por ejemplo, combustión de gas natural u otros combustibles)
Alcance 2: Emisiones indirectas provenientes de electricidad, vapor, calor o enfriamiento adquiridos
Alcance 3: Todas las demás emisiones indirectas a lo largo de la cadena de suministro (por ejemplo, proveedores, transporte, uso del producto)
La herramienta es una aplicación de escritorio basada en Python, diseñada pensando en la escalabilidad. Dado que el desarrollo está orientado al proceso de carburizado tanto por razones de mercado como regulatorias, se encuentra altamente enfocada en las necesidades de la industria. Adicionalmente, Zhao y Srinivasan diseñaron la herramienta para que los usuarios puedan integrar características adicionales y conjuntos de datos que se alineen con nuevos requerimientos o tecnologías emergentes. También subrayaron que la arquitectura de la herramienta está pensada para su crecimiento como una aplicación basada en la web.
Imagen de la herramienta digital de seguimiento de carburizado | Image Credit: Srinivasan and Zhao
La facilidad de uso es un aspecto esencial. Zhao y Srinivasan han refinado la herramienta para limitar la cantidad de entradas únicas requeridas por el usuario para generar un resultado preciso. El equipo explicó que este aspecto fue particularmente desafiante, ya que se examinaron alternativas para simplificar la interfaz sin simplificar en exceso la “física subyacente”. Describieron como funcionará la versión final de la herramienta, explicando que una vez que se introduzcan los parámetros clave (tipo de horno, temperaturas de proceso, tiempo, pieza) la herramienta automáticamente calculará la energía usada y las emisiones con una intervención manual mínima.
Los miembros del PHTC, de los cuales muchos representan compañías manufactureras que cuentan con tratamiento térmico interno, han mostrado interés, proporcionando retroalimentación y recursos para dar forma al desarrollo de la herramienta. Un entusiasmo adicional se observó durante el IHEA’s annual SUMMIT en agosto de 2025, donde Srinivasan presentó el desarrollo de la herramienta. Cuando se les preguntó qué interrogantes han guiado su investigación, Zhao y Srinivasan compartieron lo siguiente:
Versatilidad y funcionalidad: ¿Qué tan flexible es la herramienta para adaptarse a diferentes geometrías de horno, geometrías de piezas, tipos de hornos y procesos de tratamiento térmico?
Asignación basada en piezas: ¿Cómo asigna la herramienta las emisiones de manera precisa a piezas individuales o lotes de una carga dentro del horno?
Emisiones específicas por ubicación: ¿Cómo considera las variaciones regionales en las emisiones del Alcance 2 y Alcance 3, tales como las diferencias en la generación de electricidad o los impactos de la cadena de suministro?
Otro desafío ha sido garantizar la calibración y verificación cuidadosa de la herramienta. Para ello el equipo ha utilizado datos reales y precisos de consumo de gas natural y electricidad provenientes de operaciones de tratamiento térmico, cortesía de los miembros del PHTC, con el fin de verificar el consumo energético predicho por el modelo a temperaturas de operación definidas del horno.
Eventualmente alguna versión de esta herramienta estará disponible para usuarios fuera del consorcio. Sin embargo, actualmente, los miembros del PHTC se encuentran a la vanguardia tanto del desarrollo como del uso. Los investigadores enfatizaron este punto: “Esta herramienta es particularmente oportuna y esencial para la industria, ya que las empresas enfrentan una creciente expectativa de proporcionar reportes de emisiones transparentes y precisos”.
Si bien el mundo de las normas y regulaciones puede sentirse como un campo minado, las discusiones comparativas sobre esta herramienta revelan aplicaciones prometedoras a corto plazo para los especialistas en tratamiento térmico con operaciones internas.
Ask The Heat Treat Doctor® has returned to bring sage advice to Heat Treat Today readers, answer questions about heat treating, brazing, sintering, and other types of thermal treatments, as well as metallurgy, equipment, and process-related issues. In this installment, Dan Herring examines the essential role of heat treatment in gear performance: exploring the key material and design considerations for power transmission gears, the difference between through hardening and case hardening, and the atmosphere heat treatment processes — from carburizing and carbonitriding to nitriding and nitrocarburizing — that determine how well a gear handles load, wear, and fatigue in heavy-duty applications.
This informative piece was first released in Heat Treat Today’sFebruary 2026 Annual Air & Atmosphere Heat Treating print edition.
Have questions or feedback? We’d love to hear from you — reach out to our editorial team at editor@heattreattoday.com.
Gears play an essential role in the performance of many products that we rely on in our everyday lives. When we think about gears, we generally separate them into two categories: motion-carrying and power transmission. Motion-carrying gears are generally nonferrous alloys or plastics, while load bearing power transmission gears (Figure 1) are usually manufactured from ferrous alloys and are intended for heavy-duty service applications.
Figure 1. Typical off-highway truck power transmission gears | Image Credit: The Heat Treat Doctor®
Gear Materials & Engineering
Power transmission gears involve a wide variety of steels and cast irons. In all gears, the choice of material must be made only after careful consideration of the performance demanded by the application end-use and total manufactured cost, taking into consideration such issues as pre- and post-machining economics.
Key design considerations require an analysis of the type of applied load, whether gradual or instantaneous, and the desired mechanical properties, such as bending fatigue strength or wear resistance — all of which will define core strength and heat treating requirements.
Figure 2. Stress profile in a heavy-duty transmission gear | Image Credit: The Heat Treat Doctor®
It is important for the designer to understand that each area in the gear tooth profile sees different service demands (Figure 2). Consideration must be given to the forces that will act on the gear teeth with tooth bending and contact stress, resistance to scoring and wear, and fatigue issues being paramount. For example, in the root area, good surface hardness and high residual compressive stress are desired to improve endurance or bending fatigue life. At the pitch diameter, a combination of high hardness and adequate subsurface strength are necessary to handle contract stress and wear and to prevent spalling.
Some of the factors that influence fatigue strength are:
Hardness distribution, a function of:
Case hardness
Case depth
Core hardness
Microstructure, a function of:
Retained austenite percentage
Grain size
Carbide size, type, and distribution
Non-martensitic phases
Defect control, a function of:
Residual compressive stress
Surface finish and geometry
Intergranular toughness
In the total manufacturing scheme, a synergistic relationship must exist between the material selection process, engineering design, and manufacturing (including heat treatment). A balance of the priorities in each discipline must be reached to achieve the optimization necessary for the ultimate performance of the gear design. This is often not an easy task.
Various atmosphere heat treatment methods are used for most types of gears including pre-hardening steps (e.g., annealing, normalizing, stress relief) and hardening processes (e.g., neutral hardening and case hardening).
Hardening
Neutral (aka through hardening) refers to heat treatment methods that do not produce a case. Examples of commonly through-hardened gear steels are AISI/SAE grades 1045, 4130, 4140, 4145, 4340, and 8640. It is important to note that hardness uniformity should not be assumed throughout the gear tooth. Since the outside of a gear is cooled faster than the inside, there will be a hardness gradient developed. The final hardness is dependent on the amount of carbon in the steel. The depth of hardness depends on the hardenability of the steel.
Through hardening can be performed either before or after the gear teeth are cut. When gear teeth will be cut after the part has been hardened, machinability becomes an important factor based on final hardness. The hardness is achieved by heating the material into the austenitic range, typically 815°C–875°C (1500°F–1600°F), followed by quenching and tempering.
Case Hardening
By contrast, case hardening is used to produce a hard, wear resistant case (surface layer) on top of a ductile, shock resistant interior (core). The idea behind case hardening is to keep the core of the gear tooth at a level under 40 HRC to avoid tooth breakage while hardening the outer surface to increase pitting resistance.
Carburizing
Figure 3. Atmosphere carburizing of large gears | Image Credit: Photograph courtesy of Aichelin Group
Atmosphere carburizing is the most common of the case hardening methods in use today and can handle a diverse range of part sizes and load configurations (Figure 3). In general, a properly carburized gear will be able to handle somewhere between 30–50% more load than a through-hardened gear. Examples of commonly carburized gear steels include AISI/SAE grades 1018, 4320, 5120, 8620, and 9310, as well as international grades, such as 20MnCr5, 17CrNiMo6, 18CrNiMo7-6, and 20MoCr4.
Atmosphere carburizing is typically performed in the temperature range of 870°C–955°C (1600°F–1750°F) although temperatures up to 1010°C (1800°F) are used for deep case work. Carburizing case depths can vary over a broad range, typically 0.13–8.25 mm (0.005–0.325 inches).
Carbonitriding
Carbonitriding is a modification of the carburizing process, not a form of nitriding. This modification consists of introducing ammonia into the carburizing atmosphere to add nitrogen to the carburized case as it is being produced. Examples of gear steels that are commonly carbonitrided include AISI/SAE 1018, 1117, and 12L14.
Carbonitriding is done at a lower temperature than carburizing, typically between 790°C–900°C (1450°F–1650°F), and for a shorter time. Combine this with the fact that nitrogen inhibits the diffusion of carbon, and what generally results is a shallower case than is typical for carburized parts. A carbonitrided case is usually between 0.075–0.75 mm (0.003–0.030 inches) deep.
Nitriding
Nitriding is another surface treatment process that has as its objective increasing surface hardness. One of the appeals of this process is that rapid quenching is not required, hence dimensional changes are kept to a minimum. It is not suitable for all gear applications; one of its limitations is that the extremely high surface hardness case produced has a more brittle nature than say that produced by the carburizing process. Despite this fact, in a number of applications, nitriding has proved to be a viable alternative. Examples of commonly nitrided gear steels include AISI/SAE 4140, 4150, 4340, and Nitralloy® 135M.
Nitriding is typically done in the range of 495°C–565°C (925°F–1050°F). Case depth and case hardness properties vary not only with the duration and type of nitriding being performed but also with steel composition, prior structure, and core hardness. Typically, case depths are between 0.20–0.65 mm (0.008–0.025 inches) and take from 10 to 80 hours to produce.
Nitrocarburizing (Ferritic or Austenitic)
Nitrocarburizing is a modification of nitriding, not a form of carburizing. In the process, nitrogen and carbon are simultaneously introduced into the steel while it is in a ferritic or at times an austenitic condition. A very thin “white” or “compound” layer is formed during the process, as well as an underlying “diffusion” zone. Like nitriding, rapid quenching is not required. Examples of gear steels that are commonly nitrocarburized include AISI/SAE grades 4140, 5160, 8620, and certain tool steels, such as H11 and H13.
Nitrocarburizing is normally performed at 550°C–600°C (1025°F–1110°F) and can be used to produce a 58 HRC minimum hardness, with this value increasing dependent on the base material. White layer depths range from 0.0013–0.056 mm (0.00005–0.0022 inches) with diffusion zones from 0.03–0.80 mm (0.0013–0.032 inches) being typical.
In Summary
There are many ways to heat treat gears. While atmosphere heat treatment (discussed above) is perhaps the most widely used technology today, other types of heat treatments, namely vacuum and induction hardening, are becoming more and more common methods. These will be discussed in Part Two.
About the Author
Dan Herring “The Heat Treat Doctor” The HERRING GROUP, Inc.
Dan Herring has been in the industry for over 50 years and has gained vast experience in fields that include materials science, engineering, metallurgy, new product research, and many other areas. He is the author of six books and over 700 technical articles.
Ask The Heat Treat Doctor® has returned to bring sage advice to Heat Treat Today readers, answer questions about heat treating, brazing, sintering, and other types of thermal treatments, as well as metallurgy, equipment, and process-related issues. In this installment, Dan Herring examines the devastating effects of hot gaseous corrosion on furnace alloys: exploring the mechanisms behind metal dusting, the gas-solid reactions that drive catastrophic carburization, and the mitigation strategies to extend the life of heat treaters’ most valuable furnace components.
This informative piece was first released in Heat Treat Today’sJanuary 2026 Annual Technologies To Watch print edition.
Have questions or feedback? We’d love to hear from you — reach out to our editorial team at editor@heattreattoday.com.
Corrosion is a concern experienced by everyone involved in manufacturing industrial products. While there is a plethora of data and information on the effects of corrosion on engineered materials available (sources provided in the references section of this column), most corrosion engineers are focused on aqueous corrosion. By contrast, heat treaters must understand the effects of hot gaseous corrosion, especially on our furnace alloys. Let’s learn more.
Corrosion Basics
It is important to understand that all materials are chemically unstable in some environments and corrosive attack will always occur. In the scientific world, it can often be modeled and its effects predicted by studying thermodynamic data and knowing which of the many corrosion-related chemical states are active. In our world, however, it is equally important to understand the various forms of corrosion, namely:
Dezincification (aka selective leaching)
Electrolytic
Erosion
Galvanic (or two metal) action
General (aka uniform) attack
Intergranular attack
Pitting
Stress corrosion
The greater the metal’s solubility, the greater the degree and severity of the corrosive attack. There are many important variations of these forms of corrosion; two of the most important are 1) localized corrosive attack (e.g. pits, intergranular attack, crevices) and 2) interaction with mechanical influences (e.g., stress, fatigue, fretting). These actions are frequently rapid and have catastrophic effects.
The number of ways to combat corrosion have been well-documented, including alloying to produce better corrosion resistance materials; cathodic protection (via sacrificial anodes); coatings (metallic or inorganic); organic coatings (e.g. paints); metal purification; alteration of the environment; and nonmetallic or design (i.e., physical) changes.
Heat Resistant Alloys
Furnace interiors contain numerous examples of heat-resistant nickel-chromium-iron (Ni-Cr-Fe) alloys, including radiant tubes, fans, heating elements, roller rails and rollers, thermocouple protection tubes, chain guides, and atmosphere inlet tubes, to name a few. Baskets, grids, and fixtures are other examples. These alloys are normally selected based on their strength (at temperature) rather than resistance to corrosive attack.
Since these heat-resistant alloy parts are often the most expensive furnace components, heat treaters must understand how they can be attacked and what can be done to extend their life by minimizing or preventing corrosion.
Gas-Solid Reactions
A chemical reaction involving a (non-equilibrium) gas or gas mixture and a solid is classified as a gas-solid reaction. Examples of intermediate and high temperature reactions of this type include oxidation, sulfidation, carburization, and nitriding. Effects of gases containing vapors of chlorine, fluorine, and effluents from deposits of various alkaline chemicals (from cleaning compounds) and even phosphates are also problematic. The principles are the same for all types — only the details differ. As heat treaters, our interest is in controlling, retarding, or suppressing these reactions to prevent unwanted corrosion, gasification, or embrittlement of the furnace alloy or materials being processed.
Examples of Catastrophic Carburization (a.k.a. Metal Dusting)
Figure 1. Pusher furnace alloy fan and shaft assembly | Image Credit: The Heat Treat Doctor®
Metal dusting (Figure 1) is a hot gaseous corrosion phenomenon in which a metallic component disintegrates into a dust of fine metal and metal oxide particles mixed with carbon.
Generally, metal dusting occurs in a localized area, and how rapidly the disintegration progresses is a function of temperature, the composition of the atmosphere and its carbon potential, and the material. Other significant factors include the geometry of the system, reaction kinetics, diffusivities of alloy components, the specific-volume ratio of new and old phases, and the ultimate plastic strain.
Metal dusting usually manifests itself as pits or grooves on the surface, or as an overall surface attack in which the metal can literally be eaten away in a matter of days, weeks, or months. As an example, this writer has seen a 330-alloy plate mounted underneath a refractory-lined inner door of an integral quench furnace (where atmosphere passes underneath the door and into the quench vestibule) reduced in thickness from 12.5 mm (0.50 in) to less than 0.75 mm (0.03 in) in a little over two months.
Figure 2. 330 alloy radiant tube removed after six months of use (rotary retort furnace) | Image Credit: The Heat Treat Doctor®Figure 3. Microstructural view: catastrophic carburization | Image Credit: The Heat Treat Doctor®
In another example, a metallographic investigation performed by this writer on a failed wrought 330 alloy radiant tube (Figure 2) was conducted. Optical microscopy of the inside (Figure 3) and outside diameter surfaces in the attacked area revealed evidence of massive carbides. These carbides are formed by the reaction of carbon with chromium, depleting the matrix of chromium in regions adjacent to the carbides. Grain detachment and subsequent failure by erosion then occurred.
How Does It Occur?
In general, catastrophic carburization of ferrous alloys proceeds via the formation and subsequent disintegration of metastable carbide. The first step in the process is absorption of the gaseous phase on the surface of the metal; the more reactive this phase, the easier it decomposes or is catalytically decomposed (in the case of iron) on the surface. This step is followed by diffusion of carbon atoms from the surface into the bulk metal.
As a result, there is a continuous buildup of carbon within the surface layer. As this layer becomes saturated with carbon, a stable carbide, metastable carbide, or an active carbide complex forms, which then grows until it reaches a state of thermodynamic instability, at which point it rapidly breaks down into the metal plus free carbon.
It’s at this stage that the metal disintegrates to a powder as the result of plastic deformation and subsequent fracture in the near-surface layer. The process is controlled by internal stresses due to phase transformation; in other words, competition between stress generation and relaxation exceeds the ultimate strength in this near-surface layer and causes fracture to occur.
In Ni-Cr-Fe alloys, the phenomenon occurs slower (but does not stop) since the disintegration leads to larger metal particles, which are less active catalysts for carbon deposition than the fine iron particles that form with ferrous metals. Therefore, the mass gain from carbon depositing onto high-nickel alloys is much lower. Also, the decomposition of high-nickel alloys occurs by graphitization and not via unstable carbides.
Pourbaix-Ellingham Diagrams
Thermodynamics can be applied to solid-gas reactions to obtain equilibrium dissociation pressures below which no reactions occur. Data and diagrams are available for the free energies of formation versus temperature for most metallic compounds. An interesting use of Pourbaix diagrams (generally reserved for mapping out possible stable equilibrium phases of an aqueous electrochemical system) as a predictor of stable alloy systems is found by superimposing the various elemental constituents. These diagrams are read much like a standard phase diagram (with a different set of axes).
In Summary
Hot gaseous corrosion should be an area of focus for every heat treater to extend the life of alloy components, reduce downtime, and save money. Mitigation in the form of alloy selection, equipment design, type of atmosphere, process/cycle selection, and idling temperatures will play a huge role in extending the life of our furnace alloys, baskets, and fixtures.
References
ASM International. 1971. Oxidation of Metals and Alloys.
Nateson, K. 1980. Corrosion–Erosion Behavior in Metals. Warrendale, PA: Metallurgical Society of AIME.
National Bureau of Standards. 1978. Gas Corrosion of Metals.
Pourbaix, Marcel. 1974. Atlas of Chemical and Electrochemical Equilibria in Aqueous Solutions. Houston, TX: NACE International.
Pourbaix, Marcel. 1998. Atlas of Chemical and Electrochemical Equilibria in the Presence of a Gaseous Phase. Houston, TX: NACE International.
Schweitzer, Philip A. 1996. Corrosion Engineering Handbook. New York: Marcel Dekker.
Staehle, R. W. 1995. “Engineering with Advanced and New Materials.” Materials Science and Engineering A 198 (1–2): 245–56.
Stempco, Michael J. 2011. “The Ellingham Diagram: How to Use It in Heat-Treat-Process Atmosphere Troubleshooting.” Industrial Heating, April.
Uhlig, Hubert H. 2008. Corrosion and Corrosion Control. Hoboken, NJ: Wiley-Interscience.
Fabian, R., ed. 1993. Vacuum Technology: Practical Heat Treating and Brazing. Materials Park, OH: ASM International.
The Boeing Company. n.d. “Practical Vacuum Systems Design Course.”
About the Author
Dan Herring “The Heat Treat Doctor” The HERRING GROUP, Inc.
Dan Herring has been in the industry for over 50 years and has gained vast experience in fields that include materials science, engineering, metallurgy, new product research, and many other areas. He is the author of six books and over 700 technical articles.
Producing durable, wear-resistant gears for the wind turbine industry requires exacting control of carbon diffusion. Modern low pressure carburizing (LPC) is pushing the boundaries of control and consistency. This technology fine tunes carbon diffusion into the surface of components, and applied in a new pit-style vacuum furnace, it also delivers temperature uniformity, stronger gears, and shorter cycle times for large, complex components, all while eliminating oxidation and direct CO₂ emissions. In this Technical Tuesday installment, Tom Hart, director of sales for North America at SECO/WARWICK Corporation, examines how modern LPC technology in a pit-style vacuum furnace is reshaping high-volume carburizing for today’s in-house heat treaters.
This informative piece was first released inHeat Treat Today’sNovember 2025 Annual Vacuum Heat Treating print edition.
The Need To Carburize
Carburizing is a thermochemical treatment that finds applications across the automotive, aviation, and energy industries, particularly in power transmission systems. The widespread use of this process across many industries stems from its ability to improve mechanical properties by enriching the surface of steel with carbon.
Consider the wind turbine industry, growing with a CAGR (compound annual growth rate) of 6.2% from 2024 to 2033 (GlobeNewswire 2024). Carburizing plays a key role in the production of gears and pinions. These components, often made of alloy steels, such as 18CrNiMo7-6, 4320, 4820, and 9310 (GearSolutions 2009, Jantara 2019), must meet high strength and quality requirements. Carburized layers, often over 4 mm thick, provide resistance to wear and dynamic loads, which is important given the turbine’s expected service life of at least twenty years.
In practice, however, gears often require servicing after five to seven years (Jantara 2019), with their failures generating long downtimes and high costs (Perumal and Rajamani 2014).
Figure 1a: Pit-LPC in a hardening cell (model)Figure 1b: The view from the operator platform
The carburizing process, combined with hardening (usually in oil) and tempering, increases:
Surface hardness: improving abrasian resistance
Core ductility: protecting against cracks
Fatigue strength: extending the life of the part, which translates into lower operating costs
Alternative technologies, such as nitriding or surface hardening, offer other benefits (e.g., reduced deformation), but have limitations, such as thinner hardened layers, relatively long nitriding process times, or difficulties with complex geometry for surface hardening.
Pit Meets Vacuum LPC
Traditional atmospheric carburizing, despite its established position, has reached its limits in process performance expectations. In response to market needs, LPC (low pressure carburizing) technology is being increasingly implemented to enable precise process control, reduced emissions, and improved energy efficiency. More specifically, a pit furnace with vacuum heat treatment capabilities, aka the Pit-LPC, has been designed and developed to carburize thick layers on very large and/or long parts. This furnace combines the advantages of LPC technology with the ability to integrate existing hardening cells, facilitating the modernization of older installations.
While a vacuum furnace opening to an air atmosphere is a feature previously reserved for atmospheric furnaces, this innovative pit furnace has ceramic insulation and a dedicated heating system to leverage this capability. The chamber door can therefore be opened at process temperature in an air atmosphere for the direct transfer of the charge to the hardening tank. Additionally, the furnace is equipped with a closed circuit forced cooling system, which significantly shortens the charge cooling time from the carburizing temperature to the hardening temperature, increasing efficiency and shortening the production cycle.
Furthermore, the furnace allows for the process to be carried out at temperatures of 1925°F (1050°C) and higher, significantly shortening carburizing time and reducing production costs, even while maintaining a safe level of grain growth (e.g., 1800°F (980°C)).
Benefits of LPC technology designed in a pit furnace include:
Reduced process time due to higher operating temperatures
Elimination of internal oxidation (IGO) in the carburizing process
Highly uniform carburized layer
Low process gas consumption
No direct CO₂ emissions and fire risk
Ready for operation without lengthy conditioning
Computer-aided process support
Additionally, the furnace design increases work safety and comfort in its elimination of open flames, risks of explosion, and the need for constant atmospheric monitoring.
Figure 2. SimVac program window with an example LPC process simulation
This new pit furnace is compatible with SimVac software, developed by Lodz University of Technology and SECO/WARWICK, which enables the simulation and optimization of LPC parameters, reducing the need for process tests. SimVac Plus is a simulation software that includes a vacuum carburizing module (Figure 2). The program can be used either as a standalone tool for designing processes based on the desired carburized layer requirements or to visualize the effect of a given boost/diffusion sequence in the form of a carbon profile.
Testing the Furnace Characteristics and Technical Parameters
The furnace was designed to meet the highest requirements for heat treatment equipment. The basic technical parameters are as follows:
Working space / charge weight: 71″ diameter x 118″ deep / 17,600 lb (1,800 mm x 3,000mm deep / 8,000 kg)
Operating temperature: up to 2010°F (1100°C)
Heating power: 360 kW, three independent zones
Vacuum level: 10⁻² torr
Carburizing gas: acetylene
Temperature Uniformity
Temperature distribution tests were conducted in the furnace, with 12 load thermocouples arranged according to the diagram shown in Figure 2. Measurements were taken at several temperatures under vacuum conditions. The purpose of the tests was to confirm compliance with the Class 1 ±5°F (3°C) requirements of the AMS2750 standard.
Figures 3a-d. Location of the TUS load thermocouples and the results in vacuum at temperatures of 1550°F (840°C), 1800 °F (980°C), and 1925°F (1050°C)
The results presented in Figure 3 indicate that the furnace provides above-average temperature uniformity, which is particularly important for a large workspace with 71″ diameter x 118″ deep (1,800 mm diameter × 3,000 mm deep) and the processing of large-sized components with thick layers. The temperature difference (ΔT) between the extreme thermocouples, measured at 1550°F (840°C), 1800 °F (980°C), and 1925°F (1050°C), did not exceed 3.5°F (2°C). This means that the furnace meets the Class 1 requirements of the AMS2750 standard by a wide margin.
Operational Dynamics
Additionally, to evaluate the furnace’s operational dynamics, heating and cooling tests were performed on an empty device with samples. Figure 4a shows the heating curve; the furnace reaches a temperature of 1800°F (980°C) in 60 minutes. The furnace’s high energy efficiency has a heat loss of just 32 kW under these circumstances.
Figure 4a. Heating RateFigure 4b. Cooling Rate
Figure 4b shows teh curve of cooling forced by nitrogen at atmospheric pressure, measured in three zones and on samples with diameters of 1″ (25 mm) and 4″ (100 mm). The temperature drops from 1800°F (980°C) to 575°F (300°C) in 60 minutes; reaching 210°F (100°C) takes only two hours, whereas natural cooling would take several days.
Vacuum tests show that the furnace reaches operating vacuum of 10⁻¹ hPa in under 30 minutes and has a leakage rate of 10⁻³ mbar·l/s, which meets the industry standard for vacuum furnaces.
Test of Atmosphere vs. Vacuum Carburizing Processes
To obtain a carburized layer 0.145–0.160″ (3.7–4.0 mm) thick for 52.3 HRC (550HV1), two tests were compared: one in the PEGAT atmosphere furnace (Figure 5a) and another in the Pit-LPC vacuum furnace (Figure 5b). In both cases, the charge consisted of seven gears made of 18CrNiMo7-6 material, with a total weight of approximately 6.5 tons and a surface area of 280 ft² (26 m²). The process consisted of three stages:
Stage I: heating to the carburizing temperature and soaking
Stage II: actual carburizing with cooling to the hardening temperature and holding
Stage III: hardening in an external quenching tank — identical in both processes
Table A. Atmosphere vs. Vacuum Carburizing Process ComparisonFigure 5a. Essential process data and schematic flow of the carburizing process in a PEGAT atmosphere furnaceFigure 5b. Essential process data and schematic flow of the carburizing process in the Pit-LPC vacuum furnace
The LPC process, which consists of saturation and diffusion segments (Figure 6) allows for the precise control of carbon distribution. As the process progresses, the duration of the diffusion segments is extended, ensuring uniform saturation of the material.
Figure 6. Vacuum carburizing process trends in the Pit-LPC
After carburizing and hardening, all components were tempered at 355°F (180°C) for three hours.
Table B. Chemical Composition of 18CrNiMo7-6 (according to EN10084)
Gears and samples made of 18CrNiMo7-6 steel were used for destructive testing, in accordance with the EN 10084 standard. Six cylindrical samples were placed throughout the workspace — inside and outside the part — to assess carburization uniformity.
Tests conducted:
Vickers microhardness (HV1): performed on a Struers Durascan 70 device, allowing for the determination of hardness profiles and carburized layer depth (ECD) — a load of 9.81 N (HV1).
Surface and core hardness (Rockwell): measurements were performed on a Wilson Wolpert TESTOR tester with a load of 1470.1 N. At least five measurements were taken for each sample.
Microstructure: assessed on a Nikon LV150 optical microscope after nital etching.
Internal oxidation (IGO): analyzed on the unetched surface of the microsection.
Figures 7a-f. Microhardness profiles after the full process (carburizing, hardening, and tempering)
Figure 7 shows the microhardness profiles for the tested samples. For each sample, microhardness paths were inspected in three cross-sections. Based on this, the effective ECD layer thickness obtained on each sample was determined, as presented in Table C.
Table C. Thickness of the Carburized Layer Read from the Microhardness Charts (effective case depth average is 0.145–0.160″ (3.7–4.0 mm) at 52.3 HRC (550 HV1))
Average ECD values obtained for the samples ranged from 0.148 to 0.154″ (3.77 to 3.91 mm).
Surface and core hardness values for all samples were consistent and typical of carburized layers (Table D). Surface hardness ranged from 61.0 to 63.2 HRC and core hardness from 39.9 to 40.7 HRC. Interestingly, samples located on the inner side of the wheel achieved slightly higher surface hardness values (caused by retained austenite and cooling intensity).
Table D. Measured values of surface hardness and core hardness
Microstructure images of low-tempered martensite, along with retained austenite, were identified, ranging from 17 to 20% (Figure 8). The amount of retained austenite was determined using NIS-Elements software. No variation in structure was observed depending on sample location.
Figure 8a. Exemplary post-processing microstructure pictures of sample 1 surface. Magnifications x100 (left) and x500 (right). Nital etching 2%. Martensite with residual austenite (approx. 18%).Figure 8b. Exemplary post-processing microstructure pictures of sample 4 surface. Magnifications x100 (left) and x500 (right). Nital etching 2%. Martensite with residual austenite (approx. 20%).
The presence of intergranular oxidation (IGO) was also inspected, averaging 5.5 μm throughout the tested samples. For comparison, intergranular oxidation in the atmospheric process averages above 15 μm. In the new LPC pit furnace, internal oxidation only occurs during unloading and transfer of the charge to the hardening tank, whereas in the atmospheric furnace, the presence of oxygen in the carburizing atmosphere is also significant, significantly increasing the IGO value.
The level of hardening deformation after the process conducted in the new LPC pit furnace and the atmosphere furnace is comparable due to the use of the same hardening tank in both devices and the absence of the carburizing process.
Comparison of Process Economics
Economic aspects play a key role in modern heat and thermochemical processing. Therefore, the consumption of basic utilities was compared for the reference processes (described in Chapter 5), resulting in a 0.152″ (3.8 mm) thick hardened layer. The analysis included a Pit-LPC and a PEGAT-type atmospheric furnace, both with identical workspace and the same charge. In addition, the LPC process was simulated at 1900°F (1040°C). The results are summarized in Table E.
Table E. Comparison of utility consumption and costs
The results show that the new LPC furnace model consumes significantly less electricity by approximately 57%, which translates into a lower carbon footprint, especially when energy is derived from fossil fuels. Nitrogen consumption is comparable, with a slight advantage for the Pit-LPC (savings of up to 10%).
The largest differences are found in carburizing gases. The atmospheric furnace consumes 9,900 ft³ (280 m³) of methane — approximately 440 lb (200 kg) and an additional 4.4–13.2 lb (2–6 kg) of propane per process. In the LPC furnace, acetylene consumption is reduced to 39.2 lb (17.8 kg) because carburizing gas only flows during the boost phase.
Importantly, the LPC process does not generate direct CO₂ emissions, unlike an atmospheric furnace, which emits approximately 1325 lb (600 kg) of CO₂ per cycle. Cooling water consumption in the new LPC furnace is also reduced by over 45%.
The presented comparison of utility consumption in the two types of furnaces directly translates into the economic aspects of using these devices and conducting production processes. For cost comparison purposes, the following unit utility costs were assumed, as presented in Table F:
Table F. Unit costs of energy factors and technological gases according to European averages
In summary, the total utility costs for the process conducted in the Pit-LPC at 1800°F (980°C) are 53% lower compared to an atmospheric furnace conducted at 1700°F (925°C). At a temperature of 1925°F (1040°C), savings reach 60%. These savings are primarily due to lower energy and process gas consumption. Furthermore, the lack of CO₂ emissions eliminates the need to pay emission fees.
The efficiency of this furnace is almost twice as much at 1795°F (980°C) and three times as much at 1925°F (1040°C) compared to an atmospheric furnace.
Summary
The new Pit-LPC vacuum furnace combines the design features of a top-loaded pit and performs carburizing using vacuum technology instead of atmospheric technology. Bringing higher processing temperatures than traditional atmospheric furnaces to the market, as well as the ability to open hot in an air atmosphere, this technology proves that direct transfer of the charge to the hardening tank is possible in vacuum furnaces.
Another key development, this design significantly shortens carburizing time compared to atmosphere furnaces since the furnace can operate under vacuum, inert gas (nitrogen, argon), air, and carburizing gases, at temperatures up to 2010°F (1100°C).
Since this new pit furnace design does not require the use a retort or atmosphere mixer, which are the most vulnerable components inside a traditional atmospheric furnace, the furnace operates with greater reliability and lower costs. Furthermore, an efficient and robust vacuum pumping system provides the vacuum environment and operational readiness in less than 30 minutes. Time is also saved by the integrated closed-loop gas cooling system that shortens cooling time: dropping temperatures from 1800°F (980°C) to 1545°F (840°C) in 30 minutes for a full charge and to 210°F (100°C) in two hours for an empty furnace, operations which would take several hours and days respectively in atmosphere furnaces.
The advanced thermal insulation and a uniform heating element layout ensure high energy efficiency and precise temperature uniformity in the working space, yielding additional cost and energy savings.
This carburizing process is based on FineCarb LPC technology and supported by the SimVac simulator, enabling precise carbon profile shaping and achieving layers 0.148–0.154″ (3.77–3.91 mm) thick with high repeatability.
With the ability to operate at temperatures up to 1925°F (1050°C), the new LPC pit-styled furnace significantly shortens process time, reduces utility consumption, and lowers operating costs by up to 50%, while increasing productivity by a factor of x2 to x3. One of these furnaces can replace two to three atmosphere furnaces of the same size.
Finally, the furnace operates in a safe and non-flammable atmosphere, emits no direct CO₂, and reduces energy consumption, making it an environmentally friendly solution.
Conclusions
The Pit-LPC furnace is a modern alternative to the traditional atmosphere furnace and offers a number of advantages in terms of quality, efficiency, safety, economy, and ecology. Providing an innovative solution for vacuum carburizing and meeting stringent carburization layer thickness guidelines, this design is a viable option to fully replace traditional atmospheric pit furnaces operating in a carburizing atmosphere.
Jantara, Valter Luiz Jr. 2019. “Wind Turbine Gearboxes: Failures, Surface Treatments and Condition Monitoring.” In Non-Destructive Testing and Condition Monitoring Techniques for Renewable Energy Industrial Assets, edited by Mayorkinos Papaelias, Fausto Pedro García Márquez, and Alexander Karyotakis. Amsterdam: Elsevier.
Perumal, S., and G. P. Rajamani. 2014. “Improving the Hardness of a Wind Turbine Gear Surface by Nitriding Process.” Applied Mechanics and Materials 591: 19–22.
Tom Hart Director of Sales for North America SECO/WARWICK Corporation
Tom Hart joined SECO/WARWICK in 2011 as a sales engineer and has been in the precision manufacturing industry for over 16 years. His responsibilities have him caring for SECO/WARWICK’s clients and their various process and heat treatment equipment needs. Tom received his manufacturing engineering degree from Edinboro University of Pennsylvania, has authored numerous white papers, and is recognized throughout the heat treatment industry as a go-to-guy for thermal processing.
