Gear Manufacturing Research Articles

Geometric Accuracy and Dimensional Precision in 3D Printing-Based Gear Manufacturing: A Study on Interchangeability and Forming Precision

This paper investigates the geometric interchangeability and dimensional precision of parts fabricated using Fused Deposition Modeling (FDM), with a focus on gear manufacturing. By employing a substrate and two spur gears as test components, critical process parameters, including layer thickness, extrusion speed, and print temperature, were optimized to achieve enhanced accuracy. Geometric and dimensional tolerances such as straightness, roundness, and surface roughness were systematically evaluated using advanced metrological techniques. The results indicate that larger components demonstrate higher precision, with deviations for large and pinion gears ranging between −0.045 and 0.060 mm, and −0.150 and 0.078 mm, respectively. Analysis reveals that the anisotropic nature of the FDM process and thermal shrinkage significantly impact accuracy, particularly in smaller features. Residual stress analysis reveals that smaller components formed via FDM exhibit higher stress concentrations and dimensional deviations due to voids and uneven thermal contraction, whereas larger components and flat substrates achieve better stress distribution and precision. The findings suggest that reducing material shrinkage coefficients and optimizing process parameters can enhance part quality, achieving dimensional tolerances within ±0.1 mm and geometric consistency suitable for practical applications. This research highlights the potential of FDM for precision manufacturing and provides insights into improving its performance for high-demand industrial applications.

Multi-objective mixed-model assembly line balancing with hierarchical worker assignment: A case study of gear reducer manufacturing operations

Assembly lines, generally speaking, can reduce production costs, shorten cycle times, and achieve higher quality levels. Since the current market is characterized by increasing product variability, mixed-model assembly lines, in which similar product models can be assembled simultaneously, are more suitable to respond to varied market demands than traditional single-model assembly lines. In addition, in an assembly line, tasks often differ in processing requirements, and workers may have different qualification levels. This study, therefore, aims to construct models for the multi-objective mixed-model assembly line balancing problem with hierarchical worker assignment (MO-MALBP-HW). The goal is to generate a suitable plan for a mixed-model assembly line balancing problem considering the constraint of a hierarchical workforce, the cost of a hierarchical workforce, and production cycle time. When the problem is simple, it can be solved by a mixed integer programming (MIP) model. When the problem becomes complex, it can be solved by a multi-objective genetic algorithm (MOGA) and a non-dominated sorting genetic algorithm II (NSGA-II) to obtain a near-optimal solution. The implementation of this model can effectively manage the multi-objective mixed-model assembly line balancing plan, thereby improving plant efficiency and reducing cost.

Process enhancements and wear evaluation of directed energy deposited bronze: Implications for reducing bronze in worm gear manufacturing

Process enhancements and wear evaluation of directed energy deposited bronze: Implications for reducing bronze in worm gear manufacturing

Service Life and Failure Analysis of Nylon, Polycarbonate, and IGUS i180 Polymer Gears Made by Additive Manufacturing

An assessment of different materials for additive manufacturing (AM) of polymer gears is presented in this research. Experimental testing is carried out for three different materials. Two materials are selected as the most common materials used for gears made by additive manufacturing. These materials are nylon and polycarbonate (PC). The third material is IGUS i180, which is a tribological material specially developed for additive manufacturing of parts with demands for high resistance properties such as resistance to friction, wear, and high temperatures which are essential for the long service life of gears. Gears are experimentally tested to determine service life in the form of operating cycles until failure. In addition, the gear temperature is monitored during the experimental testing. Using the value of maximum temperature at the moment of total gear failure at a specific load level enables the categorization of failure type. Different types of gear failures are categorized and presented. Taking into consideration failure type and the service life in the form of operating cycles, the applicability of analyzed materials for specific applications concerning load, speed, and thermal conditions is presented and discussed at the end of the paper. The main goal of this research was to test IGUS i180 material and compare its mechanical and thermal properties with other commonly used materials for gears manufactured by AM, such as nylon (PA6/66) and polycarbonate (PC). IGUS i180 material showed inferior properties concerning gear design in the case of high loads. This research showed that PA6/66 material is still the best solution for polymer gears production using AM, but the applicability of this material, due to temperature constraints, is still quite limited.

Experimental Analysis on Hybrid Polymer Gears Produced with Fused Deposition Modeling Method: Thermal Behavior and Wear

In this study, an experimental analysis of the thermal behavior and wear of polymer and hybrid polymer gears produced with the Fused Deposition Modeling (FDM) method was performed. Compared to conventional polymer gear manufacturing methods, the FDM process represents an energy-efficient material forming method. The low thermal conductivity of polymer gears has an impact on heating, which limits their application. The novelty of this research is an experimental analysis on hybrid polymer gears, and, for this purpose, a new hybrid polymer gear design with aluminum and steel inserts has been proposed. An in-house-developed non-mechanically closed-loop test rig was used to investigate Polyamide (PA) gears under different loads. An accelerated step load test procedure was employed, while the gears’ bulk temperature was recorded with a thermal imaging camera. The print quality affected the tooth flank surface roughness, so polymer gears with two different print qualities were initially produced. Hybrid polymer gears were produced with a higher print quality, since the print quality had an influence on the heating and wear. The correlation between the bulk temperature and wear was observed for all of the tested gears. A novel design of hybrid polymer gears with aluminum inserts achieved up to a 9 °C (17%) bulk temperature and a higher wear resistance.

A novel approach based on a mathematical algorithm and measurement of involute flanks for computing spur gear dimensions with unknown parameters

AbstractInvolute gears of all sizes and types are widely utilized in most machinery. Accurate generation of teeth flanks from the nominally required base circle is most vital in gear manufacturing, performance, and inspection. Despite the vital importance of the base circle in actual gear performance, it is not a widely used inspection parameter. Moreover, the size of base circle radius and geometrical center cannot be obtained by direct measurement. In this work, a new mathematical algorithm was developed to evaluate the base circle dimensions by measurement of only the teeth profiles. Measurement of the outer diameter is not required nor is the prior knowledge of any gear dimension such as its module or pressure angle. The evaluated base circle dimensions are then used to compute remaining dominant gear dimensions including its pressure angle. The developed approach was tested on an ideal gear model then applied to the flank points obtained by measurements performed on a Coordinate Measuring Machine (CMM) and by photogrammetry (PG). The experimental results were compared to those measured using a gear roll tester (GRT) and were found to be in very good agreement. The methodology and measurement procedure presented in this work are distinguished by their ability to measure the actual gear dimensions regardless of any tooth modification made to the profile or addendum during manufacturing. This makes the proposed work well-suited for reverse engineering and rapid prototyping reverse calculations.

Analysis of small plastic gears manufactured by SLS printing

Selective laser sintering (SLS) is an additive manufacturing method. During the production, the equipment sinters powdered material and binds this material together to create a solid structure. SLS 3D printers use a laser as the power and heat source. During the manufacturing process, the laser is aimed automatically at points in space defined by the 3D model. Since in the past we have worked on the manufacturing of small plastic gears by other additive techniques (FDM, stereolithography) and on the determination of their accuracy, in this article we determined the same characteristics for the SLS process.

The Concept of Technological Support of Operational Properties Based on Stabilization of Mechanical Properties of Gear Materials in a Gas Turbine Engine Drive System

Modern production of gears for gas turbine engines for aviation, marine and land use is inherently related to the calculation of the stress state of the working surfaces of the mating teeth. To create conditions for the operability of the gear train and the drive system as a whole, an engineering analysis of the contact endurance of the mating surfaces is a necessary criterion. The contact strength determines the life of the gear mechanism. The value of the contact strength, taking into account its distribution in the contact zone of the working mating surfaces of the gears, is determined by the processing technology and operation, but the mechanical properties and texture of the material have the greatest influence. This determines the requirements for the stability of the mechanical properties of the materials used for the manufacture of gears, making a topical question on their study. The technology of manufacturing the gears in the gas turbine engine drives forms the layer structure of the toothed crown because of the use of chemical-thermal treatment. The surface hardened layer of the gear tooth after chemical-thermal treatment is saturated with carbon and nitrogen, and as a result of thermal action acquires mechanical properties and structure different from the material in the supply. The paper presents the results of practical research of evolution of mechanical properties of structural steels 20H3MVF-Sh, 18H2N4MA, 16H3NVFM-Sh and 12H2N4A-Sh based on various types of chemical-thermal treatment, as well as microstructure of toughened layer and core of the part. The steel mechanical properties stabilization evaluation in the process of gear technology was performed. The presented results of experimental studies of mechanical properties of the material prove stabilization of mechanical and structural indicators, which are responsible for the contact strength of the mating surfaces of toothed gears.

Deep learning of 3D point clouds for detecting geometric defects in gears

Geometric integrity directly impacts the functionality, reliability, and safety of final manufactured products, making the qualification of parts based on measurements of their geometry a fundamental quality control activity in modern manufacturing. Recent advancements in three-dimensional (3D) metrology technologies have enabled fine-scale inspection of geometric integrity characterized by dimensional accuracy, surface quality, and shape conformity. However, the widespread adoption of high-resolution 3D metrology in manufacturing faces some significant challenges posed by the inherent data structures of 3D point clouds such as high dimensionality, unstructured nature, and sparsity in defective regions. To address these challenges, this paper first creates a “MFGNet-gear” dataset, which is a scalable and comprehensive benchmark dataset comprising 12 part designs with four quality classes for each design. Subsequently, we develop a deep learning model adapted from the PointNet++ architecture to enable automated, end-to-end analysis of 3D point clouds. The model can be configured for different decision-making tasks including part design classification and multi-class geometric defect detection. Implementations of the proposed model on the “MFGNet-gear” dataset achieve accuracies up to 100% in classifying gear designs and up to 85% in four-class quality inspection. Additionally, we systematically investigate the impacts of measurement resolution and precision on the classification performance through a series of case studies. The obtained results highlight the potential of using deep learning methods for automated analysis of 3D point clouds for a variety of quality control tasks beyond gear manufacturing. This study also proposes future research directions, including the development of new deep learning architectures specifically designed for manufacturing 3D point clouds and strategies for adaptive measurement planning.

On Wrist and Forearm Pain Experienced by Rowers: Can Mechanical Metamaterials Make Rowing and Coastal Rowing Safer?

On‐water rowing is a sport where participants make extensive, powerful, and complex repetitive movements with their wrists to pull and feather (twist) the oar. Herein, the aim is to assess the frequency and perceived causes of wrist and forearm pain in rowers and, in particular, assess whether there are any possible mechanical issues that could be addressed through the use of auxetic technology. Through an online survey of 145 on‐water rowers, it is found that 33.8% of the rowers reported wrist or forearm pain arising from rowing. The majority (67.3%) consider over‐gripping to be the cause while one out of five associated it with periods of tension and anxiety, which also led them to over‐grip. This indicates that rowing handles could benefit from the use of mechanical metamaterials, auxetics in particular, owing to their anomalous manner in how they deform when subjected to mechanical deformations. Moreover, given the rise in popularity of coastal rowing, which will become an Olympic discipline alongside classic rowing as from the 2028 Los Angeles Olympic Games, the potential use of auxetics in the manufacture of protective gear for use in coastal rowing is also discussed.

Calculation of the inverse involute function and application to measurement over pins

Abstract Measurement over pins plays a crucial role in ensuring the quality of gear manufacturing, which requires the evolution of the inverse involute function. In this paper, an efficient algorithm for calculating the inverse involute function is proposed. Firstly, the initial approximate solution of the pressure angle near 0 rad is established by using Padé approximation and one step of Schröder iteration. Then, the involute equation is transformed into another form by introducing a variable transformation, and the initial approximate solution of the pressure angle near π / 2 rad is constructed by using the same method. A piecewise initial approximate solution over the entire interval of expanded angles is obtained by combining these solutions. Again, the accuracy of the initial approximate solution can be significantly improved by using one step of Schröder iteration. A numerical example of a two-pin measurement is presented to demonstrate the superiority of our method over traditional iterative approaches. The algorithm is highly efficient and accurate, and is a useful tool for designers to accurately calculate gear systems.

Multi-physics field coupling interface lubrication contact analysis for gear transmission under various finishing processes

Surface integrity is crucial for the load-bearing capacity, transmission performance, and service life of gears. Finishing processes can effectively improve surface quality and are widely used in gear manufacturing processes to enhance surface integrity and improve the service performance of gears. Five precision machining tests of form grinding, vibratory finishing, barrel finishing, honing, and abrasive flow machining were conducted on spur gears. High-precision surface integrity characterization methods were used to analyze the surface integrity parameters of the finished gear surfaces, including surface roughness, surface microtopography, residual stress, texture aspect ratio, roughness peak curvature radius. The finishing processes uniformity and effectiveness of the tooth profile surface were also evaluated. By using the finished rough surfaces as inputs and considering the impact of thermal elasto hydrodynamic lubrication on the gear surface, a multi-field coupling contact analysis model encompassing solid, liquid, and thermal fields at the gear meshing interface was established. Lubrication performance parameters such as oil film pressure, oil film thickness, oil film temperature rise, and friction coefficient under various finishing surfaces were compared and analyzed. Experimental results indicate that barrel finishing can simultaneously improve various parameters, such as surface roughness, texture aspect ratio, and compressive residual stress. Finishing processes can effectively reduce surface roughness, improve lubrication performance and reduce the risk of scuffing failure. This approach provided an effective method for the comprehensive evaluation of the effects of various finishing processes. The developed program offers theoretical guidance and data support for the selection and optimization design of gear surface finishing processes.

Meshing analysis of mismatch toroidal worm gearing characterized by different basic parameters of hob and worm

Aiming at high error sensitivity and complicated worm gear manufacturing of the planar double enveloping toroidal worm drive, a new TP-H gearing which worm generates by a plane and the worm wheel generates by a straight profile hob is proposed. Firstly, a comprehensive and systematic meshing theory of this drive is established; A rigorous calculation method for the instantaneous contact point is proposed; A formula for calculating the eccentricity of the instantaneous contact ellipse based on the relative principal curvature is deduced, and it is suggested innovatively that the eccentricity can be used as the quantitative index for describing the degree of mismatch between teeth. Secondly, the selection and matching strategy of mismatched process parameters is given, and the contact behavior between tooth surfaces is simulated based on numerical examples, the results show that the novel transmission can achieve good point contact. The research will promote the in-depth development of the theory of mismatched meshing in toroidal worm drive, and explore the specific form of gearing with simple manufacturing, low error sensitivity, and considerable meshing performance.

Modelling width of the spectral component of a gas-turbine engine gearbox output shaft speed

Gearbox is the most stressed component in an aircraft gas-turbine engine. This implies the need for finding ways to monitor its technical condition. Practice shows that the most efficient method is vibration-based diagnostics. However, this method requires the use of sophisticated measurement systems and highly skilled personnel. This paper shows that errors of gear coupling manufacture and assembly, characteristics of machine operating mode, design factors, frequency modulation of the carrier of the engine rotor speed in the stationary mode of its operation, and wear of teeth flanks determine the width of the spectral component of the gearbox output shaft speed. Using the results obtained from the developed model of the width of gear tooth spectral component, ratios for width of the spectral component of the signal of the “standard” tachometric speed sensor of the gearbox output shaft speed and the corresponding spectral component of its vibration were obtained. Models for repaired and newly manufactured gearboxes and gearboxes with tooth flank wear were proposed. This allowed the development of a number of new diagnostic indicators of a defect. Several examples of the use of these new diagnostic indicators are given for the gearbox of one of turbo-prop engines. The results obtained provide an opportunity to assess the gearbox technical condition in operation.

Gear Hobs-Cutting Tools and Manufacturing Technologies for Spur Gears: The State of the Art.

The present work aims to provide the readers with a bird's-eye view of the general domain of cylindrical gear manufacturing technologies, including the cutting tools used, and related topics. The main scientific sources are explored to collect data about the subject. A systematization of the scientific works is completed, to emphasize the main issues the researchers have focused on in the past years in the domain. Several specific aspects are investigated: chip-forming process, cutting tool lifetime, the materials used to produce gear hobs, temperature and lubrication, the cutting tool geometry, cutting parameters, design methods, and optimization. Some gaps in the research have been identified, which are mainly related to the gear hob's design. These gaps, the organization of knowledge, the current requirements of the industry, and the actual socio-economic priorities form the basis for identifying new scientific research directions for the future in the area of spur gears manufacturing technologies and cutting tools. The main output of this work is a frame to guide the development of scientific research in the domain of spur gear production.

Addendum To: Manufacturing of spur gears having normal teeth on different pressure angles by module disc milling cutter

Addendum To: Manufacturing of spur gears having normal teeth on different pressure angles by module disc milling cutter

Relationship between firefighter protective clothing design ease and heat stress

PurposeClothing fit, including garment ease and drape, impacts the volume of air between clothing layers and the body, directly affecting the amount of heat that can be transferred through a multi-layer clothing system. As most acute firefighting fatalities are caused by overexertion and heat strain, the purpose of this research was to determine the impact of ease allowances on air gaps in structural firefighting turnout suits and their subsequent effect on total heat loss (THL) when worn on a three-dimensional form.Design/methodology/approachFour turnout suits with chest ease allowances of 6″, 8″, 10″ and 12″ were evaluated using an ANDI dynamic sweating thermal manikin. The average predicted manikin THL of each ensemble was calculated from the thermal and evaporative resistance measurements. A three-dimensional (3D) body scanner was utilized to calculate the distance and volume of clothing air gaps between the base layer and each turnout suit.FindingsResults demonstrate that reductions in upper body ease measurements trend towards statistically significant increases in THL, to a point, with fit limitations being reached before benefits can be significantly realized. An increase in standard chest ease measurements significantly decreased heat loss, even when forced convection from movement was considered.Originality/valueThis is the first article of its kind to explore the relationship between garment ease and predicted manikin THL, especially for fire service protective clothing. Findings indicate a valid recommendation for turnout gear designers and manufacturers to optimize clothing fit to improve breathability and potentially reduce incidents of heat strain in the fire service.

A virtual measurement method for evaluating the gear radial composite deviation based on point cloud data

Radial composite deviation is an important index to evaluate the precision of gear transmission, and its detection method is also an important trend of gear detection in industrial development. The ability to predict radial composite deviation while obtaining geometric deviation of gears is a key challenge in advancing intelligent online inspection within gear manufacturing workshops. This study presents a virtual measurement method for determining gear radial composite deviation using point cloud data. The method involves using an optical three-dimensional scanner to capture tooth surface cloud data, determining tooth profile deviation, and applying reverse engineering technology to reconstruct the gear model, the variation curve of gear center distance is determined by simulating, allowing for the calculation of the total radial composite deviation and tooth-to-tooth radial composite deviation. In comparison to actual measurement, the virtual measurement method is generally reliable. It can effectively illustrate the overall trend of center distance variation and has good interpretability for predicting radial composite deviation results. This method reduces the dependence on the specialized gear measuring instrument and addresses the critical issue of simultaneously obtaining tooth profile deviation and radial composite deviation.

ANALYSIS OF MODERN METHODS FOR OPTIMIZING TECHNOLOGICAL PROCESSES IN MACHINE-BUILDING PRODUCTION USING ARTIFICIAL INTELLIGENCE

This article explores the integration of artificial intelligence (AI) into machine-building production processes, focusing on the optimization of gear production for KrAZ trucks. Through a detailed analysis of AI applications in various industries and a review of relevant literature, the study identifies key opportunities and challenges in implementing AI technologies in mechanical engineering. The research presents a comprehensive examination of the benefits of AI-driven systems in improving production efficiency, quality control, and predictive maintenance. A case study on automated gear grinding quality control demonstrates how AI, coupled with advanced sensors and machine learning algorithms, enhances process precision and reduces defects. Results demonstrate the effectiveness of AI-driven systems in improving precision, reliability, and cost-effectiveness in gear manufacturing, with an observed accuracy rate of approximately 95% or higher. Also highlights a precision rate of ±0.005 mm in gear tooth surface finishing, leading to consistent gear performance and reliability. Additionally, AI-driven predictive maintenance strategies are shown to predict equipment maintenance needs with up to 90% accuracy, maximizing productivity and reducing maintenance costs by up to 30%. Moving forward, further research and implementation efforts should focus on selecting and integrating appropriate AI systems into existing production processes, to maximize efficiency and innovation within the machine-building industry. Keywords: artificial intelligence, gear grinding, quality control, data analysis, automation

New deterministic model for calculating mesh stiffness and damping of rough-surface gears considering elastic–plastic contact and energy-dissipation mechanism

For a long time, meshing parameter calculations and dynamic modeling of gear systems have assumed smooth tooth surfaces, disregarding the impact of actual three-dimensional (3D) microscopic topography. Based on elastic–plastic contact and energy-dissipation mechanisms, this work developed a comprehensive deterministic model that integrates 3D rough surface modeling, reconstruction, and contact analysis, for calculating the time-varying mesh stiffness (TVMS) and mesh damping (TVMD) of deterministic rough-surface gears. Distinct from fractal and statistical models, the deterministic model analyzes deterministic, real 3D rough surfaces rather than simple surfaces defined by a few parameters. Utilizing stochastic process theory, different-topography surfaces are obtained using height and spatial features and reconstructed employing watershed algorithm and ellipsoidal asperity fitting. Subsequently, a deterministic elastic–plastic contact model based on equivalent rough curved-surface contact is constructed, emphasizing local contact states and energy dissipation for calculating contact stiffness (CS) and damping (CD) of gears. Accordingly, a meshing characteristics analysis model is established for calculating TVMS, TVMD, and load sharing ratio (LSR). Experimental validation and comparisons with several statistical and gear contact models demonstrate the effectiveness, reliability, and superiority of the proposed deterministic model. Multi-parameter impact analysis reveals small Sq (meaning low roughness Sa) and Ssk and high load correlate with increased CS and TVMS, while CD and TVMD depend on their interaction and hardness. Overall, by bridging the micro-surface topography and macro-meshing parameters, our model provides essential insights for the design and manufacturing of high-performance gear to reduce vibration and noise.