Automotive Manufacturing Research Articles

Workload Analysis and Green Human Resource Management on Employee Performance

The manufacturing industry sector is an industrial sector in Indonesia that is developing and contributes to the industry nationally, therefore companies engaged in this field must be able to face competition which is the impact of the growing industry. So that human resources are an important part of the company, if the human resources are lacking, the company's target in achieving its goals will not be carried out PT. ASTRA INTERNATIONAL Tbk Isuzu Sukabumi - Bogor. Tbk Sukbumi -Bogor is a company engaged in the automotive manufacturing industry that has problems with employee performance. This study aims to find out whether workload and green human resource management have an influence and impact on employee performance at PT. ASTRA INTERNATIONAL Tbk Isuzu Sukabumi - Bogor. The research method used is a quantitative method using descriptive and associative methods. The data source used by conducting interviews and distributing questionnaires as a tool in obtaining data and samples was used namely saturated sampling to 31 respondents of PT. ASTRA INTERNATIONAL Tbk Isuzu Sukabumi - Bogor by using a differential semantic measurement system. Then the data that has been obtained is carried out several tests such as validity and reality tests, then a classical assumption test is carried out, which is then analyzed with the help of SPPS 23 software to answer the hypothesis in this study. The results of the study show that there is a positive and significant influence between workload and green human resource management on employee performance and by reducing workload and implementing green human resource management can improve the performance of employees of PT. ASTRA INTERNATIONAL Tbk Isuzu Sukabumi - Bogor.

Optimizing Continuous Improvement in Automotive Manufacturing through SPC and Q-DAS Integration

Optimizing Continuous Improvement in Automotive Manufacturing through SPC and Q-DAS Integration

Effects of deformation-induced BCC martensitic transformation on uniaxial ductility and biaxial stretchability in metastable ferrous medium-entropy alloys

This study investigated the effects of deformation-induced martensitic transformation (DIMT) on the stretchability and fracture behavior of thin sheets made from ferrous medium-entropy alloys (MEAs). Analyses of punch load-stroke curves from Erichsen tests revealed that DIMT occurred in the 60 at% Fe MEA, 64 at% Fe MEA, and 304 stainless steel (60Fe, 64Fe, and 304SS alloys, respectively). This DIMT affects necking onset, uniform elongation, and the Erichsen index (EI) under diverse stress conditions. DIMT plays a significant role in strain hardening and mechanical instability during uniaxial tests, enhancing strain hardening through martensite formation and also initiating necking due to non-uniform deformation. Particularly in 64Fe, DIMT-induced early necking resulted in reduced uniform elongation. On the other hand, biaxial Erichsen test results demonstrated further strain hardening due to martensite-induced strain accommodation, leading to enhanced resistance to deformation during biaxial loading. The distinctive shapes of punch load-stroke curves in biaxial tests, compared to stress-strain curves from uniaxial tensile tests, are a result of the interaction between DIMT and stretching directions, as well as its alloy-dependent phase stability. In 60Fe, transformed martensite contributed to strain hardening and delayed necking initiation, while extensive martensite transformation in 64Fe enhanced strain hardening further. This understanding of the complex correlation between DIMT, strain hardening, and mechanical instability holds potential for alloy optimization and developing processing strategies, applicable to automotive manufacturing and structural engineering industries.

Influence of hybrid nanofiller on elastic behavior and stiffness of basalt/E-glass MWCNTs/SiO2 hybrid nanocomposites

Sustainable material development techniques help in finding and employing sustainable materials without compromising quality. Composite materials are crucial in structural design, automotive manufacture, and aeronautical engineering. Advanced materials that use reinforcement and filler ingredients must be developed strategically to improve strength and performance. Hence, this study develops hybrid nanocomposites with hybrid nanofillers (MWCNTs and SiO2) and hybrid fibers (basalt and E-glass) and optimizes the competition to maximize elastic behavior and stiffness. Using a hand layup approach, composite samples were made by altering mass fractions of two filler materials (0%, 1%, 1.5%, and 2% by weight) and epoxy matrices (40%, 38%, 37%, and 36%). Shore D hardness and dynamic mechanical analysis (DMA) were used to evaluate the composites. The storage modulus, loss modulus, and damping coefficients are examined using DMA. Specifically, the largest storage modulus is 4.86 × 1010 Pa at 61 °C, while the peak loss modulus is 1.01 × 1010 Pa at 80 °C. The highest damping coefficient is 0.25. Note that 1.5% MWCNTs and SiO2 filler materials independently contribute to the excellent storage and loss modulus. However, an outstanding damping coefficient was achieved without filler materials. The highest achieved shore D hardness value is 88. Filler materials are used to achieve this high hardness.

Improving the corrosion resistance of aluminum alloy welds through powder-ball combined ultrasonic shot peening

Aluminum alloy 5052 is used extensively in various industries, including aerospace, shipbuilding, and automotive manufacturing. Components made from this alloy often require welding treatments; however, in marine environments, these welds are susceptible to corrosion, which affects their durability and service life. In this study, power-ball combined ultrasonic shot peening (USSP) was used for surface-strengthening 5052 aluminum alloy welds. The resulting surface characteristics and corrosion resistance were examined, and the compared to the untreated sample, the USSP-treated sample showed a shift in the stress state from residual tensile stress (31.4 MPa) to residual compressive stress (−257.5 MPa). Immersion and electrochemical corrosion experiments confirmed that the formation of residual compressive stress and a gradient structure on the surface enhanced the corrosion resistance, which was substantiated by detailed characterization. The corrosion rate of the treated aluminum alloy weld sample (7.18 μm/year) decreased by 72.90 % compared with that of the untreated sample. The study findings indicate that the powder ball combined USSP is a potential method for improving the corrosion resistance of aluminum alloy welds in marine environments.

Achieving Work-Life Balance: A Tan Sri Syed Zainal Experience

One Saturday morning in 2005, Syed Zainal sat at his desk contemplating the career decision he would have to make over the weekend. At 38, Syed Zainal was Chief Executive Officer (CEO) at HICOM Holdings Berhad, a Malaysian automotive manufacturing company, for ten years. Perodua just offered Syed Zainal a promotion to CEO, a position that would make him responsible for the entire division. Normally, Syed Zainal would have been blissful by such an opportunity, but he worried about its impact on his already fatigued personal life. Since his last promotion, he has struggled to balance an increasingly demanding workload with his responsibilities at home. Syed Zainal explained: “I have worked my whole career, and until now, I have never had any issues balancing work and home. However, things started spinning a bit out of control after my last promotion. At first, I thought I could handle the longer hours and more frequent travel, but it became a real drag on the family after a while. Then, two kids need my attention. That is when I realized it was time to change the situation. Syed Zainal has mixed feelings about accepting the promotion.” Over the past several years, Syed Zainal has taken steps to get his schedule under control. He and his wife Jan agreed that things were better. Nevertheless, another promotion would invert their lives all over again. As CEO, he could expect to be busier than before. It actually worried him. Syed Zainal found it hard to decide about accepting the promotion. He knew that the CEO of Perodua expected him to accept; in fact, he had emphasized that he had no second choice.

A Novel Approach to Construct Finite Automata Using Grid and Product Automata

This research aims to utilize an organized grid-based strategy to make the development of complex Finite Automata easier. Product Automata are used to merge many automata into a single automaton to integrate various computing processes. Combining these methodologies provides novel methods of improving the scalability and efficiency of automata building, broadening the field of research for automata theory and its applications. The scalability of this developed automated system will benefit sectors such as automotive production and logistics. The results indicate considerable improvements in construction time, memory usage, scalability, and resilience compared to older approaches. The performance of the developed method, as measured by construction time, memory utilization, scalability, robustness, application range, and complexity, is 25% to 50% higher than that of traditional methodologies in the literature.

Analyzing the Suitability of Vehicle Telematics Data as a Surrogate Safety Measure for Short-Term Crashes

Traffic safety analysis relies heavily on the comprehensiveness of traffic crash data. However, crash occurrences are rare events. Researchers have sought alternative measures closely linked to crash occurrences, known as surrogate safety measures, to address this challenge. The advent of vehicle telematics has introduced a valuable source of data, consisting of time-stamped positional information of vehicles, facilitated through telecommunication networks. Wejo Data Services Inc. collects vehicle telematics data through collaboration with various automotive original equipment manufacturers (OEMs) to furnish connected vehicle data along with driver event variables, such as braking and acceleration. This study seeks to investigate the relationship between hard-braking events and the incidence of total crashes and peak period crashes across different facility types using analysis of variance and negative binomial models. The results show a strong correlation between hard braking and crash frequency. The ratio of hard-braking events to crashes exhibits notable variations across peak hours, off-peak periods, and nighttime. Further, the coefficient of hard braking is significantly higher on freeways compared with non-freeways. The model performance of different short period models improved better than the extent of improvement in total crash model after hard braking was introduced as an explanatory variable. The marginal effects of hard braking on crash frequency on freeways are consistently higher than those in non-freeway segments.

An offset-transformer hierarchical model for point cloud-based resistance spot welding quality classification

Resistance spot welding (RSW) is a widely used welding technology in automotive manufacturing, and weld nugget quality is closely related to the quality of the vehicle body. Offline random checks are largely relied on the quality inspection of weld nuggets, but they have low efficiency and high cost. To address this issue, this paper proposes a deep learning model for RSW weld nugget classification, named the offset-transformer hierarchical model (OFTFHC), which is based on the point cloud data of its appearance shape. OFTFHC uses a hierarchical network structure to gradually expand the receptive field. A local feature module is introduced to extract local features from the point cloud, effectively enabling the recognition of the fine structural features of the resistance spot weld point cloud. A residual ratio module, which is based on MLP_MA and uses max and average functions for feature enhancement, is designed to adapt to the complex spatial structure of the point cloud. The offset-transformer structure is used to learn global context features, thereby enhancing the global feature extraction capability. Through classification experiments on RSW weld nuggets across 5 categories with a total of 1050 samples, OFTFHC achieved an average accuracy of 80.6 %, outperforming existing models. This demonstrates the effectiveness and superiority of the method, making it highly suitable for weld nugget quality control in automotive automation production lines.

Second-hand car price prediction based on multiple linear regression models

With the advancement of the automotive manufacturing industry and the convenience of public transportation, the second-hand car market continues to expand. To comprehensively evaluate the price of used cars considering various factors, there is an urgent need for a computational model based on big data and machine learning. This article aims to fulfill this requirement, this article introduces a multiple linear regression model based on machine learning technology, which is applied to predict the prices of second-hand cars. In this study, the author digitized categorical variables and removed factors irrelevant to numerical variables using a dataset containing nearly 1500 samples from the second-hand car market. By constructing a multiple linear regression model with independent variables such as insurance validity, fuel_type, seats, ownership, transmission, mileage (kmpl), engine (cc), kms_driven and registration year with price (unit: ten thousand) as dependent variable. The root mean square error (RMSE) was finally obtained as 13.939.

Spark Timing Optimization through Co-Simulation Analysis in a Spark Ignition Engine

The automotive industry is experiencing radical changes under the pressure of institutions that are increasingly reducing the limits on CO2 and pollutant emissions from road vehicles powered by internal combustion engines (ICEs). A way to decarbonize the transport sector without disrupting current automotive production is the adoption of alternative fuels for internal combustion engines (ICEs). Hydrogen is very attractive, thanks to the zero-carbon content and very high laminar flame speed, allowing for extending the lean burn limit. Other alternative fuels are methanol and ethanol. This work deals with the conversion of a small-sized passenger car powered by a three-cylinder spark ignition (SI) engine for the use of alternative fuels. In particular, the spark timing has been optimized to improve the fuel economy under every operating condition. The optimization procedure is based on the MATLAB/Simulink® R2024a-GT-Power co-simulation analysis and minimizes the fuel consumption by varying the spark timing independently for each cylinder. In particular, at full load, the algorithm reduces the spark timing only for the cylinder in which knock is detected, reducing fuel consumption by about 2% compared to the base calibration. This approach will be adopted in future activities to understand how the use of alternative fuels affects the ignition control strategy.

Synchronizing the Supply of Components for Automotive Assembly amid Chip Shortages and Other Supply Delays

The push for more battery-powered electric vehicles, the COVID-19 pandemic, and other global supply chain destabilizing events (e.g., the war in Ukraine) have made it necessary for manufacturers to consider innovative approaches to sourcing and materials management. This study assesses the value of sharing delivery due date updates, which are then used to convert spent time into a fraction of the expected total time for order fulfillment (i.e., progress updates), to synchronize the delivery of components for an automotive manufacturer who, amid long and variable lead times for semiconductor chips, maintains a strategy of waiting for the delivery of all needed parts before commencing production. Having progress updates in a fractional form puts numerical bounds (i.e., 0% to 100%) on the shared information, and this facilitates closed-form analytical comparisons. We develop analytical models to show decreases in expected assembly-related costs based on the progress update information shared between two suppliers—one supplier has a shorter and more reliable order fulfillment lead time than the other. When there are more than two suppliers, we use a simulation model to estimate the expected value of sharing progress updates. Our results show that increasing the frequency of shared progress updates, and having more suppliers share progress updates, results in increased cost-savings percentages. However, the opposite occurs with increasing uncertainty in suppliers’ delivery lead times. The computational study provides support for the existence of a critical mass level of suppliers needed to achieve a given percentage cost saving. This study can help automakers to make informed decisions on encouraging information sharing among suppliers, by first creating a critical mass of suppliers to share progress updates. Our investigations also help show the conditions in which to best leverage such information sharing strategies while waiting for the delivery of all needed components prior to production.

Improving Lead Time through Lean Manufacturing: A Case Study

Lean manufacturing is a well-established methodology aimed at optimizing production by eliminating waste, enabling industries to thrive in a globally competitive environment. This paper presents a case study of a well-known automotive manufacturing industry on the axle process. This article aims the Value Stream Mapping (VSM) methodology was used in the axle process to reduce lead time by producing quality products with a reduction in non-value-added activities. The current state of the axle process was created using industry data from the past six months. Significant improvements were realized following the successful implementation of VSM, including a reduction in the lead time from 89.50 hours to 50.55 hours. The new state map was also created after implementing the improvements. The results illustrated that the VSM increased the effectiveness by 56.48% in the axle process.

Optimization of GMAW Processes in Robotic Welding: A Case Study from Automotive Manufacturing

The optimization of Gas Metal Arc Welding (GMAW) processes in robotic welding has become crucial for enhancing efficiency and quality in automotive manufacturing. This paper explores the integration of advanced robotic welding technologies, focusing on the use of the KUKA KR8 L8 Arc HW robot in GMAW applications. By leveraging artificial intelligence and sensor integration, this study demonstrates significant improvements in welding precision and process stability. Key advancements include the use of geometric and process sensors for real-time adaptive control, and the implementation of Fronius CMT for superior arc control and penetration. Detailed case studies from automotive manufacturing illustrate the practical benefits of these technologies, showcasing enhanced productivity, reduced cycle times, and improved weld quality. The findings underscore the importance of continuous innovation and optimization in robotic welding processes to meet the evolving demands of the automotive industry.

The Relationship Between Stress and Burnout: A Sample of Automotive Factory Workers

The purpose of this research is to determine the relationship between stress and burnout in employees of an automotive factory. This research was conducted descriptively with 306 participants at Sango Automotive Products Industry and Trade Joint Stock Company in Kocaeli/Türkiye between April and July 2021. Data were collected using the Personal Information Form, Perceived Stress Scale and Burnout Scale-Short Version. The mean Perceived Stress Scale score of participants was 25.11±7.39; The average score of the Burnout Scale were 29.69±12.61. A statistically significant positive relationship was determined between the mean Perceived Stress Scale scores and Burnout Scale scores of participants (r=0.67; p

Company Valuation and Influencing Factors: A Study of Automotive and Component Manufacturers Listed on the Indonesia Stock Exchange

The company's value is crucial as it reflects the company's performance, which can influence investors' perception of the company. The aim of this research is to determine the influence of profitability, company size, liquidity, and managerial ownership on company value in the automotive and component manufacturing sub-sector on the Indonesian Stock Exchange (IDX) for the years 2017-2021. The population in this study consists of manufacturing companies listed on IDX from 2017 to 2021, totaling 13 companies, with a sample size of 12 companies selected through purposive sampling method. This study employed multiple linear regression analysis to investigate the factors influencing company value. The results reveal that profitability and managerial ownership have a positive and significant impact on company value, while company size has no significant effect. Interestingly, liquidity exhibits a negative and significant relationship with company value. These findings suggest potentially important areas for future research. Expanding the study to include additional variables, such as leverage, capital structure, and dividend policies, could provide a more comprehensive understanding of the determinants of company value

Current Problems in a New Distribution Center Under Labor Shortage

With economy globalization, the distribution center becomes very popular in the supply chain. A well-equipped distribution center empowers a company to deliver products and service to customers whenever it is required. Under-staffing is becoming a severe issue among a lot of distribution centers, which directly affects normal operations including unloading and loading, sorting and shipping activities, and these factors lead to a poor on-time delivery rate to customers. In this paper, we take an automotive accessories manufacturer and distributor as an example. We analyze its existing problems by comparing the corresponding process and data.

Practical Aspects of the Organization of Ergonomics Committees in the Context of the Quality of Ergonomic Activities Undertaken in Manufacturing Enterprises

Theoretical background: In order to systematize ergonomic activities in the enterprise, some of them decide to establish ergonomics committees whose task is to solve problems in this area and also to propose new, often innovative solutions for implementation. The structures of these units often include employees from different departments who have a different view of ergonomics depending on the position they hold. However, the organization of ergonomics committees can cause many problems due to the lack of top-down guidelines for their activities (each company must establish its own rules). In scientific research on the ergonomic aspects of projects, there is a tendency to look for factors that favor the diffusion of ergonomic issues in their implementation. One such factor may be the creation of an ergonomics committee to pursue ergonomic goals. Their activities are not described in detail in the literature (there are no practical guidelines for their functioning), which is why the topic is discussed in this article. Purpose of the article: The main goal of this article is to present propositions for actions that can be taken to systematize the functioning of the ergonomics committees and to link this task with the quality of ergonomics management in manufacturing enterprises. The aim of the article is also to describe, using a practical examples, various aspects of the operation of ergonomics committees and to indicate guidelines for their establishment and activities. Thus, the article aims to fill the research gap in the field of creating ergonomics committees. Research methods: The research used the interview method with participants of ergonomics committees from companies from various industries. The questions were asked in the following groups: organization and functioning of the ergonomics unit in the enterprise and assessment of the effects of the ergonomics team’s activities. The respondents were participants of the ergonomics committees, which was appointed at least 2 years earlier, the industries represented by the respondents are: automotive (2 companies) and furniture production. Data obtained in three selected enterprises (through informal interviews) where such committees operate, as well as a literature review in this area, were used to formulate these suggestions. The results of the undertaken research allowed for the identification of practical aspects of the functioning and organization of the ergonomics committees. This is an innovative area of research due to the fact that few scientific studies describe such units and guidelines for their practical implementation. Main findings: The main result of the undertaken research was to indicate the categories in which the activities of ergonomics committees should be considered and to provide practical guidelines for their activity. These guidelines are presented as structured areas for consideration when establishing an ergonomics committee: (1) establishing the principles of operation and reporting; (2) determining the composition of the committee; (3) determining the scope of activity of the committee; (4) providing appropriate training for committee’s representatives; (5) support for the committee’s activities. The most important conclusion from the undertaken research is the indication that each enterprise must plan the operation of the committee taking into account its internal conditions. The conclusions from the conducted research were supplemented with indications of directions for further research into the conditions for the functioning of ergonomics committees in manufacturing companies.

Dampak Just in Time pada Inventory Management Studi Kasus pada Industri Manufaktur Automotive

The purpose of this study is to determine the Impact of Just In Time on Inventory Management Case Study in the Automotive Manufacturing Industry by determining the key factors that are fundamental to just in time practices. This research was conducted in two automotive manufacturers serving the sector hereinafter referred to as Company A and Company B, as these companies cannot be named, for this reason, the identity of these companies cannot be revealed. The approach used here is a mixed approach of quantitative research and qualitative methodology. From the study it can be concluded that organizations can have lower performance or efficiency in managing or controlling inventory, when not implementing JIT or Just-Time practices. In addition, we can also see how JIT affects inventory management practices in organizations in a positive way. This further leads to a positive perception of business performance from both employees and management of the organization. The results for Company A show better performance with cost effective performance through the implementation of the JIT system, with employees being more aware of the inventory management practices in place and the changes and benefits being transmitted to the system

Strategic workforce and project planning for engineering automotive production systems: tackling the transition to electric vehicles

Car manufacturers are electrifying their product portfolios as a reaction to restrictions imposed on car emissions. This leads to additional product introductions of battery electric vehicles to the existing portfolio of internal combustion engine vehicles. For each introduction, car manufacturers must engineer the corresponding production systems. The engineering of these production systems is executed as projects that consist of designing, building, installing, and testing, requiring different types of engineers. Car manufacturers deploy an engineering workforce and outsource work to engineering service providers. In practice, workforce planning, project planning, and outsourcing are performed sequentially using spreadsheets. However, portfolio electrification increases the complexity of planning, calling for more advanced methods. We formulate an integrated workforce and project planning problem (mixed-integer programme) to minimise outsourcing and perform an experimental study using realistic data representing different prevalent strategies for portfolio electrification. Our approach significantly reduces outsourcing and increases workforce utilisation compared to current industry practice for a wide range of workforce sizes. Furthermore, we investigate the benefit of partially aligning the current practice with our integrated approach. Optimising outsourcing alone while maintaining the sequential planning process reaps 70% to 80% of the potential benefits, and integrating workforce or project planning achieves up to 90%.