Automotive Manufacturing Research Articles

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%.

Improving Productivity in Automotive Manufacturing: A Combined Approach of Root Cause Analysis and Sem Models

Improving Productivity in Automotive Manufacturing: A Combined Approach of Root Cause Analysis and Sem Models

Qualitative analysis about best practices and project management tools in intralogistics

Project management in automotive manufacturing is crucial due to the dynamism in updating operating models and high investment in the supply chain and logistics. This article presents a systematic literature review of 134 articles (2011-2023) from four relevant databases (IEEE, ScienceDirect, Scopus, Taylor & Francis) with the purpose of exploring the best practices in project management applied in intralogistics activities. Analyzing aspects such as country, management methods and techniques, solution levels in internal logistics projects, business line, among other items. The findings will identify opportunities that contribute to academic indicators and the generation of proposals in the automotive industry in Mexico, focused on the fulfillment of projects and management according to their context.

Modeling Rate Dependent Volume Change in Porous Electrodes in Lithium-Ion Batteries

Automotive manufacturers are working to improve individual cell, module, and overall pack design by increasing the performance, range, and durability, while reducing cost. One key piece to consider during the design process is the active material volume change, its linkage to the particle, electrode, and cell level volume changes, and the interplay with structural components in the rechargeable energy storage system. As the time from initial design to manufacture of electric vehicles decreases, design work needs to move to the virtual domain; therefore, a need for coupled electrochemical-mechanical models that take into account the active material volume change and the rate dependence of this volume change need to be considered. In this study, we illustrated the applicability of a coupled electrochemical-mechanical battery model considering multiple representative particles to capture experimentally measured rate dependent reversible volume change at the cell level through the use of an electrochemical-mechanical battery model that couples the particle, electrode, and cell level volume changes. By employing this coupled approach, the importance of considering multiple active material particle sizes representative of the distribution is demonstrated. The non-uniformity in utilization between two different size particles as well as the significant spatial non-uniformity in the radial direction of the larger particles is the primary driver of the rate dependent characteristics of the volume change at the electrode and cell level.

The growing use of flax fibre in transport

Automotive and mobility manufacturers continue to evaluate flax and hemp materials across their model ranges as they look to reduce the overall environmental impact of their products, while taking advantage of their technical properties, says the Alliance of European Flax Linen & Hemp.

Pointwise profile monitoring considering covariates based on Gaussian process

In the intelligent manufacturing process, sensors are increasingly becoming an important means of measurement and data acquisition. Profile data from sensors are generally huge, irregular, and correlated. Meanwhile, profiles are usually affected by many external factors, which are referred to as covariates in this paper. Existing statistical process control methods are mainly based on statistical models, which have many limitations in dealing with such complex profile data. Motivated by the real life problem of industrial busbar temperature monitoring, this paper proposes a nonparametric pointwise profile monitoring scheme for unbalanced data considering time varying covariates. The developed Gaussian process-based model provides flexibility for predicting autocorrelated profiles. To incorporate time varying covariates, the Gaussian process model kernel is modified by an automatic relevance determination structure. The control chart is then constructed based on the difference between the observed and predicted profiles. Instantaneous anomalies within a profile can be detected by pointwise monitoring without waiting for the entire profile data collection. The effectiveness and applicability of the proposed monitoring scheme are validated by both simulations and a real case of busbar temperature monitoring in the workshop of an automotive manufacturer.

A novel and efficient mathematical optimization model for multi-stage assembly flow shop considering post-processing

ABSTRACT We addressed the multistage assembly flow shop problem with post-processing and makespan minimization, a production environment commonly encountered in diverse industries such as automotive, dental, medical equipment, and clothing manufacturing. In this context, we presented an innovative mixed-integer linear programming model with a position-based strategy. Our proposed formulation demonstrated remarkable efficiency when compared to the model of the literature. It achieved optimal solutions in 77.16% of instances, with an average optimality gap of 10.59%. This study constitutes a significant contribution to the efficient resolution of a practical and frequently encountered scheduling problem that has received relatively limited attention in existing literature. The findings highlight the crucial role of mathematical optimization models as valuable decision-making tools for scheduling within the addressed production system.

Accelerating Brand Value: The Role of CSR in Shaping Automotive Brand Reputation and Consumer Preferences

Objective - The increasing concern surrounding automotive product recalls has captured the attention of stakeholders due to the significant potential risks faced by consumers. These recalls have a profound impact on the public perception of automakers. While numerous studies have investigated the relationship between corporate social responsibility (CSR), reputation, and consumer behaviour, there has been a notable lack of research on the influence of CSR and reputation on consumers' intention to purchase automotive brands specifically. To address this research gap, a comprehensive quantitative study was conducted, involving the distribution of questionnaires to 419 automotive customers in Malaysia. Methodology/Technique - The collected data from 419 automotive customers in Malaysia were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM), which allowed for the testing and confirmation of both measurement and structural models. Findings – Economic responsibility, legal and ethical responsibility, and philanthropic responsibility were found to significantly affect organizational reputation. However, only economic responsibility and philanthropic responsibility influence the intention to purchase when mediated by organizational reputation. By examining the impact of CSR and reputation on Malaysian customers' intention to purchase, this study provides valuable insights into an underexplored area of research. Novelty - This study contributes to the existing literature by specifically focusing on the influence of CSR and reputation on consumers' intention to purchase automotive brands in Malaysia. It utilizes robust quantitative methods to analyse data from a sizable sample of automotive customers, shedding light on an important aspect of consumer behaviour in the automotive industry that has been relatively understudied. Type of Paper: Empirical JEL Classification: M14, M31 Keywords: Brand Value, Corporate Social Responsibility; Brand Reputation; Purchase Intention. Reference to this paper should be made as follows: Ismail, Z; Mohamed, W.N.W. (2024). Accelerating Brand Value: The Role of CSR in Shaping Automotive Brand Reputation and Consumer Preferences, J. Mgt. Mkt. Review, 9(2), 76 – 86. https://doi.org/10.35609/jmmr.2024.9.2(3)

Binary Pareto Multi-Objective Whale Optimization Algorithm for Power Plant Maintenance Scheduling

Maintenance scheduling is a critical challenge in all major industrial sectors, such as aeronautics, automotive manufacturing, and power generation plants. The goal of power plant maintenance scheduling is to establish a schedule plan for carrying out preventive maintenance shutdowns for each unit within a defined planning horizon. In this paper, a mathematical model for optimizing the maintenance schedule was established to maximize the supply, minimize fuel costs, and CO2 emissions from generating units. A developed Whale Optimization Algorithm called Binary Pareto Multi-Objective Whale Optimization Algorithm BPMOWOA is proposed and implemented to find optimal maintenance scheduling for a power plant. The proposed algorithm uses two different approaches. The first approach includes binary encoding, in which each generating unit and each time interval are represented in binary form. Then, in the second approach, a fixed-sized repository is integrated into the WOA for saving and retrieving the Pareto optimal solutions, and a grid mechanism is integrated into the WOA to maintain diversity in the population of non-dominated solutions. A case study was conducted on fourteen generating units adapted from a real-world power plant to validate the algorithm's efficiency. The results illustrate that the proposed algorithm was effective in optimizing the maintenance schedule in terms of coverage and non-dominated solution and improved the power plant performance by increasing electricity generation by 11.48% and decreasing fuel expenses by 6.56%, which are the main goals of the considered power plant. Index Terms— maintenance scheduling, multi-objective, whale optimization algorithm, power plant.

Economic impact of ACES trends on the automotive value chain: a forecast exploratory study of the Chinese automotive industry in 2030

In the context of green transportation, the automotive industry is undergoing a revolution in autonomous, connected, electric, and shared (ACES) vehicles. ACES vehicles have a relatively short history and there is limited relevant market data available. Therefore, quantitative research on the economic impact of ACES trends remains a new area of exploration. The purpose of the paper is to explore the economic impact of ACES trends on the automotive value chain, with a specific focus on the production and aftermarket segments. In the paper, a detailed quantitative analysis of the installation scale and the market size of Chinese automotive production as well as the income changes of Chinese automotive aftermarket in 2030 is conducted. The findings show that the new markets for power batteries, electric powertrains, sensors, in-vehicle software and chips are created, thereby delivering more value to the business. While the ACES trends are expected to decrease the average aftermarket income per vehicle, the growth of the vehicle stock suggests significant potential for the development of the automotive aftermarket in 2030. Our research contributes by offering a business perspective on the impact of ACES trends. The quantitative insights presented are timely and crucial for all the stakeholders along the value chain, enabling them to adapt and thrive in the dynamic automotive landscape and align their strategies with the transformative ACES trends.

An Approach to Enhancing Manufacturing Throughput Capability through System Design

<div>This article presents a new approach that integrates and balances cycle time and reliability considerations during system design to enhance manufacturing system capability, with direct applicability to automotive and high-volume manufacturing. The method addresses system throughput capability in three steps without complex mathematical modeling. The steps are: (1) managing workload cycle times, (2) considering real-world operational availability, and (3) achieving capability balance. Through analytical estimation and discrete event simulation of an example manufacturing system, this approach’s application shows a substantial increase in throughput capacity compared to a traditional workload-based design. This throughput-centric design approach, serving as a valuable tool for manufacturing system synthesis aimed at maximizing throughput, can apply to volume production systems to enhance throughput capacity through system design.</div>

TOWARD ROBUST IN-CAR CONNECTIVITY: SIMULATIVE INSIGHTS INTO THE BEHAVIOUR OF SINGLE PATCH AND 2x2 ARRAY ANTENNAS FOR 2.4 GHZ WI-FI APPLICATIONS

The incessant demand for reliable and robust in-car connectivity drives the evolution of automotive wireless communication. In this pivotal research, we ventured into the realm of 2.4 GHz Wi-Fi applications, emphasising refining antenna designs that focused specifically on the Bio-composite material single patch and the 2x2 array configurations. Our simulations, executed meticulously in CST Microwave Studio, yielded noteworthy findings. The single patch antenna, fortified with a quarter-wave feeding line, delivered an efficiency of 51% and a gain of 2.83 dBi. While promising, its bandwidth limitations beckoned a deeper dive into alternative configurations. Subsequently, our exploration of the 2 x 2 array antenna, enriched with a power divider, stood out as a beacon of improvement. Notably, it exhibited a significant gain elevation, registering at 5.79 dBi. This uptick underscores the 2 x 2 array's superiority over its single-patch counterpart in amplifying in-car Wi-Fi strength and hints at its potential to set a new benchmark in automotive wireless solutions. In synthesis, this research does more than just present empirical data; it offers a roadmap for automotive manufacturers and WiFi solution providers, leading them towards more efficient and robust in-car wireless ecosystems. Beyond its immediate implications, our study lays a strong foundation for future explorations, potentially steering the discourse towards more intricate array antenna designs tailored for vehicular environments.

Impact of Humidity and Temperature on Quality of Automotive Products

In the automotive industry, maintaining optimal quality and performance for electronic components used in vehicles is crucial to meet consumer demands and regulatory standards. Humidity and temperature are pivotal environmental factors affecting automotive systems, influencing all essential electrical components. This article provides a study elucidating their effects on reliability, durability, and customer satisfaction. Additionally, it discusses the significance of controlling temperature and humidity in production areas and quality laboratories, highlighting their crucial role in ensuring the highest standards of quality and reliability in automotive manufacturing and analysis processes.

Successful Foreign Direct Investment Through the Development of Parts Supply Industries in the Host Country: A Study of India's Automobile Manufacturing Sector

Several large multinationals and a few local assemblers dominate the Indian automobile industry. The largest multinational, Maruti Suzuki, entered the Indian automobile industry with a policy of developing local automotive parts manufacturers to achieve high local content ratio. This study seeks to determine the extent to which foreign direct investment (FDI) in host countries contributes to the growth of automobile parts manufacturers. We use district‐level panel data from 2000 to 2008 to assess the linkage between the production of major automobile assemblers and the development of automotive parts suppliers located in the same and adjacent districts to those assemblers. Our regression results show the heterogeneity of the linkages, suggesting that the formation of industrial clusters by local parts suppliers and the expansion of their production capacity are likely to be key determinants of the success of FDI in the Indian automobile industry, rather than relying on in‐house parts production or imports.

Enhancing quality 4.0 and reducing costs in lot-release process with machine learning-based complaint prediction

PurposeThis study proposes a machine learning framework to predict customer complaints from production line tests in an automotive company's lot-release process, enhancing Quality 4.0. It aims to design and implement the framework, compare different machine learning (ML) models and evaluate a non-sampling threshold-moving approach for adjusting prediction capabilities based on product requirements.Design/methodology/approachThis study applies the Cross-Industry Standard Process for Data Mining (CRISP-DM) and four ML models to predict customer complaints from automotive production tests. It employs cost-sensitive and threshold-moving techniques to address data imbalance, with the F1-Score and Matthews correlation coefficient assessing model performance.FindingsThe framework effectively predicts customer complaint-related tests. XGBoost outperformed the other models with an F1-Score of 72.4% and a Matthews correlation coefficient of 75%. It improves the lot-release process and cost efficiency over heuristic methods.Practical implicationsThe framework has been tested on real-world data and shows promising results in improving lot-release decisions and reducing complaints and costs. It enables companies to adjust predictive models by changing only the threshold, eliminating the need for retraining.Originality/valueTo the best of our knowledge, there is limited literature on using ML to predict customer complaints for the lot-release process in an automotive company. Our proposed framework integrates ML with a non-sampling approach, demonstrating its effectiveness in predicting complaints and reducing costs, fostering Quality 4.0.

From intentions to action: how behavioural intentions shape employee performance through digital learning?

PurposeThis study aims to explore the impact of “Performance Expectancy” (PE) on the performance of Indian automotive manufacturing employees through their “Behavioural Intention” (BI) in the context of digital learning within the volatile, uncertain, complex and ambiguous (VUCA) world.Design/methodology/approachA descriptive research design was adopted to gather data from 211 employees of Indian automotive manufacturing companies. Structural equation modelling was applied for data analysis and obtaining results.FindingsLargely, the findings indicate that BI does mediate the relationship between PE and employee performance (EP) in the context of the Indian automotive manufacturing sector. The findings would help in boosting digital learning initiatives, improving EP and fostering organizational success in the VUCA world.Research limitations/implicationsThe current study focused on the Indian manufacturing industry. Extending the research beyond the manufacturing sector to other industries in India could possibly help in generalizing the findings, and thereby enhance knowledge of the broader consequences of digital learning on EP.Practical implicationsDigital learning platforms can enhance sustainable industrialization in the manufacturing sector by providing employees with access to digital learning opportunities. Managers must provide employees with access to digital learning opportunities for making them more creative and innovative, so that they can become real change agents, and can handle real-world problems more efficiently, leading the organization to deal with the complexities and unpredictability in this VUCA world.Originality/valueWithin the ambits of Indian automotive manufacturing organizations, there have been limited research studies that have used two constructs of the UTAUT2 framework to see their impact on EP in terms of digital learning. Thus, based on the limited information available, this research stands as a pioneering effort in the realm of digital learning within the Indian automotive manufacturing industry, where the relationship between PE and EP is examined through the mediational role of BI of employees. Moreover, this research possibly would pave the way for further research studies on exploring the role of potential factors influencing the strength and direction of the relationships between these variables (PE and EP).

The Effects of Global Market Changes on Automotive Manufacturing and Embedded Software

The procedures used to create modern cars require extensive thought in various relevant scientific domains. Arguably, the most challenging obstacle facing the automobile sector is the management of production facilities by integrating software production lines, continuous integration, and continuous delivery/continuous deployment (CI/CD). All this is determined by market demands, the engine of a vehicle, and the complexity of assembling the entire car and installing its corresponding embedded software. As a result, concerns about various types of global change have grown, as has the lack of the ability to use fossil fuels, creating a substantial impact on the purchase and sale of modern automobiles. The research foundation is reflected in covering strategies for the deployment and administration of software, as well as opportunities for business improvement in particular production processes. This article strives to provide a summary of a scientific investigation of original equipment manufacturers, market segmentation, and the effects of global market changes on automotive manufacturing by examining the correlation between certain changes in the purchase of a specific brand and the powertrain of a vehicle. The research examines numerous datasets from the United States of America and Washington State, based on which we estimate possible future changes in the automotive industry’s sales.