Automotive Component Manufacturing Research Articles

Development of Digital Transformation Maturity Assessment Model for Collaborative Factory Involving Multiple Companies

Recent advancements in digital transformation (DX) in the industrial sector have spotlighted digital collaborative factories, which emphasize relationships with partners, particularly in the manufacturing sector. However, existing DX maturity assessment models primarily focus on evaluating individual companies, lacking consideration of partnerships and thereby failing to reflect the complexities of collaborative systems. To address this limitation, this study aims to develop a DX maturity assessment model tailored to digital collaborative factories while accounting for collaborative relationships. Initially, 25 existing DX maturity assessment models were reviewed, and the evaluation elements related to collaboration were extracted from each. Accordingly, the maturity assessment model was created with 15 evaluation factors, including organizational aspects, process management, quality control, and logistics operations. Finally, to verify the applicability of the model, the DX maturity levels of a lead company—a forklift-manufacturing company—and its partner—an automotive component manufacturer—within the same value chain were assessed, and the model’s suitability was evaluated. The results indicate that the lead company needed to improve on the intelligence, connectivity, and automation aspects, while its partner needs to streamline production process operations and technological connectivity. This approach enables manufacturers to obtain more reliable information in resolving issues arising from collaboration with partners, as well as in establishing future strategies. The findings suggest that strengthening collaboration systems among partners and advancing DX based on digital collaboration will raise competitiveness within the manufacturing sector.

Research on reconfigurable systems in discrete manufacturing workshops

Abstract With the development of smart manufacturing, the demand for personalized production has made reconfigurable systems in the manufacturing industry a focal point of research and application in high-end manufacturing. The paper analyzes the current status of the manufacturing industry and the challenges of reconfigurable technology. Furthermore, it designs and develops a reconfigurable system for discrete manufacturing of automotive components. The paper focuses on issues such as creating reconfigurable models, designing adaptive reconfiguration algorithms, accomplishing the creation of multi-layered models, the design of rule libraries, and algorithm implementation. The reconfiguration result scheme can be input into commercial software for performance simulation, and can directly integrate with production systems to complete production planning. This demonstrates the rationality of the reconfigurable models in the system, the correctness of the reconfiguration algorithms, and the effectiveness of the system, providing a theoretical basis for reconfigurable production lines.

Creating a Virtual Shadow of the Manufacturing of Automotive Components

Within the automotive industry, there is an increasing demand for a paradigm shift in terms of which materials are used for the manufacturing of the automotive body. Global climate goals are forcing a rapid adaption of new, advanced, sustainable material grades such as the fossil free steels and materials containing higher scrap content. With the introduction of these new and untested materials, methods for accounting for variation in material properties are needed directly in the press lines.The following study will focus on creating an initial virtual shadow of the manufacturing of a Volvo XC90 inner door panel through the application of Artificial Neural Networks (ANN). The virtual shadow differs from the concept of the digital twin by only being a virtual representation of the production line, with training data generated exclusively by numerical simulations, and having no automated communication with the physical press line control system. The virtual shadow can be used as an assistance to the press line operators to see how different press line settings and material parameter variations will impact the quality of the stamped component. The study aims to validate the virtual shadow through accurate predictions of the material draw-in measured in the physical press line.

Microstructure and mechanical properties of a hypereutectic Al–Si–Cu alloy manufactured by laser powder bed fusion

A novel Al–Si–Cu alloy was designed for additive manufacturing of automotive components, such as pistons and supercharger rotors, requiring a combination of elevated temperature properties and high cycle fatigue strength. The alloy was designed with an Al–Si hypereutectic chemistry to exploit the formation of primary Si nucleants to enable an equiaxed as-printed microstructure during laser powder bed fusion (LPBF). The alloy design space was assessed using a combined integrated computational materials engineering (ICME) approach with melt-spinning experiments to select a chemistry exhibiting primary Si nucleants acting as heterogeneous grain nucleation sites. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) of the LPBF as-printed samples revealed primary Si particles with a fully equiaxed grain structure and no apparent texturing as evaluated using electron backscatter diffraction (EBSD). High-resolution scanning transmission electron microscopy (STEM) revealed sub-micron Si particles and Al2Cu θ-phase precipitates which result in enhanced room and elevated temperature mechanical strength (room temperature: UTS: 449 ± 10 MPa, YS: 336 ± 12 MPa) as compared to commercial Al10SiMg (UTS: 417 ± 3 MPa, YS: 236 ± 6 MPa).

Pallet Loading Problem: A Case Study in the Automotive Industry Applying a Simplified Mathematical Model

Logistics and the supply chain are areas of great importance within organizations. Due to planning gaps, an increase in extra and unnecessary transport costs is usually observed in several companies due to their commercial commitments and need to comply with the delivery time and the batch quantity of products, leading to a negative economic impact. Thus, the objective of this work was to adjust an optimization model to maximize the shipments usually carried out by the companies. To validate the model, an automotive components manufacturer was selected, allowing us to apply the model to a real case study and evaluate the advantages and drawbacks of this tool. It was found that the company to validate the model exports most of its products, and most pallets sent are not fully optimized, generating excessive expense for the company in terms of urgent transport. To solve this problem, two mathematical optimization models were used for the company’s current reality, optimizing the placement of boxes per pallet and customer. With the use of the new tool, it was possible to determine that five pallets should be sent to the customer weekly, which correspond to their needs, and that have the appropriate configurations so that the pallet is sent completely.

INTERFIRM PARTNERSHIPS AND ORGANIZATIONAL INNOVATION FOR INDONESIAN AUTOMOTIVE COMPONENT MANUFACTURERS FACING THE TRANSITION TO BATTERY ELECTRIC VEHICLES

Background: Indonesia’s Automotive Industry has gradually shifted from manufacturing Internal Combustion Engines (ICE) to Battery Electric Vehicles (BEV) in recent years. This transition of Battery Electric Vehicles (BEVs) is disrupting conventional automobile manufacturers, creating an urgent need for traditional automakers and component suppliers to innovate and revamp of the current automotive manufacturing capabilities. However, The pursuit of Interfirm partnerships between OEMs and suppliers is believed to enhance resiliency and innovative process within the automotive organization. The main objective of this study is to identify the impact of several factors interfirm partnerships affecting the implementation of organizational innovation activities. Methods: A quantitative cross-sectional design was adopted for this study. The data collection consisted of 30 respondents from 1st tier of Indonesian Automotive Component Manufacturers through site visits, interview and online questionnaires. Data processing and analysis were carried out using descriptive statistics, factor analysis and multiple linear regression. Results: The result indicate that interfirm partnerships factors associated with organizational innovation activities. Among four key aspects of interfirm partnerships such as Efficiency, Innovation and Learning, Market opportunities, and Technology and Competition, only the motives aligned with the latter were found to exert a statistically significant and positive impact on organizational innovation. Conclusion: The study reveals that technology and competition in the context of interfirm partnerships formation shows positive and significant relationships with organizational innovation. Implications of research: The research helps the Indonesia Automotive Industry to improve manufacturing capabilities and competitiveness in electric vehicles sector and also expands the literature on Battery Electric Vehicles research for academics. Originality and value: The study performs the assesment of relationship between interfirm partnership and automotive component organizations in Indonesia. By addressing practitioners’ viewpoints, this research utilizes quantitative measurement to drive automative innovation and enhance manufacturing capabilities with the presence of Battery Electric Vehicles.

DEPLOYING BUILT-IN QUALITY TO REDUCE SCRAP IN AN AUTOMOTIVE COMPONENT MANUFACTURER

Automotive component manufacturers face global competitive challenges, and the paradigm has shifted from product price as the determining factor of competitiveness to the quality of the product. An automotive component manufacturer was struggling to manage the outflow of defects, and adding inspectors as quality gates to the rear-step bumper production line had severe cost implications. This study aimed to reduce the number of defects by deploying a strategic path of implementing built-in quality. Quality tools were used, and the study’s results included significant manpower reduction, improved quality capability, and reduced scrap rates and reworks.

Reducing dandori processing time using the single minute exchange of die method in swaging areas in automotive rubber components company

The automotive component company is engaged in the manufacture of automotive rubber components. Based on data obtained from field observations, it was found that the Dandori process on the swaging Nox machine, especially TA090 type, had the highest downtime compared to another component. Based on these problems, research uses the Single Minute Exchange of Die (SMED) method to reduce Dandori downtime in the TA090 swaging process. The SMED method was carried out in three stages: 1. identify internal and external setup, 2. Converting internal to external setup, and 3. Streamlining aspects of operation. In addition, it also used data processing tools, namely SMART, fishbone, and 5W+1H as support to solve this problem. Improvements were made by converting internal work elements into external ones and streamlining aspects of operation by improving on man, method, and machine/tools categories. The result of these improvements was a decrease in downtime of 39 minutes 48 seconds and the improvement efficiency achieved was 81.2%.

Mechanical analysis of sisal fiber/bio-epoxy/fly-ash reinforced hybrid composites

This research investigates the mechanical characteristics of a novel hybrid composite material, which combines bio-epoxy reinforced with sisal fiber and integrated with fly ash nano-fillers. The study focuses on exploiting the environmentally friendly attributes of natural fiber composites and reducing reliance on synthetic materials. In this study, sisal fiber serves as the reinforcement, and a bio-epoxy matrix is utilized to create the composite. To further enhance its properties, fly ash, a byproduct of coal-fired power plants, is incorporated as a nano-filler. The experimental findings reveal significant improvements in the mechanical properties of the composite due to the inclusion of fly ash nano-fillers. The tensile strength shows a notable enhancement of up to 6.3%, flexural strength experiences an impressive increase of 68%, impact strength demonstrates a remarkable boost of 28%, and scratch hardness elevates by 17% which were all achieved at 20% fiber weight fraction and 5% fly ash weight fraction. The considerable potential of this hybrid sisal fiber reinforced bio-epoxy composite, integrated with fly ash nano-fillers, as an eco-friendly alternative to traditional synthetic composites is evident from these results. Such enhancements make the composite suitable for a wide range of engineering applications, including the manufacturing of automotive components, construction materials, and consumer goods. By adopting this bio-composite, industries can actively contribute to sustainable practices while maintaining optimal performance in their products. This research offers valuable insights into a promising solution for eco-conscious engineering applications, with both quantitative and qualitative evidence demonstrating the achievement of superior mechanical properties in this innovative hybrid material.

Microstructure and mechanical properties of hybrid nano-titanium carbide-carbon nanotubes (nano-TiC-CNT) reinforced aluminium matrix composite

To use Al composites in structural applications, we need to improve strength and ductility at the same time. In this article, we explore three main concepts to solve this problem: improving the dispersion uniformity of CNTs in Al powder without damaging its structure by solution coating technique, fabricating a hybrid composite by reinforcing Al with nano-TiC-CNT, comparing the properties of nano-TiC-CNT and micron-TiC-CNT hybrid composites. Microstructure observation by SEM, TEM, and XRD revealed well-dispersed and preserved CNTs without the formation of a second phase. The Al-0.5CNT composite showed good tensile strength and elongation at break of 278 MPa and 14%, respectively. Further improvements in tensile strength and ductility of 285 MPa and 23%, respectively, were measured after the addition of 2.5 wt%; (1.4 vol%) TiC nanoparticles to Al-0.5CNT composite. However, the introduction of 2.5 wt-% TiC macroparticles only improved the tensile strength by 48% but elongation at break was up to 32%. The improved strength and ductility are attributed to the introduction of geometrical necessary dislocation and Orowan looping of dislocations leading to back stress strengthening. The new Al composite is expected to find application in automotive and aerospace component manufacture and thermal management.

Ensemble learning for demand forecast of After-Market spare parts to empower data-driven value chain and an empirical study

Demand forecast for spare parts in supply chains is essential for ensuring customer satisfaction while minimizing appropriate inventory. The after-market orders mainly depend on repair and maintenance that makes the present problem for demand forecast challenging owing to high variability in demand sizes and time intervals. It is critical to address market fluctuation for effective demand forecast to reduce the risks of oversupply and shortage for supply chain resilience. Intelligent data-driven technologies should be developed to promote value integration and value co-creation among supply chain partners for digital transformation. The shortening product life cycle and the reducing lot sizes of diverse products have increased the challenges of demand forecast and supply chain management. This study aims to classify the demand patterns and develop the corresponding models via stacking ensemble approach to improve the overall forecasting performance. This study develops an alarm system to monitor the performance of the proposed approach and a systematic mechanism for retraining the model to maintain the decision quality. An empirical study is conducted in a leading automotive after-market component manufacturer for validation in real settings. The results have shown the forecast errors and the total cost can be effectively reduced by the developed solution.

An Experimental Protocol for Human Stress Investigation in Manufacturing Contexts: Its Application in the NO-STRESS Project

Stress is a critical concern in manufacturing environments, as it impacts the well-being and performance of workers. Accurate measurement of stress is essential for effective intervention and mitigation strategies. This paper introduces a holistic and human-centered protocol to measure stress in manufacturing settings. The three-phased protocol integrates the analysis of physiological signals, performance indicators, and the human perception of stress. The protocol incorporates advanced techniques, such as electroencephalography (EEG), heart rate variability (HRV), galvanic skin response (GSR), and electromyography (EMG), to capture physiological responses associated with stress. Furthermore, the protocol considers performance indicators as an additional dimension of stress measurement. Indicators such as task execution time, errors, production rate, and other relevant performance metrics contribute to a comprehensive understanding of stress in manufacturing environments. The human perception of stress is also integrated into the protocol, recognizing the subjective experience of the individual. This component captures self-assessment and subjective reports, allowing for a more nuanced evaluation of stress levels. By adopting a holistic and human-centered approach, the proposed protocol aims to enhance our understanding of stress factors in manufacturing environments. The protocol was also applied in the automotive industry and plastic component manufacturing. The insights gained from this protocol can inform targeted interventions to improve worker well-being, productivity, and overall organizational performance.

Microstructure, Hardening, and Mechanical Properties of Hypoeutectic Al–Ce–Ni Alloys with Zr and Zr + Sc Additions and the Effect of Ultrasonic Melt Processing

Ternary Al–Ce–Ni alloys have a potential in the manufacture of automotive and airspace components, as well as in replacing traditional aluminum alloys in high‐temperature applications, which is determined by the formation of fine and thermally stable Al11Ce3 and Al3Ni eutectic. Herein, the microstructure and mechanical properties of a hypoeutectic Al4Ce2Ni alloy using Zr and Zr + Sc additions combined with ultrasonic melt processing and dispersion hardening are improved. As a result, the grain structure of the as‐cast alloys is significantly refined and the annealing at 350 °C leads to a considerable hardening effect, especially in the alloys with Zr + Sc additions (doubling the hardness). Al3Zr and Al3(Zr,Sc) coherent particles are identified as hardening nanoprecipitates. The compressive mechanical testing at room and elevated temperatures shows that the additions of Zr and Zr + Sc improve the strength with the additional increase caused by ultrasonic melt processing.

The Effect of Organizational Transformation, Organizational Culture, and Transformational Leadership on Employee Performance Through Job Satisfaction: An Evidence from Automotive Component Manufacturing Companies

This study aimed to analyze organizational transformation, organizational culture, and transformational leadership in relation to employee performance, with job satisfaction serving as a mediating variable. The participants consisted of 101 employees from automotive component manufacturing companies. They were selected using purposive sampling techniques to ensure alignment with the research objectives. Data were analyzed using Partial Least Squares (PLS) to illustrate the variables and indicators influencing employees' performance. The results indicated that organizational transformation, organizational culture, and transformational leadership had a positive impact on employee performance. Furthermore, the mediating role of job satisfaction in relation to employee performance was also observed. Therefore, organizations should optimize job satisfaction to enhance employee competencies in response to business challenges. By implementing organizational transformation, fostering a positive organizational culture, and promoting transformational leadership, organizations can potentially increase satisfaction, responsiveness, and performance, thereby supporting business innovation. Job satisfaction plays a crucial role in maintaining performance stability, as the business process appears to be highly reliant on organizational transformation, organizational culture, and transformational leadership. The variables examined in this study demonstrate that job satisfaction enhances employees' responsiveness to the company's operations. Consequently, organizations should prioritize responsiveness and adaptability when empowering their human resources.

Application of Non-destructive Testing in Quality Control of Manufactured Aluminium Metal Matrix Composite Components for the Automotive Industry

The manufacturing of automotive components using aluminium metal matrix composites (Al-MMCs) is progressively gaining a relevant place in the automotive industry. Due to the increasing competition in the automobile sector, there is a great need to supply efficient, stable, and high-quality products. Generally, following automotive standards is voluntary, which means that businesses and other organizations are not legally obliged to apply them. Nevertheless, in certain cases standards may facilitate compliance with legal requirements, such as those contained in European directives and regulations. IATF 16949:2016 is the current version of the IATF 16949 Standard and outlines the requirements an organization must maintain in their quality system for IATF 16949 certification. This new application of manufacturing Al-MMCs requires additional procedures to guarantee the quality of the components manufactured. Because the manufacturing process may generate various defects, such as cracks, voids, lack of fusion, inclusions, porosities, and other metallurgical aspects, non-destructive testing (NDT) techniques should be used for guaranteeing the quality of the components manufactured. The development of reliable NDT methods for aluminium metal matrix composite parts is thus a major challenge. This aspect is related to how NDT procedures need to be optimised or developed to address the singular structures of the processes, such as complex geometry, anisotropic material properties, special internal structures, and the presence of nanoparticles. The main objective of this work is to summarize and present the relevant potential of different NDT techniques used in quality control of manufactured Al-MMC components in the automotive industry, to be explorer in the European FLAMINGo project (Fabrication of Lightweight Aluminium Metal Matrix Composites and Validation in Green Vehicles). This study is very significant because the NDT techniques present different probabilities of detection of the defects, principally of the microdefects.

Unveiling Sustainable Potential: A Life Cycle Assessment of Plant-Fiber Composite Microcellular Foam Molded Automotive Components.

The development and utilization of new plant-fiber composite materials and microcellular foam molding processes for the manufacturing of automotive components are effective approaches when achieving the lightweight, low-carbon, and sustainable development of automobiles. However, current research in this field has mainly focused on component performance development and functional exploration, with a limited assessment of environmental performance, which fails to meet the requirements of the current green and sustainable development agenda. In this study, based on a life cycle assessment, the resource, and environmental impacts of plant-fiber composite material automotive components and microcellular foam molding processes were investigated. Furthermore, a combined approach to digital twinning and life cycle evaluation was proposed to conduct resource and environmental assessments and analysis. The research results indicate that under current technological conditions, resource and environmental issues associated with plant-fiber composite material automotive components are significantly higher than those of traditional material components, mainly due to differences in their early-stage processes and the consumption of electrical energy and chemical raw materials. It is noteworthy that electricity consumption is the largest influencing factor that causes environmental issues throughout the life cycle, especially accounting for more than 42% of indicators such as ozone depletion, fossil resource consumption, and carbon dioxide emissions. Additionally, the microcellular foam molding process can effectively reduce the environmental impact of products by approximately 15% and exhibits better overall environmental performance compared to chemical foaming. In future development, optimizing the forming process of plant-fiber composite materials, increasing the proportion of clean energy use, and promoting the adoption of microcellular foam injection molding processes could be crucial for the green and sustainable development of automotive components.

Direct additive manufacturing of metal parts for automotive applications

Additive manufacturing or three-dimensional (3D) printing offers tremendous opportunities for the automotive industry to reduce vehicle weight and improve vehicle performance through consolidating parts, tailoring material properties, enabling multifunctional components, and simplifying manufacturing processes. However, additive manufacturing research for direct manufacturing of automotive components is limited, partially because of the sheer volume of automotive production. In this paper, we explore the potential of direct manufacturing of metallic vehicle components using additive manufacturing coupled with the generative design approach. Using a radar mounting bracket as an example, we show that desired part strength and safety performance can be achieved with 42 % weight reduction and simplified manufacturing and assembly process. A production cost analysis was also conducted based on two mainstream additive manufacturing systems. The result suggests that the cost of metal powder is the limiting factor for wider adoption of additive manufacturing in the automotive industry.

Formalising human resource practices in a family-centric business: the case of Precision Engineering

Learning outcomes After studying the case, the students will be able to: 1. understand the business and existing HR practices at Precision Engineering; 2. evaluate the factors affecting business that may require the company to formalise its HR practices; 3. create recruitment and selection-related solutions for HR 2.0 using appropriate models and theory to aid the company meet its business goals; 4. create training needs identification and evaluation practices for HR 2.0 using appropriate models and theory to aid the company meet its business goals; and 5. create performance planning and review-related solutions for HR 2.0 using appropriate models and theory to aid the company meet its business goals. The case helps students objectively assess HR practices related to three core verticals – recruitment and selection; training; and performance management systems. It also enables them to reassess these practices with the help of specific metrics and models. Case overview/synopsis Precision Engineering was a manufacturer of machined metal components in the Indian automotive components industry. It had been a family-run business since its inception in 1995. Precision was awarded the prestigious Automotive Component Manufacturers of India award in 2020 for excellence in HR. Ms Sakshi Kapoor, General Manager of Innovation, was ecstatic at the receipt of this award. She, however, was thoughtful about the informal human resource (HR) practices at the company. The top management had announced an aggressive growth plan and advised Ms Kapoor to leverage HR practices to facilitate these plans. Recruitment and selection, employee training and performance management systems needed to be formalised on a priority basis to strategically aid the future business agenda at Precision. Ms Kapoor faced the challenge of preparing the roadmap of HR 2.0 while preserving the employee-centric beliefs at Precision. The case initiates a discussion to achieve this goal by adopting suitable HR metrics and models. Complexity academic level It should be taught in the core course on Human Resource Management for first-year Masters in Business Administration (MBA) students. Alternatively, it could be used in elective courses such as Strategic Human Resource Management, Training and Development and Performance Management Systems for second-year MBA students. Supplementary materials Teaching notes are available for educators only. Subject code CSS 6: Human Resource Management.

Sustainable development‐oriented regulatory and competitive pressures to shift toward a circular economy: The role of environmental orientation and Industry 4.0 technologies

AbstractAutomakers' transition from a linear economy to a circular economy (CE) in response to sustainable development‐oriented regulatory and competitive pressures is a challenging process that requires innovative, practical technologies. However, Industry 4.0 (I4.0) technologies are an important part of the transition to CE for environmentally friendly companies. In this study, we examine whether regulatory pressure (RP) and competitive pressure (CP) toward sustainability motivate firms to implement I4.0 technologies for CE, along with the mediating effects of environmental orientation (EO). PLS‐SEM via SmartPLS software was used to analyze data from 230 managers in the automotive and auto component manufacturing industries in India. The findings of this study showed that RP and CP positively influence I4.0 adoption, which impacts CE capability. Furthermore, EO partially mediates the relationship between RP and CP with I4.0 technologies. As a practical implementation of this study, to transition to CE and contribute to sustainable development, managers need to deal effectively with RP and CP. Several implications for theory and practice are discussed at the end of the study.

Inventory Forecasting and Control Decisions for Effective Inventory Management in the South African Automotive Component Manufacturing Industry: Pre COVID-19 and Lockdown Period

The COVID-19 global health pandemic significantly affected the global economy and the automotive industry when lockdown measures were implemented. This study seeks to investigate the influence of inventory forecasting and control decisions on effective inventory management in the South African automotive component manufacturing (SAACM) industry. Using a positivistic paradigm with a quantitative research approach, data was sourced from 162 Automotive Component Manufacturers (ACMs) to establish whether their inventory forecasting and control decisions changed from prior COVID-19 to the lockdown period during the COVID-19 pandemic. The multiple regression analysis found statistically significant relationships between inventory forecasting decisions and effective inventory management prior to COVID-19, inventory control decisions and effective inventory management prior to COVID-19 and inventory forecasting decisions and effective inventory management during the lockdown period. Thus, regardless of the COVID-19 pandemic, inventory managers in ACMs in South Africa (SA) should use inventory forecasting methods such as demand forecasting, economic order quantity and materials requirement planning. They should further consider using an inventory information sharing system and inventory replenishment procedure to manage inventory more effectively.