Automotive Supplier Industry Research Articles

Machine Learning-Based Demand and Pricing Optimization for a Resilient Automotive Supply Chain

In the supply chain management of the automotive industry, this paper investigates the use of demand forecasting, supply optimization, and price optimization. Optimizing the supply chain is essential for satisfying changing customer needs, cutting expenses, and increasing revenue. This study aims to improve the accuracy of demand prediction, optimize supplier relationships, and simplify pricing strategies through the use of ML-driven models. To solve the difficulties faced by automakers in a volatile market, the suggested framework combines historical data analysis, market trends, and inventory management strategies. The results help the automotive industry's supply chain systems become more flexible and resilient.

Mitigating data inaccuracy and supply chain challenges in Western Romania's automotive industry

The purpose of this paper was to emphasize the importance of data accuracy within internal logistics systems and their extended influence on supply chains in automotive industry through 6-month multiple case studies conducted on 3 first tier original equipment manufacturers (OEM) based in Western Romania. The study investigates the most common causes of data inaccuracies among automotive suppliers and their approaches to reduce consequential supply chain issues and be more agile. Data collection and analysis revealed that main issues arise due to ordering quantities mismatching actual customer demand, a wide range of order lot sizes, lead times and delivery reliability concerns and the reluctance to shift away from mainstream cost-effectiveness and towards strategic added value thinking. These issues sourced significant other related operational challenges such as excessive inventory, short-term stockouts and subsequent express shipping services or product-related inconveniences (quality and capacity levels, contracted volumes and dedicated lines). The paper sources different logistics and supply chain strategies used by the 3 OEMs, their features and operational performance, as well as their overall effectiveness, which can be applied by other automotive industry suppliers to improve own results. Introducing more reliable real-time data collection tools and performance metrics has started hauling more focus towards solving these prevalent issues with some ongoing improvement projects showing up to 25% better results. For one of the 3 OEMs introducing a new warehouse management system has already sourced an overall quality increase (5 percentage points) due to a 60% higher utilization of its production equipment.

Making Cognitive Ergonomics in the Human–Computer Interaction of Manufacturing Execution Systems Assessable: Experimental and Validation Approaches to Closing Research Gaps

Cognitive ergonomics and the mental health of production workers have attracted increasing interest in industrial companies. However, there is still not much research available as it is regarding physical ergonomics and muscular load. This paper designs an experiment to analyze the cognitive ergonomics and mental stress of shop floor production workers interacting with different user interfaces of a Manufacturing Execution System (MES) that is adjustable for analyzing the influence of other assistive systems, too. This approach is going to be designed with the Design of Experiments (DoE) method. Therefore, the respective goals and factors are going to be determined. The environment will be the laboratories of the University of Applied Sciences Amberg-Weiden and its Campus for Digitalization in Amberg. In detail, there will be a sample assembly process from the automotive supplier industry for demonstration purposes. At this laboratory, the MES software from the European benchmark SAP is installed, and the respective standard Production Operator Desk is going to be used with slight adaptions. In order to make the cognitive ergonomics measurable, different approaches are going to be used. For instance, body temperature, heart rate and skin conductance as well as subjective methods of self-assessment are planned. The result of this paper is a ready-to-run experiment with sample data for each classification of participants. Further, possible limitations and adjustments are going to be discussed. Finally, an approach to validating the expected results is going to be shown and future intentions are going to be discussed.

Designing a Model for the Integration of Physical, Informational, and Financial Processes in the Supply Chain to Achieve Resilience in the Automotive Industry

Objective: This research aims to design a model for the integration of physical, informational, and financial processes in the supply chain to achieve resilience in the automotive industry. Methodology: The approach used in this research is modeling, initially utilizing Fuzzy DEMATEL to identify influencing and influenced factors. Since DEMATEL typically does not describe the nature and levels of interactions, the study further employs an Interpretive Structural Modeling (ISM) approach using MICMAC software to understand causal relationships and categorize influential factors into five levels. Data collection was based on a questionnaire and the Delphi method. A questionnaire grounded in a hybrid Fuzzy DEMATEL-ISM approach was designed and distributed to 20 supply chain management experts in the industry. After reaching a consensus, these factors were analyzed with the chosen approaches and classified into five levels, categorized into four types: autonomous, independent, dependent, and linkage. Findings: The findings indicate that eight categories of factors (including integration of measurement, resource management, communication integration, organizational; socio-economic sub-component; human and technical sub-component; managerial components, customers, planning, information and product quality; financial, process, and environmental components; technology planning integration and flexibility) have the highest impact on achieving resilience in the automotive industry supply chain. Conclusion: The most influential factor in the resilient supply chain of the automotive industry is the integration of measurement, which is connected with all other sub-components. In fact, resilience measurement impacts the resource management sub-component and the managerial sub-component.

Identification and Reduction of Product Carbon Footprints: Case Studies from the Austrian Automotive Supplier Industry

Greenhouse gas (GHG) emissions from human activities have climbed significantly above pre-pandemic levels and have reached record highs that unequivocally accelerate global warming. Industry has a significant impact on climate change, emitting at least 21% of global GHGs and making little overall progress toward its reduction until now. Reducing industry’s emissions requires coordinated action along the value chains in order to promote mitigation options, such as energy and material efficiency, circular material flows, and transformative changes within production processes. This article is the first evaluation of GHG emissions generated during the manufacturing of vehicle components by Austrian companies. For this, the authors analyzed three different products of automotive suppliers according to the methodology of ISO 14067. Despite previous efforts toward an environmentally compatible fabrication, additional and significant reduction potentials were identified. These measures for product carbon footprint (PCF) reduction included the sourcing of low-carbon materials (which are already available on the market), more extensive use of renewable energy, and changes towards more resource efficient manufacturing processes and machinery. Depending on the materials used, the PCF can be reduced by up to 80%. The findings serve to prepare for future PCF reporting regulations and illustrate reduction potentials to achieve future market advantages, especially when PCFs become an awarding criterion.

Standardization of Project Management Practices of Automotive Industry Suppliers

This paper deals with the issue of standardization of project management (PM) practices of development activities of automotive industry suppliers. Development activities are critically important for ensuring the final quality of the developed products and related production systems while keeping the target costs. The key to their successful management is considered the use of modern PM practices. In order to represent the current best practices and to be apparent and transparent, the PM practices must be properly standardized. A comprehensive branch standard of PM in automotive industry is however missing. In order to fill the gap in the current state of knowledge, consecutive steps of standardization were defined. This article describes one of the initial steps, a systematic literature review of existing resources that could serve as a valuable basis for standardization. The results show that general PM standards are suitable for treating the quality of project processes and branch PM standards of automotive industry for treating the quality of project product – manufacturing processes of automotive suppliers. The paper discusses the individual methods within both groups in more detail and recommends what purpose they are suitable for.

New Generation FMEA Method in Automotive Industry: An Application

It is aimed to gain study substantiality by making an application for risk analysis study in the automotive industry. To bring to the literature the current point of risk analyzes used in FMEA methods applied in the automotive industry. At the same time, it is aimed to improve a problem experienced in the process of an operating in the automotive supplier industry with the risk analysis method. Failure Mode and Effects Analysis (FMEA) from risk analysis which is strong method to identifying and managing of the risks of potential failures occurring from product, process, service and system. Three methods were used in FMEA risk analysis in the study. AIAG FMEA Handbook fourth edition 2008, VDA-4 standard and new generation AIAG&VDA FMEA handbook, 2019. In this study, a Process FMEA study was prepared for the surface coating preparation process used by an automotive supplier industry. According to the results of the risk analysis, corrective actions were defined and prepared after the P-FMEA study. Afterwards, the necessary investments were made by the company management and the risks were minimized. With this investment, an innovative and technological application was integrated by ensuring the transition of the process from the human factor to automation. In addition, differences and current information about FMEA evaluation methods used in the automotive industry have been brought to the literature

Solution of the assembly line balancing problem using the rank positional weight method and Kilbridge and Wester heuristics method: An application in the cable industry

Today, assembly lines are frequently used in factories' production areas because they increase production processes' efficiency. Due to increased customer demands, increasing production amounts and intense competition cause severe fluctuations in production environments. This is also evident in assembly lines. Balancing problems caused by many reasons in assembly lines has become a big problem for companies. In this study, the balancing problem in the assembly line in an automotive supplier industry company that produces cables has been tried to be solved. In the solution of the problem, the Rank positional weight method, which is among the heuristics frequently used in the literature, and the Kilbridge and Wester heuristics were used. Considering the current situation, the cycle time from 170 s has been reduced to 142.25 s, and the line efficiency has been increased from 82.36% to 98.42%. There was no increase or decrease in the number of stations on the line and the number of operators working there. As a result of all these efforts, the workload was distributed equally among the stations, severely reducing waiting time. In this way, the downtimes in production were reduced, the overtime hours required to reach the required daily production amount were eliminated, and labor costs were reduced.

Which is better? Business models of partial and cross ownership in an NEV supply chain

PurposeTo examine how shareholding affects optimal profits, R&D innovation, NEV market scale and social welfare in two supply chain models with partial and cross ownership patterns.Design/methodology/approachThe gradual retreat of government subsidies has directly weakened the financial support available to the stakeholders of new energy vehicles (NEVs). In this context, upstream and downstream enterprises of NEV are constantly seeking new business models of cooperation to achieve possible win-wins. NEV supply chain shareholding is an emerging new practice for such explorations. However, its performance in the NEV supply chain is seldom investigated. In this paper, we employ a Stackelberg game model to investigate how partial and cross-ownership affect the optimal decisions in a NEV supply chain.FindingsResults showed that: (1) Compared with the unilateral shareholding model, the battery supplier will benefit from cross-ownership in the supply chain, while the NEV manufacturer will not necessarily benefit from it. At the same time, cross-ownership will bring the greatest incentive for battery R&D (2) Supply chain downstream competition will not necessarily lead to the improvement of the total consumption of NEVs or the level of battery design. Pareto improvement can be brought only when one of the manufacturers holds less than a certain equity threshold. In addition, downstream competition will also not necessarily bring more benefits to the battery supplier.Originality/valueAt present, NEV supply chain management has attracted widespread attention from scholars from all walks of life. Previous studies have been carried out that covers topics such as pricing strategies and optimal profits and the role of NEV in the sustainable development of the automotive industry supply chain, or disparate impacts of government subsidies and carbon emission regulation on supply chain members. However, as far as the authors know, compared with the new emerging NEV corporate practice, the shareholding phenomenon between upstream and downstream in the supply chain of NEV has not been studied in the existing studies.

Rescuing the global automotive industry supply chain

China's economy has been deeply integrated into the global industrial supply chain, and the global industrial chain is highly dependent. The automobile industry is an important pillar industry of the national economy. It plays an important role in the development of the national economy and society because of its wide industrial chain, strong correlation, wide employment and large consumption. This paper studies the value chain of the global automobile industry. By analyzing the current situation of China's automobile industry, the degree of dependence on global foreign trade, and the position and advantages and disadvantages in the global value chain, it puts forward the development trend and direction of the future automobile industry chain, which has certain reference significance for the development of the automobile industry.

Review of recent developments in battery systems and hydrogen solutions for road transport applications

This study aims to provide an overview of the current state-of-the-art technology and the research challenges that lie ahead for the electric vehicle (EV) ecosystem in Europe, including both batteries and hydrogen fuel-cells, which must be overcome to enable the user acceptance of alternative powertrains with respect to the conventional internal combustion engine (ICE). With a focus on the automotive supply industry, this study addresses the different aspects along the entire value chain of the respective technologies and how they can be integrated within a sector which has been dominated by the ICE as the prime mover of road vehicles for over a century. CLEPA, the European Association of Automotive Suppliers, supports the Paris agreement and is ready to contribute to achieving climate neutrality while maintaining competitiveness through a technology-open approach.

Planning and Multi-Objective Optimization of Production Systems by means of Assembly Line Balancing

The ever-shorter time to market demanded by customers and an increasing number of variants lead to high-frequency product development and production system planning cycles. This article therefore presents an approach that aims at increasing efficiency in the repetitive planning of variant-specific assembly systems. Compared to the state-of-the-art manual, document-based planning prevailing in industry, formal optimization methods have the potential of considering multiple optimization criteria. This article therefore proposes an approach for assigning individual process steps to stations for a given customer cycle time while minimizing the number of stations as well as optimizing additional criteria such as increasing the production system flexibility, achieving good ergonomics or reducing the deviation within provided tolerances. The solution space of the optimization is constrained by the mathematical modeling of a limited number of stations. The operations research (OR) model developed for this purpose considers given assembly precedence graphs as an input and includes variables, parameters, objective function and constraints. Especially the latter considers the process precedence relations in terms of the Assembly Line Balancing (ALB) problem as well as a divisibility of process steps. The approach is applied to the variant-specific planning of a highly automated welding assembly in the automotive supplier industry as use case. The results show its applicability and potential in reducing planning time.

Design of a Guideline for a Strategy Process of medium-sized Companies

Companies with a clear, documented strategy perform better than their competitors without a strategy. Nevertheless, the strategy process confronts medium-sized companies (250-3,000 employees) with major challenges while many of them do not have a clear strategy process. Reasons for that can be the focus on operations and thus lack of time and resources, missing methods knowledge, or the underestimation of the value of a strategy. In times of a structural change in an industry, as we see it currently for example with the electrification of the automotive industry, a strategy becomes even more important. The automotive supplier industry alone employs around 150,000 people just in medium-sized companies in Germany. This paper aims to design a guideline that supports medium-sized companies to define their long-term goals and in the implementation of their derived strategy. Based on a literature review and 16 expert interviews a guideline was developed that contains templates to document the strategy process and a process model including checklists to fill the templates. The guideline was initially evaluated against the defined success factors in a medium-sized company.

Implementing Organisational Ambidexterity for a Successful Transformation of the Automotive Supply Industry Towards a Green Future

Background: Customers demand more sustainable mobility solutions and shift to electric vehicles and Mobility-as-a-Service offers. Because of these shifts, automotive suppliers must improve their corporate social responsibility (CSR). Especially in Germany, where they play a dominant role in the economy, they need to assume their responsibility towards the green future and seize new growth opportunities within and outside the traditional automotive industry to ensure their competitiveness.
 Research objectives: The article aims to determine the role of ambidexterity, the competencies required from employees at all levels, and the success measurement of the transformation in the automotive supplier industry in working towards a green future.
 Research design and methods: The research is based on 12 expert interviews with top managers from German automotive suppliers, consultants, ambidexterity experts, and employee representatives.
 Results: The trends (electrification, autonomous driving, digitalisation and new mobility services pose unprecedented challenges for automotive suppliers. To deal with these challenges and improve their CSR performance, automotive suppliers must follow an ambidextrous approach to make their core business more efficient while at the same time seizing new growth opportunities towards a green future.
 Conclusions: The organisational ambidexterity combined with CSR allows firms to improve their environmental performance. However, organisational ambidexterity is not only a structural design choice but a task that requires specific competencies.

한국자동차산업 공급네트워크의 진화

Most studies on the supply network structure have focused on revealing the “stationary’ network structure based on cross-sectional data. However, when the supply network is defined as a complex adaptive system that is a dynamic process, it is particularly important to explore its structure and evolution. Therefore, this study empirically analyzed how and through which micro-mechanisms the traditional vertical structure of the Korean automotive industry supply network is evolving into a horizontal structure. The results confirmed that new firms were continuously entering the Korean automotive industry supply network, and transaction relationships that were not found in the traditional supply chain structure were increasing. Additionally, among the existing suppliers, high-performing suppliers continued to form new transaction relationships while maintaining existing relationships. The significance of this study is as follows. SAOM was applied to the supply network of the Korean automotive industry for the first time, and the existing vertical and linear relationship studies were expanded from a network perspective. Furthermore, unlike the existing supply network-related studies, which were limited to an analysis at a specific point in time, the dynamic evolution of the supply network was identified.

Transfer Pricing in the Automotive Supplier Industry

Automotive suppliers are characterized by a centralized IP ownership, centralized provision of services, and a global presence of local plants that sell and invoice manufactured components directly to their customers’ local production facilities. All this makes cross-border intercompany transactions and the respective transfer pricing of automotive suppliers with respect to intangibles, manufacturing and services very challenging.

How Does Ecological Organizational Innovation Affect Performance? Konya Automotive Sub-Industry Business Cluster Survey

Ekolojik örgütsel yenilik işletmelerde yeni ve güncel bir yenilik türü olarak dinamik işletme yapılarının gelecek kaygıları bağlamında ele alınan bir konu olmaktadır. İşletme performansı ise işletmelerin başarı ölçütlerini belirleyen bütünsel sistemdir. Kavramsal incelemelerin ardından “Ekolojik örgütsel yenilik performansı nasıl etkiliyor?” temel araştırma sorusuna yanıt aranmaktadır. Çalışmada, işletmelerde ekolojik örgütsel yenilik ile işletme performansı arasındaki ilişkinin tespit edilmesi amaçlanmıştır. Çalışma görgül araştırma niteliğindedir. Bu araştırmada veri toplama aracı olarak anket tekniği kullanılmıştır. Basit tesadüfi yöntemle belirlenen Konya Otomotiv Yan Sanayi İş Kümesi çalışanlarından 148 geri dönüş elde edilmiştir. Elde edilen geri dönüşlere bağlı olarak analizler yapılmıştır. Yapılan regresyon analizi sonuçlarına göre ekolojik örgütsel yeniliğin işletme performansı üzerine etki ettiği görülmüştür.

The micro-foundations of a dynamic technological capability in the automotive industry

This article seeks insights into how individuals, processes, and structures interact to create the micro-foundations of an operational capability related to production line innovation. Drawing on the literature on the micro-foundations of dynamic capabilities, we develop a model that explains how structures and processes encourage individuals to interact and how organizational routines and production line innovation capabilities emerge through these interactions. We based this study on a single case study design and used the Gioia methodology to analyze the data. The model was developed using 20 interviews with automotive industry suppliers, data collected from participant observations, and data from secondary sources. First, the findings at the individual level show that the mentality and experiences of managers affect macro-level capabilities. Second, social capital and networks, learning and integration capabilities, participatory decision-making and communication, coordination capabilities, and human resources management capabilities influence the development of production line innovation capability by promoting interpersonal interaction. Finally, structural factors such as organizational barriers and processes improve production line innovation capability. This study contributes to the literature on the micro-foundations of dynamic capabilities.

Combined Technology Selection Model for Digital Transformation in Manufacturing: A Case Study From the Automotive Supplier Industry

Among generic technology management activities, rapid technology identification and selection stand as the significant determinants of technology adoption success in the digital transformation era. Especially for manufacturing SMEs in developing countries, rapid digital technologies are critical since they struggle to protect their competitiveness in global value chains threatened by digitalization. Previous studies introduce various multi-criteria decision-making model-based approaches to identify and select appropriate manufacturing technologies. However, these approaches were relatively rigid and required an advanced understanding of the technology for criteria and alternative settings and evaluation. Decision-makers need more flexible and scalable contextual frameworks for technology selection in digitalization. Since digital technologies offer both benefits and challenges, the decision-making models should reflect this dialectic nature of Industry 4.0 adoption and contextually optimize their decisions by combining multiple quantitative methods for technology identification and selection. Besides, case studies on digital technology selection are rare in manufacturing SMEs from developing country context in the literature. In this context, this study proposes a technology selection framework that utilizes the three dimensions (industry 4.0 technologies, benefits, and challenges) and combines AHP with a QFD-inspired intervention matrix and an optimization model by Mixed Integer Programming (MIP). The proposed model is validated with a case study from the automotive supplier industry in Turkey with the data provided from interviews and a Delphi survey with 11 experts from the digitalization value chain of the selected industry. Case study results revealed that the highest benefits of industry 4.0 lie in process/quality efficiency improvement and reduced inventory. At the same time, data analytics and sensor technologies occurred as the most critical tools. Significant challenges of digital technology adoption are insufficient expert know-how and budget constraints.

Supplier selection by integrated IFDEMATEL-IFTOPSIS Method: A case study of automotive supply industry

Selecting the best supplier emerges as a crucial subject for all sectors to achieve long term collaborations in supply chains. This study object to select the most suitable supplier for a company engage in activities in the automotive supply industry. For this purpose, a five-stage Intuitionistic Fuzzy Multi-Criteria Decision Making (IFMCDM) model is conducted. Firstly, decision criteria are defined by literature research and expert group opinions. Secondly, the importance weights of these criteria are obtained by IF Decision Making Trial and Evaluation Laboratory (IFDEMATEL). Followingly, the most suitable supplier is assessed by IF Technique for Order Preference by Similarity to Ideal Solution (IFTOPSIS). In the fourth stage, Sensitivity Analysis is utilized to analyze the effect of differentiation in criterion. Lastly, a comparative analysis is carried out. The results of the study has pointed that “Price” is the most important criterion in supplier selection and “Supplier 4” is the best alternative for this case. Main contribution of this study is to integrate IFDEMATEL-IFTOPSIS method for the first time in automotive supplier selection literature and propose a specific decision framework. In addition, proposed model is found robust and valid.