DIGITAL LIBRARY
STUDYING FUTURE COMPETENCE PROFILE IN AUTOMOTIVE ASSEMBLY: A MIXED-METHOD APPROACH
1 Daimler AG (GERMANY)
2 Cybernetics Lab IMA & IfU - RWTH Aachen University (GERMANY)
About this paper:
Appears in: INTED2021 Proceedings
Publication year: 2021
Pages: 10558-10568
ISBN: 978-84-09-27666-0
ISSN: 2340-1079
doi: 10.21125/inted.2021.2216
Conference name: 15th International Technology, Education and Development Conference
Dates: 8-9 March, 2021
Location: Online Conference
Abstract:
The German automotive industry is currently undergoing a structural transformation driven by global trends, which clearly leave their marks: Sales decrease in many markets, profitability is suffering from high investments in digitalization, electrification and autonomous driving. At the same time, customer demand for higher product varieties requires faster time-to-market, smaller lot size and cost savings. To adapt to constantly changing market needs, the demand for more flexibility in production environment increases. In this context, humans are called as a major enabler for production flexibility. This is in particular since robots are seen as not economically efficient for small batch sizes. Up to now, the automotive production is mainly automated except the assembly, which is characterized by manual work. For the future, it is expected that global trends influence not only product characteristics, but also production processes and the human workplace: For example, the human work tasks will get more complex and require problem-solving abilities because of increasing product and process complexity as well as the required interaction with smart devices. Moreover, the electric vehicle production requires the acquisition of new skills in working on high voltage equipment. Further, the ageing workforce increases the risk of physical disabilities. This illustrates the enormous challenges for the automotive industry to ensure that employees are deployed according to their physical and mental abilities, while at the same time meeting the increasingly demanding work requirements. The development of new worker competences will require great efforts and long-term qualification pathways. Therefore, it is all the more important that companies prepare themselves and the workforce for the urgency regarding the change of worker competences. This paper presents a profound study on the future competence profile of workers in German automotive assembly. The aim of this paper is to conduct a comprehensive study of future competences for assemblers, which is validated by experts from science and practice. For this purpose, a mixed-method approach is applied: Firstly, the most relevant trends and technical challenges with influence on the future automotive manufacturing are identified by literature review. Secondly, on this basis, future assembler competences are derived from an extensive literature review using future scenarios of automotive production. In total, ten significant competences (e.g. problem-solving skills, lifelong learning,...) are identified as crucial for the future automotive assembly. Thirdly, the individual competences are evaluated on a quantitative survey regarding their influence by global trends and technological challenges. The goal of the survey evaluation is to enhance the validity of the derived competences through verification by different departmental experts from science and practice. The study sample includes 66 responses of handpicked experts in the field of future competences in automotive production. The cross-sectional survey is conducted at different business functions (like production management, human resources, design and technology development) of automotive production, scientific institutes and trade unions in Germany. The results of the survey are discussed and the paper concludes with an outlook regarding future measures of an early and proactive development of the relevant assembler competence profile.
Keywords:
Assembler Competence Profile, Automotive Assembly, Global Trends, Worker Requirements, Mixed-Method Approach.