Facing environmental uncertainties with the digital twin technology : a case study of german automotive OEMs

• Autor(a) principal: Brück, Laura Sophie
• Data de Publicação: 2022
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.14/40206
• topic: Germany; Automotive industry; Automotive development; Automotive production; Digital twin technology; Environmental uncertainty; Alemanha; Indústria automóvel; Desenvolvimento automóvel; Produção automóvel; Tecnologia digital twin; Incerteza ambi; Domínio/Área Científica::Ciências Sociais::Economia e Gestão

The German automotive development and production process is vulnerable to environmental uncertainties, threating the goal of low-cost and efficient processes for original equipment manufacturers (OEMs). Uncertainties like changing market regulations, market price volatility of materials, or product market feasibility force the OEM to adapt its processes and vehicles. Lack of technical resources, good coordination and flexibility issues across actors involved in the problem space are the main cause of adaption failure leading to production stops and market delays. Past research has shown how OEMs integrated the digital twin technology (DTT) into their ecosystem. Digital twins (DTs) are real-time virtual presentations of their physical counterparts simulating and predicting its behavior, leading to reduced planning complexity. Different DTs can be created for vehicles (parts, software, processes, technologies) or factories (production lines). Thus, this research will provide an explanatory case study comparing how OEMs adapt automotive development and production processes to environmental uncertainties without incorporating DTT versus with DTT. It consists of qualitative data only: expert interviews and literature research. Results suggest DTT provides a single source of truth by linking different DTs, actors, systems and work processes allowing for hybrid analyses instead of discrete analyses with different modules and simulators, providing fluidity of knowledge and inclusivity across actors involved. The visualized data provides simulations and predictions to evaluate business decisions digitally first and synchronizing updates across actors involved supporting coordination. Ultimately, supporting the concept of DTT to help OEMs adapt efficiently.