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Technology Serves People: Democratising Analytics and AI in the BMW Production System

In: Responsible Artificial Intelligence

Author

Listed:
  • Matthias Schindler

    (BMW Group – Innovation, Digitalisation, Data Analytics)

  • Frederik Schmihing

    (BMW Group – Innovation, Digitalisation, Data Analytics)

Abstract

Individualisation and an increasing number of variants characterise the production of premium vehicles in particular. This implies an increase in complexity in manufacturing. The principles of lean production form the basis for the continuous improvement of processes. Further optimisation of production can be achieved with data analytics and artificial intelligence (AI) methods. These innovations raise the issue of corporate social responsibility, CSR. This article describes the BMW Group’s approach to corporate social responsibility and the sustainable development of digitalisation in production. In addition to the technical aspects of data analytics and AI, the organisational implications are highlighted. For the BMW Group, the claim that ‘technology serves people’ means that production employees must understand the quality figures in their area and be able to independently carry out a root cause analysis in the event of an error. AI systems must be designed intuitively so that employees can tailor them to their specific application in self-service. The BMW Group places people—in the production system, especially the direct production employees—at the centre. Data analytics and AI must contribute to making work in the BMW production system more pleasant and even more attractive. The goal is a strength-based division of labour between humans and IT systems.

Suggested Citation

  • Matthias Schindler & Frederik Schmihing, 2023. "Technology Serves People: Democratising Analytics and AI in the BMW Production System," CSR, Sustainability, Ethics & Governance, in: René Schmidpeter & Reinhard Altenburger (ed.), Responsible Artificial Intelligence, pages 159-182, Springer.
  • Handle: RePEc:spr:csrchp:978-3-031-09245-9_7
    DOI: 10.1007/978-3-031-09245-9_7
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