Process innovation strategies for implementing effective smart factories in German manufacturing companies

  • Daniel G. Jentzsch

    Student thesis: Doctoral Thesis


    The importance of Smart Factory technologies in the context of Industry 4.0 is growing for manufacturing companies in Germany due to ongoing globalisation and the ambition to produce highly individualised workpieces at an efficient price. However, basic knowledge about the Smart Factory framework and the approach to implementation of the associated technologies and processes is missing in most companies. Concurrently, the importance of process innovation, including its challenges and success factors in business and especially in manufacturing companies, has been identified by scholars, including governmental organisations in Germany, as a way to foster the innovation spirit.

    The research in this thesis therefore aims to explore the specific targets, success factors, requirements and challenges of Smart Factory process innovations in German manufacturing companies, and so to create a comprehensive Smart Factory process innovation model affording an accessible visual overview of the required actions and recommendations for manufacturing companies in Germany to improve their innovation capability.

    To achieve the goal of this research, a pragmatic abductive research design has been applied, relying on 15 qualitative semi-structured in-depth interviews with 16 industry experts in chosen best practice German manufacturing companies. The research data have been coded using template analysis in an overall research strategy derived from grounded theory.

    The Smart Factory Process Innovation Model recommended by this research therefore provides a comprehensive overview of the necessary actions, success factors and requirements in the different phases and stages of the innovation process, thereby contributing to process innovation knowledge, as well as to the practice of improving the innovativeness of German manufacturing companies
    Date of AwardSept 2019
    Original languageEnglish
    SupervisorDavid Grant Pickernell (Supervisor) & Alan Tait (Supervisor)

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