Abstract
ABSTRACTGlobalization and growing business dynamics lead to weakly harmonized supply chain (SC) systems. While smart technology offers innovation opportunities, supply chains often lack the integration needed to fully leverage resources and collaboration. A comprehensive systems engineering (SE)‐driven model for integrated innovation and optimization of smart SC business models is still missing. This study, through case research at SAP SE's Industry 4.0 division and three automotive companies, identifies key digital transformation objectives and interoperability gaps hindering smart opportunities. Systems engineering, supply chain management (SCM), and artificial intelligence (AI) methods were synthesized into a holistic SE‐driven model for transforming and optimizing SC business models. This model integrates management concepts like the theory of ambidexterity and dynamic capabilities, with SE methods capability engineering and complex adaptive systems, and semantic web concepts. Key SE contributions include meta‐modeling multi‐tier SC architectures, ensuring performance and resilience via simulations, and balancing value exploration and exploitation. Moreover, semantic harmonized and profit‐optimized SC ecosystems enable collaborative innovation for flexible, efficient manufacturing—a core Industry 4.0 principle. This SE‐driven model, validated by experts, provides a concise view of digital SC business models and a driver of generative design.
Published Version
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