Modeling Supply Chain Ecosystem Architecture to Support Digital Twins

Ola G. Batarseh
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Ola G. Batarseh: Dassault Systemes

Chapter Chapter 6 in Optimizing Supply Chains Through Digital Twins, 2025, pp 85-100 from Springer

Abstract: Abstract Supply chains are becoming increasingly complex and vulnerable to disruptions, from geopolitical conflicts to global health crises. In response, a model-based approach is proposed to architect and analyze supply chain ecosystems. This chapter explores how Model-Based Systems Engineering (MBSE) can be applied to supply chains through the Unified Architecture Framework (UAF). By leveraging UAF’s enterprise viewpoints and aspects, supply chain architects can create a traceable, interconnected digital architectural model that enables early-stage validation, predictive analysis, and digital twin development. The chapter introduces the enterprise architecture framework UAF, highlighting its viewpoint: strategic, operational, resources, security, and others, along with their cross-allocation. Using Dassault Systèmes’ CATIA Magic Systems of Systems Architect (MSOSA), the chapter walks the reader through digital views of the supply chain, demonstrating how they support real-time inventory management, logistics coordination, cybersecurity controls, and roadmap planning. The ability to link enterprise elements through a digital thread provides a maintainable architecture along with actionable insights. By replacing fragmented, document-based approaches with a single authoritative source of truth (ASOT), this model-based approach strengthens supply chain resilience, enhances adaptability, and enables organizations to systematically manage risks and disruptions. The chapter concludes by discussing scalability, reusability, and the role of enterprise architecture in supporting digital twin adoption for modern supply chains.

Keywords: Model-Based Systems Engineering (MBSE); Unified Architecture Framework (UAF); Digital Twin; Supply Chain Architecture; Authoritative Source of Truth (ASOT) (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-032-08147-6_6

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