Digital Value Stream Analysis and Evaluation for Data Farming Based Strategic Production Network Design

Abstract

Industrial companies are responsible for a significant portion of global trade, as they operate global and regional production networks. The value stream in production networks, comprising material and information flows between dispersed yet interconnected sites, is highly complex but crucial to manage in order to deliver the final product to the customer. In strategic network design, network planners face challenges in identifying an efficient value stream from the large solution space of possible alternatives and understanding the downstream effects of local planning decisions. Although data-driven Value Stream Mapping (VSM) is the state-of-the-art approach for analyzing and improving existing value streams, its application in strategic production network design faces the challenge of data scarcity. While simulation experiments can be used to generate datasets for multiple alternative value stream scenarios, a data-driven approach for analyzing and evaluating value streams that can serve as decision support for network planners is currently missing. To address this deficit, this article introduces a data-driven value stream analysis and evaluation approach that uses simulation data of multiple value stream scenarios in production networks. It incorporates a systematic, process mining-based analysis that utilizes visual analytics concepts to support decision-making in strategic network design, leading to an efficient value stream. The approach integrates the traditional steps of VSM, enhanced by process-based cost and sustainability evaluations, to provide a comprehensive understanding of cause-and-effect relationships. An industrial use case is presented to demonstrate the applicability of this approach.