CHALLENGES OF DATA ACQUISITION FOR SIMULATION MODELS OF PRODUCTION SYSTEMS IN NEED OF STANDARDS

In this paper, we analyze the challenges in data acquisition for simulation models of production systems based on two cases from the robotics and aerospace industries. Unlike prior research, we focus not only on the challenges of data acquisition but also on how these challenges affect decisions in production systems. We examine this linkage using the concepts of strategic objectives, decision areas, and internal fit from operations management literature. Empirical findings show that for data acquisition to lead to improved production system performance it is necessary to develop standards. Standards should consider ownership of data by different functions within a manufacturing company, alignment of data to performance measurements, and the connection between data, information, and production decisions. Using these concepts, this paper proposes a set of guidelines that facilitate the standardization of data acquisition for simulation models in production systems. We conclude by discussing the managerial implications of our findings.

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