Digital Engineering Platform for Synergistic Decision-Making In Manufacturing Plant Operations: Research Questions

Abstract

Decision makers in the manufacturing industry ranging from plant operators to senior management make decisions based on a combination of defined procedures and rules, expert inputs and analysis, and their own knowledge and understanding of the problem context. Decision spaces are getting more complex, with the business paradigms shifting towards autonomous plants and servitization of products. With the advent of Internet of Things (IoT) and technologies such as machine learning and digital twins, the resources and capabilities available to decision-makers are expanding vastly. The gamut of concerns to be addressed is also expanding, with new challenges such as sustainability and its concomitant regulations and the pressure to make businesses more socially aware. Further, it would be ideal if decision-makers could easily draw upon the relevant knowledge, intuition, and experience of human experts, as well as knowledge currently buried in documents and data, and synthesize all the diverse inputs towards informed decision-making by integrating cyber, physical, and social systems. This motivates the question, “How do we create platforms that synergize these diverse knowledge sources and capabilities to facilitate better decision-making?” In this paper, we try to delve into identification of few key research questions and discuss opportunities and requirements around the same, that can aid in creating a digital platform to synergize all these diverse inputs and support decision-making. While this paper uses decision-making in manufacturing plant operations to explore the challenges and discuss one possible approach, the problem of enabling seamless synergy between the knowledge and capabilities of diverse human, IT and physical elements applies to all Cyber Physical Social Systems (CPSS).