A Digitised AI and Simulation Ecosystem for Enabling Data-driven Decisions

Abstract: As data availability increases so do the opportunities within businesses. Companies need to explore technologies that are able to exploit and capitalise on this vast amount of data in order to stay relevant in today’s competitive market. Artificial intelligence and simulation are two promising technologies that are able to manage and utilise these large amounts of data. This paper explores the opportunities and challenges that exist of combining artificial intelligence with simulation in order to achieve data-driven decisions within industries. Although these two technologies are well researched in isolation, their combination and synergetic effects remain largely unexplored. The aim of this study is to survey this existing vacuum by performing a literature review and producing a digitised AI and simulation ecosystem that encapsulates the opportunities and challenges enabled by these two technologies. This research explored this ecosystem by applying and developing it on a real case study of an automotive parts supplier’s production process. It was concluded that this modularised digitised ecosystem could act as an alternative to expensive and generic software solutions due to its high customisation, simple integration and cost-efficiency, especially for SMEs. The study also concluded that adding additional AI and simulation models to the ecosystem reduces the modules’ unit costs since they can share some high cost structures such as: databases, servers and user-interfaces; this idea was encapsulated in the term digitised economies of scale.