Modelling of Smart Manufacturing System for Layout and Capacity Planning

Modern consumers are expecting highly personalised services and products with reduced cost and lead time. This has driven companies to digitalise as well as automate their operations and introduce Decision-Support Systems (DSSs) into their planning, towards the paradigm of smart manufacturing. However, prior to the transformation, companies must meticulously plan and quantify the productivity gains with accurate, data-driven projection to justify the return of investment. Specifically, to evlauate the (re-)layout feasibility of newly acquired and existing production resources and to make throughput estimates. In this paper, a flexible placement method that translates the approximate locations provided by existing layout planning algorithm to exact production floor locations is proposed. Unlike current placement methods, it considers both new and existing production resources that cannot be relocated. In the area of capacity planning, a modelling approach that projects the production volume increment in smart manufacturing operations is proposed. It utilises passive data objects and active agents to accurately represent the production status and distributed decision-making in DSSs respectively. Both proposed approaches have also been validated in a smart manufacturing environment, whereby a production floor layout was planned and minimal operating hours was computed based on the given production target.