A modelling framework to support integrated design of production systems at early design stages

Abstract

Multidisciplinary, large scale, and dynamic essence of production-logistic systems make their design knowledge complex. As a result, designers from different disciplines mostly design these systems with sequential approaches. This does not address the impact of single design decisions on overall system performance, which may lead to inconsistencies between different disciplines or failures. This paper aims to realise the integrated design of such systems by introducing a framework that incorporates Systems Engineering and Object-Oriented methods to develop a model that holistically embodies design knowledge of such systems. This model is constructed in Finite-State-Machine formalism to achieve an executable architecture and integrated with optimization models to allow simulation of alternatives and to observe the impact of design decisions on system behaviour. Supportive algorithms are introduced for refinements of design alternatives according to the simulation results. A fuzzy assessment approach is introduced to also assess the alternatives against qualitative criteria. The framework integrates simulation and fuzzy assessment results and performs a multi-criteria assessment to select an alternative for the detailed design. Therefore, the framework can stand as a decision support framework at early design stages, giving insights to designers about the impact of single design decisions on system overall performance and satisfaction of various objectives.