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Abstract
Production, assembly or logistic systems exist in many domains. More than 50% of life cycle performance, costs and environmental impacts of such systems are due to those decisions that are made in the early design stages of these systems. The large scale, multi-disciplinary, and dynamic essence of such systems make their design considerably challenging. Hence, mostly sequential design approaches are followed, which the design in each lower level is finalized before proceeding to the next level and designers from different disciplines design these systems in silos, which this may lead to inconsistencies in later stages or missing a good design solution. This research aims to propose a modelling methodology that allows having an integrated approach in the early design stages of such systems. The proposed methodology incorporates certain modelling approaches to conceptually capture the complex structure of such systems due to their multi-disciplinary and large scale essence. The proposed methodology embodies such a conceptual structure in a modelling formalism that results in an executable artefact that can also capture the dynamic nature of such systems by means of simulation. The methodology integrates the resultant executable artefact with optimization models and supporting algorithms, which jointly allow an integrated design. The methodology allows generating and simulating different design alternatives in one model and consequently observing the impact of different design decisions on system integrated performance as a result of dynamic interactions in the system. The systematic interconnection between the methodology artefacts allows proper data exchange between them assuring data consistency across the methodology. The methodology also incorporates the expert’s opinion into a fuzzy assessment methodology to realize multi-aspect design assessment. Therefore, the methodology can be used as a decision supporting methodology to support the design in the early design stages of such systems.