Optimal operations sequence retrieval from master operations sequence for part/product families

This research capitalises on commonalities between members of a product family to increase the speed, consistency and efficiency of constructing a master operations sequence and optimal operations sequences for new variants. Two novel mixed integer programming (MIP) models are developed for generating master operations sequence based on available operations sequences of a family of part/product variants. The use of master operations sequence reduces the time, cost and effort required for developing new operations sequences, hence improving the planning efficiency and productivity. The first MIP model is developed for variants with serial operations sequence while the second is a generalised model for serial, networked operations sequences or a combination of both structures. The developed models generate master operations sequences which have minimum total dissimilarity distance from existing variants. The master operations sequence is then used to construct the operations sequence for new variants falling within or significantly overlapping with the boundary of the considered product family. As the number of operations increases, the efficiency of mathematical models decreases. Therefore, a novel algorithm is proposed to generate master operations sequences for product variants with any type of process sequence structure (i.e. serial, networked, or combination). Computational results demonstrated the capability of developed MIP algorithms to find optimum solutions and optimal operations sequence for new variants in a fraction of a second in most cases of small, medium and large size studied problems. Two assembly and fabrication case studies are provided for demonstration.