Optimal Sequencing of Machining Operations for Changeable Manufacturing

Abstract

Process planning is a key enabler of the various production planning activities, that lies at the core of current state-of- the-art product lifecycle management key components. Operations sequencing is the first and main step to take place at the macro planning level, and is defined as the problem of sequencing a global set of machining sub-operations required to machine a certain part in order to minimize changeover time/cost while satisfying a number of precedence constraints. The problem is well known to be NP-complete. An integer based model has been suggested to minimize the changeover time between successive sub-operations, and was used as the basis for the developed evolutionary meta- heuristic. A variant of the canonical Genetic Algorithms is developed, where tailored genetic operators specific to the problem at hand were used. A greedy algorithm is developed for initialization of the genetic population. The developed approach was applied to a benchmark problem of varying geometry that requires different machining configurations; results proved to be superior in terms of quality of solutions. Keywords: