Scheduling and machining of jobs through parallel nonidentical machine cells

Process planning and scheduling are two functions commonly encountered in any manufacturing system. Despite the well recognized interdependencies between them, research in these areas have progressed separately as if there is virtually no relationship between the two. The result of such separate development in terms of manufacturing systems planning can lead to the adoption of policies that are far from optimal. In this paper, a modelling approach that integrates the functions of job scheduling and process planning in cells with parallel and nonidentical machine groups is presented. A heuristic algorithm is developed that allocates the jobs to machines while at the same time generates the best machining parameters to use for each job in order not to violate any job and machine related restrictions. The basis of optimization is the minimization of total manufacturing cost.