Part selection (PS) and machine loading (ML) are two major interrelated production planning problems in flexible manufacturing systems (FMSs). The two problems have been treated separately in most previous research work, thereby raising the possibility of conflicts and inconsistencies between the two sets of individually obtained solutions (Hwang & Shogan, 1989). This research is directed towards the development of an integrated approach to solve the combined part selection and machine loading problems in FMSS to obtain consistent solutions.

Three classes of FMSs are identified:​ FMS I, FMS II and the hybrid system (HS). FMSS I and and II are identified based on tooling strategies. The third class of FMSs is a hybrid system where conventional manufacturing systems (CMS) and FMS sub-systems exist concurrently. Decisions related to part selection, job allocation, tool selection and assignment and process route selection are considered for both FMSs I and II In the hybrid system, sharing of loads between CMS and FMS sub-systems is further investigated, in addition to the decision modules mentioned above.

Associated bicriteria models are developed for the combined PS and ML problems in the three classes of FMSS to take advantage of both productivity and flexibility that FMS can offer. The models, once solved, will yield a set of consistent solutions for both PS and ML problems. Example problems are solved for all of the developed models. The benefits of considering secondary objectives, and the effects of magazine capacity and available machining time on PS decision are discussed.

The solution algorithms for the models associated with FMSs I and II have been proposed through the Lagrangian relaxation based method incorporating the decomposition principle and column generation scheme. The FORTRAN 77 program is coded for a representative model (Mcdel M-1). Computational experience is presented for several sets of test problems on IBM 4381 mainframe. The efficiency of the algorithm and FORTRAN code are demonstrated through the test problems.