a.k. chanda

The use of material handling robots (MHRs) for efficient material handling operations in the flexible manufacturing systems (FMS) has gained wide popularity and acceptability across the automated production industries. The coexistent scheduling between jobs and MHRs improves the overall efficiency of the FMS significantly. In the present study, the coexistent scheduling between the MHRs and the jobs under production in the FMS is carried out by using an advanced grey wolf optimization (AGWO) algorithm. The proposed FMS layout is made up of the tandem flow path configurations for the movements of MHRs. The FMS constitutes six flexible manufacturing cells (FMCs) partitioned in six zones and served by six MHRs deployed in each partitioned zone for efficient material handling operations. To develop the coexistent schedule between MHRs and jobs, a combined objective function is formulated by combining the two diverging objectives and solved by using the AGWO algorithm. The combined objective function yield for coexistent production scheduling in FMS, operating with nineteen work centers (WC) and six MHRs to produce thirty-six types of jobs and sixty-six types of jobs in varying batch production quantities is also reported in the paper.

The selection of an appropriate cutting tool for the production of different jobs in a flexible manufacturing system (FMS) can play a pivotal role in the efficient utilization of the FMS. The selection procedure of a cutting tool for different production operations becomes more significant with the availability of similar types of tools in the FMS. In order to select and allocate appropriate tool for various production operations in the FMS, the tool selection rules are commonly used. The application of tool selection rules is also observed to be beneficial when a system demands two or more tools for the production operations at different work centers at the same time in the FMS. In this paper, investigations are carried out to evaluate the performance of different tool selection rules in the FMS. The performance of the tool selection rules is evaluated by simulation with respect to different performance parameters in the FMS namely makespan, mean work center utilization (%) and mean automatic tool transporter (ATT) utilization (%).