mahdi khaki - Dept‘ of Industrial Eng, University ۰fKurdistrm, Sanandaj, Iran

This study considers a manufacturing robotic cell including two identical CNC machines and a material handling robot. The robotic cell produces a set of parts of the different types that presents a flow-line manufacturing system. Parts which require the completion of a number of operations are to be produced in a cyclic scheduling environment. The sequencing of parts and allocations of the operations to the machines are variable and also the processing time of an operation on a machine can be changed between two upper and lower bounds. The new idea behind this study is considering a bi-criteria model which determines the allocation of the operations to the machines, the sequencing parts to the production cycle, the processing times of the operations on the machines, and the robot move sequence that jointly minimize two objective functions; i.e.; the cycle time and the total manufacturing cost. Mathematical models for the two 1-unit cycles and a genetic algorithm with numerical analysis of the model are provided and the efficiency of the approach in terms of the solution quality is shown. The genetic algorithm proposed in this paper is the second version of the Non-dominated Sorting Genetic Algorithm which is called NSGA-II. Goal programing has also been used in order to handle the multiple objective measures.

Cycle time; Total cost, 2-Machine robotic cell; Part sequencing; Robot moves sequence