Concurrent scheduling and layout of virtual manufacturing cells considering assembly aspects

Cell formation, scheduling, and facility layout are three main decisions in designing manufacturing cells. In this paper, we address the integration of these decisions in virtual manufacturing cells considering assembly aspects and process routing. We develop a mathematical model to determine the machine cells, the layout of machines and workstations on the shop floor, the processing route of parts, and the production sequence of operations on the machines. In this mathematical model, material handling costs and cycle time are minimized. To the best of our knowledge, this is the first paper that concurrently addresses the scheduling and layout of virtual manufacturing cells with assembly aspects and so-called criteria. To effectively solve the problem, a Population-based Simulated Annealing (PSA) combined with linear programming is proposed. The practical usability of the developed model is demonstrated in a case study. Finally, instances from the literature are solved to evaluate the performance of the PSA. The comparison results showed the superior performance of the PSA in comparison with CPLEX solver and standard simulated annealing.

Application of Ant algorithm in virtual manufacturing cells

In this work, Ant algorithm is applied for scheduling tasks in virtual manufacturing cells (VMC). In virtual manufacturing cells, machines are randomly arranged in the workshop area. The task to be processed selects appropriate machines based on pre-determined objectives. The selection of the machinery turns into a complicated problem if there are several tasks for processing. There are a limited number of machines of any type in this workshop and the objectives are the minimization of the range of operation (sequence of tasks and starting time for each task) and the sum of the distances travelled by the entire piece. A number of standard problems were solved using the Ant algorithm in order to evaluate the efficiency of the algorithm. The results obtained show that the Ant algorithm offers good solutions in shorter times.