Cell Formation And Scheduling For Cellular Manufacturing Enterprises

Short production life cycles, short delivery times, high production variety, and diverse customer needs have challenged manufacturers to improve their production efficiency and meet changing market demands quickly for holding a solid market share in the fierce competition. Cellular manufacturing is a lean manufacturing approach that integrates the high flexibility of individual production and the high efficiency of mass production, and reduces the cost of individual production and the rigidity of mass production. Cellular manufacturing incorporate efficiency and flexibility, and develops self-discipline and independence in an enterprise organization. Currently, Cellular manufacturing is becoming more and more popular. Reported benefits of the implementation of cellular manufacturing systems include reductions in work-in-process, finished goods inventory, response time to orders, transportation distance/time, setup time and production cost.Currently, most production enterprises in China engage in extensive management procedures, which focus on improving production output. But the enterprises ignore the huge waste of inventory, labor, material, time, space and transportation in the traditional mass production, which make them difficult to cope with those problems under the considerable pressure of cost, delivery and quality. Hence, China companies are required to establish a feasible cellular production system to implement the intensive management, enhance core competitiveness and keep pace with the world's leading manufacturing companies.This research was financially supported by National Science Fund for DistinguishedYoung Scholars and Innovative Research Groups.The background of this dissertation is theimplementation and operation of cellular manufacturing systems for discrete manufacturingenterprises. Based on analyzing the research status quo of cellular manufacturing, especiallyfor cell formation and scheduling problem, this dissertation studies several crucial problemson cell formation and scheduling. The major research results of this dissertation falls on fiveaspects as follows:(1) A multi-period, multi-objective dynamic cell formation problem with alterable cell configuration under varying market demands environment is studied. Machine relocation cost, utilization rate of machine capacity and total number of inter-cell moves are considered, and a nonlinear multi-objective mathematical programming model of dynamic cell formation approach is proposed. To solve the model effectively, a scatter search based on heuristic approaches is developed, which includes diversification generation method, global criterion method, reference set update method and other improvement methods to form alterable manufacturing cells.(2) A multi-period, multi-objective dynamic cell formation with machines duplication is studied. Considering same type machines assigned in several cells in one period, a nonlinear multi-objective mathematical model of the addressed problem is built by weighing the three objectives including the total cost in the process of cell formation, maximum deviation of workload from available capacities of machines, and total number of inter-cell moves. Using adaptive niche technique, penalty technique, double roulette wheel method, and reserving elite strategy, a random weight multi-objective genetic algorithm based on the reserving elite is designed for solving the multi-objective dynamic cell formation problem with machines duplication.(3) A parts scheduling problem in cellular manufacturing system considering parts with different process routings in multiple cells is studied. To develop processing sequences for the parts in cells, two nonlinear mathematical programming models of the problem are proposed respectively with the objective of minimizing the flow time and tardiness penalty in a cellular manufacturing system. A scatter search approach for the problem is developed, which improves diversification generator to generate a collection of diverse initial solutions, and develops the reference set update method, subset generation method, solution combination method and improvement method for the parts scheduling problem.(4) A joint decision of cell formation and cell scheduling in a cellular manufacturing system is studied. An integer programming model including a computation rule for the joint decision problem is proposed with the objective of minimizing the total tardiness penalty cost. To solve the model effectively, a Lagrange relaxation decomposition method with heuristic is developed. Using the method, the addressed problem is solved by decomposing into two sub-problems, i.e. cell formation sub-problem and cell scheduling sub-problem. After linearizing the model of cell formation sub-problem, it is solved by the optimizer CPLEX. A scatter search approach is developed to solve cell scheduling sub-problem. Combined with the Lagrange multipliers, cell scheduling sub-problem takes into consideration the assignment of part families and the associated machine groups to each cell, when it sequences the processing of the parts on each machine in cells. Using the method, the joint decision of cell formation and cell scheduling is solved.(5) A joint decision of cell formation and parts scheduling with machines duplication is studied, which consider each type of machine and part with multiple numbers and parts required processing and transferring in batches in a cellular manufacturing system. A mathematical model for the joint decision problem, with nonlinear terms and integer variables, is developed. To solve the model for practical purposes, a scatter search approach with dispatching rules is proposed, which interactively uses a combined dispatching rule and considers two different combination methods and two improvement methods to further expand the conceptual framework and implementation of the scatter search so as to better fit the addressed problem. This scatter search approach interactively uses a combined dispatching rule to solve a scheduling sub-problem corresponding to each integer solution visited in the search process. The joint decision of cell formation and parts scheduling with machines duplication is solved by the proposed approach.