Scheduling Manufacturing Systems in an Agile Environment

Producing customized products to respond to changing markets in a short time and at a low cost is one of the goals in agile manufacturing. To achieve this goal customized products can be produced using an assembly-driven product differentiation strategy. The successful implementation of this strategy lies in efficient scheduling of the system. However, little research has been done in addressing the scheduling issues related to assembly-driven product differentiation strategies in agile manufacturing. In this paper, scheduling problems associated with the assembly-driven product differentiation strategy in a general flexible manufacturing system are defined, formulated, and solved. The manufacturing system consists of two stages: machining and assembly. At the machining stage, multiple identical machines produce parts. These parts are then assembled at the assembly stage to form customized products. The products to be produced in the system are characterized by their assembly sequences that are represented by different digraphs. The scheduling problem is to determine the sequence of products to be produced in the system so that the maximum completion time (makespan) is minimized for any given number of machines at the machining stage. The scheduling problems discussed in this paper have not been solved in the literature. The originality of the paper lies in defining and formulating the problems in the context of agile manufacturing and developing optimal and near-optimal for solving them. The heuristic algorithm solves the scheduling problem in two steps. First, an optimal aggregate schedule is determined by solving a two-machine flowshop problem. Next, the optimal aggregate schedule is decomposed by solving a simple integer programming formulation model. The computational experiment shows that the heuristics provide optimal and near-optimal solutions to the scheduling problems. INTRODUCTION Producing customized products in a short time at low cost is one of the goals of agile manufacturing. To achieve this goal in a manufacturing system, products are differentiated either by a machiningdriven or an assembly-driven differentiation strategy. When product differentiation takes place at the machining stage, non-standard and complex parts are machined with relatively complex machines at the machining stage and assembled at the assembly stage with relatively simple assembly equipment. This machining-driven strategy relies on machining to express model mix and achieve flexibility. When product differentiation takes place at the assembly stage, simple and common parts are machined with simple machines at the machining stage and assembled at the assembly stage with relatively novel assembly techniques. The successful implementation of these two strategies lies in efficient scheduling of the system. However, little research has been done in addressing the scheduling issues related to assembly driven product differentiation strategy in agile manufacturing, especially when products with complicated assembly sequences are produced. In this paper, the scheduling problems related to the assembly-driven product differentiation strategy for agile manufacturing are formulated and solved. The structure of the manufacturing system that implements the assembly-driven product differentiation strategy in agile manufacturing is shown in Figure 1. The manufacturing process in the system consists of two stages: machining and assembly. There are m identical machines at the machining stage and there is one assembly machine at the assembly stage. The machining operations include all activities that consist of material-removal operations. Assembly involves assembling the machined parts to form the required products. Figure 1. The general structure of the manufacturing system The originality of the paper lies in formulating scheduling problems in the context of agile manufacturing and developing optimal and near-optimal methods to solve the problems. Heuristics for solving effectively the scheduling problem are developed. The heuristics solve the scheduling problem in two steps. First, an optimal aggregate schedule is determined by solving the scheduling problem as a two-machine flowshop makesapn scheduling problem. The optimal aggregate schedule is then decomposed by solving a simple integer programming formulation model to obtain a feasible solution to the scheduling problem. A tight lower bound on the optimal makespan is also developed to evaluate the effectiveness of the heuristics. The computational experiment shows that the heuristic provides optimal and near-optimal solutions to the scheduling problems. The remainder of the paper is organized as follows. In Section 2, scheduling problems to be solved in this paper are formally defined. Literature on solving related scheduling problems is reviewed in Section 3. Section 4 focuses on the methods development for solving the scheduling problems. The computational results for solving the scheduling problems with the developed solution approaches are provided in Section 5. Finally, Section 6 concludes the paper. PROBLEM DEFINITION In this section, the scheduling problems related to implementation of the assembly-driven product differentiation strategy for agile manufacturing are defined. The Scheduling Problem: There are m identical machines at the machining stage and there is single assembly equipment at the assembly stage. The objective of the scheduling is to assign parts and subassemblies/assemblies to the machines at the machining stage and determine the processing Assembly Raw material Parts Finished products Machine 1