Abstract
In the conveyor-aided picking system, the shop-floor supervisor has to assign the picking tasks to workstations on conveyor based on loading balance between the workstations. In the past, the traditional distribution center that utilizes the conveyor-aided picking system rely on expertise of the supervisor to balance the tasks of workstations. The traditional decision process for workload balance is usually time consuming and inefficiency. In order to assist the supervisor to efficiently and accurately search a workload balance solution for workstations of the conveyer-aided picking system. This research proposed a quantitative methodology for workload balance by extracting the expertise of domain experts. Based on the proposed methodology, a computer-aided decision support system can be developed to automatically generate the workload balance solutions of the conveyer-aided picking system. The main idea of this research is to extract the empirical principles by interview with the domain experts and to establish quantitative indicators for workload balance. In addition, weightings of indicators can be derived from historical information. By utilizing the indicators for workload balance, the supervisor can objectively and efficiently determine the picking tasks of workstations. As a whole, this research provides a quantitative methodology and technique for the supervisor to efficiently and accurately determine the picking tasks of workstations in the conveyor aided picking system.