A study on lot streaming models in flow shops

• Main Authors: Chang Jen-Huei, 張仁輝
• Other Authors: Chiu Huan-Neng
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/65610289112858754639

博士 === 國立臺灣科技大學 === 工業管理系 === 92 === Time-based strategies have been widely adopted in a variety of enterprises and optimized production technology has been successfully implemented in a number of production systems. These two important developments have made lot streaming receive much more attention from both researchers and practitioners. In today’s production environment, lot streaming has been shown to be an effective technique for compressing the manufacturing lead time and reducing the work-in-process inventories. Consequently, this dissertation determines three research topics to explore the lot streaming problems and to analyze the benefits of using this technique. To date, there are no yet review papers on lot streaming. Therefore, this dissertation makes a comprehensive survey to fill this research gap. First, a uniquely categorized structure is proposed and a notation set is defined to characterize the existing lot streaming problems. Then, the literature is divided into four categories: single-product time-related, multi-product time-related, single-product cost-related, and other problems. For the lot streaming problems in each category, the studied problem setting, the used methodology, and the drawn conclusion are presented. In the single-product time-related problems, a more general mathematical programming model with a limited number of capacitated transporters is developed to carefully address the impact of transportation activities between manufacturing stages on makespan. Two efficient heuristic procedures are proposed due to the large amount of computational time required to solve the proposed mathematical programming model. A practical case is demonstrated to show the real-world usefulness of the two proposed heuristic procedures. Additionally, two numerical experiments are conducted. The purpose of the first experiment is to analyze the effects of changing the parameters in the proposed mathematical programming model on the optimal solution. The second experiment aims to verify the effectiveness of the two proposed heuristic procedures. In the single-product cost-related problems, this dissertation develops two economic production lot-sizing models to obtain the optimal processing batch size and the optimal number of transfer batches that minimize the total annual cost. In the first model, a more complete and accurate method is proposed to measure the costs of raw materials, work-in-process, and finished-product inventories. The total cost includes the setup cost, the transfer batch transportation cost, the three-type inventory holding cost, and the finished-product shipment cost. The second model contains not only the four costs in the first model, but also the imputed cost associated with makespan. Two cost functions with dual decision variables are proven to be convexity, and two methods are suggested to find the optimal solution with integer number of transfer batches, respectively. Finally, a numerical experiment is implemented to analyze the impacts of changing the model parameters on the optimal solution and to compare the optimal solutions to the two proposed lot-sizing models.