MULTI-OBJECTIVE ROBUST PRODUCTION PLANNING CONSIDERING WORKFORCE EFFICIENCY WITH A METAHEURISTIC SOLUTION APPROACH

Timely delivery of products to customers is one of the main factors of customer satisfaction and a key to the survival of a manufacturing system. Therefore, decreasing wasted time in manufacturing processes significantly affects production delivery time, which can be achieved through the maximization of workforce efficiency. This issue becomes more complicated when the parameters of the production system are under uncertainty. This paper presents a bi-objective scenario-based robust production planning model considering maximizing workforce efficiency and minimizing costs where the backorder, demand, and costs are uncertain. Also, backorder, raw materials purchasing, inventory control, and manufacturing time capacity are considered. A case study in a faucet manufacturing plant is considered to solve the model. Furthermore, the ε-constraint method, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the Strength Pareto Evolutionary Algorithm 2 (SPEA2), and the Pareto Envelope-based Selection Algorithm II (PESA-II) are employed to solve the model. Also, the Taguchi method is used to tune the parameters of these algorithms. To compare these algorithms, five indicators are defined. The results show that the SPEA2 is the most time-consuming algorithm and the NSGA-II is the fastest, while their objective function values are nearly the same

Production Planning in Remanufacturing Systems with Uncertain Component Processing Time

Today’s manufacturing industries in many countries have developed systematic product recovery, remanufacturing and recycling procedures in an environmentally supportive manner to release the regulatory pressure as well as to achieve economic benefit. This thesis presents a mixed integer programming model addressing production planning problems in hybrid system of manufacturing and remanufacturing. The objective of solving the mathematical model is to minimize the total cost based on the optimal quantity of new items to manufacture and the optimal quantity of returned products to remanufacture in each period of the planning horizon. The proposed model has a distinctive feature that considers the uncertainty of remanufacturing time for the same type of returned products. A new heuristic solution method, similar to Silver-Meal heuristic for solving traditional lot-sizing problems, is developed to solve the considered production planning problems in hybrid manufacturing-remanufacturing systems is developed in this thesis. The developed heuristic is examined using various example problems generated in three dimensions (problem size, returned products quantity and category quantity). The results show that it can generate optimal or close-to-optimal solutions for all tested example problems with much reduced computational time. The model and the solutions were analyzed and sensitive analysis is conducted to investigate the performance of the developed model and solution method

Development of Gen2 RFID-based Closed-loop Supply Chain Management System

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 산업·조선공학부, 2018. 2. 박진우.With the extended producer responsibility, which is a countermeasure for environmental problems such as resource depletion in manufacturing industries, responsibility of manufacturers who produce automotive, electrical and electronic equipment has been extended beyond production, retailing, to collection and recycling of the end-of-life products. Particularly in the case of recycling, a legal system has been introduced that enforces recycling at a certain rate or more on a mass basis. In this background, scope of the supply chain management also has been extended beyond forward process, which consists of sourcing, producing, and delivery, to reverse process. It is called closed-loop supply chain in terms of constantly using the resources that have been put into the manufacturing ecosystem. Proper operation of the closed-loop supply chain can maximize economic profit by value creation along with whole product lifecycle as well as complying with environmental legislation. However, chronic uncertainties of reverse process cause inefficiency in terms of overall performance of closed-loop supply chain. In terms of physical flow, the timing and quantity of end-of-life product return is difficult to predict. Moreover, recycling network is complex because there are many participants in reverse process. In terms of product lifecycle, residual values of returned products are all different due to the factors like usage environments, user behaviors, and so forth. Moreover, this problem becomes even worse at component level. Many research efforts have been proved that real-information gathering can solve this problem. In this context, a system framework that minimizes uncertainties and facilitates various positive effects along with the product lifecycle by using the internet-of-things including radio frequency identification (RFID) and sensors, will be proposed in this dissertation. Unlike the existing approaches that only tag products, component-level individual tagging that tags not only products but also components will be proposed for more detailed lifecycle information management. Especially, encoding the family relationships among the components, by using user memory that is provided by Gen2 RFID protocol, will be proposed to extract new contribution. Information system including RFID tag encoding scheme, will be designed to strictly comply with the established standards to ensure compatibility within the industries in the future. Additionally, potential effects will be examined. Real-time monitoring and maintenance (RMM) and counterfeit prevention scheme, which are intangible effects in terms of product service in the middle-of-life phase, will be introduced. Especially, sweeping scan approach to prevent structural counterfeits of products by using the family relations in the user memory, will be introduced. Also it will be shown that the proposed system is valuable for remanufacturing process streamlining and hybrid remanufacturing/manufacturing production planning with numerical studies.1. Introduction 1 1.1. Product Recycling 1 1.2. Closed-loop Supply Chain 4 1.3. Internet-of-Things 8 1.4. Goal and Scope 10 2. Literature/Technology Review 15 2.1. Literature Review 15 2.2. Technology Review: RFID and Gen2 Standard 21 3. Analysis of Korean ELV Remanufacturing Industry 24 3.1. Overview 24 3.2. Problem Extraction and Classification 26 4. Design of the Proposed System 32 4.1. Lifecycle Information Gathering and Component-level Tagging 32 4.2. Information System Framework and Lifecycle Implications 37 4.3. Design of Data Architecture 46 4.4. Database Transactions for Potential Effects 57 5. System Implementation in the MOL Phase 61 5.1. Real-time Monitoring and Maintenance 61 5.2. Counterfeit Prevention 66 6. Remanufacturing Process Streamlining 70 6.1. Elimination of the Unnecessary Loop 70 6.2. A Requisite for Enhancement 77 7. Hybrid Production Planning for a Remanufacturing/Manufacturing System 87 7.1. Conceptual Modeling 87 7.2. Mathematical Modeling 94 7.3. Computational Results 101 7.4. Sensitivity Analysis 110 8. Conclusion 126 8.1. Summary 126 8.2. Limitations and Future Research Direction 129 Appendix. Numerical Experiment Settings 131 Bibliography 138 국문초록 149Docto