Mehmet Ali Ilgin

Environmentally conscious manufacturing and product recovery (ECMPRO): A review of the state of the art.

Gungor and Gupta [1999, Issues in environmentally conscious manufacturing and product recovery: a survey. Computers and Industrial Engineering, 36(4), 811-853] presented an important review of the development of research in Environmentally Conscious Manufacturing and Product Recovery (ECMPRO) and provided a state of the art survey of published work. However, that survey covered most papers published through 1998. Since then, a lot of activity has taken place in EMCPRO and several areas have become richer. Many new areas also have emerged. In this paper we primarily discuss the evolution of ECMPRO that has taken place in the last decade and discuss the new areas that have come into focus during this time. After presenting some background information, the paper systematically investigates the literature by classifying over 540 published references into four major categories, viz., environmentally conscious product design, reverse and closed-loop supply chains, remanufacturing, and disassembly. Finally, we conclude by summarizing the evolution of ECMPRO over the past decade together with the avenues for future research.

Optimal End-of-Life Management in Closed-Loop Supply Chains Using RFID and Sensors

Wireless communication and monitoring devices, namely, radio frequency identification (RFID) tags and sensors, capture and store dynamic life-cycle information during the economic life of the products. RFID tags deliver this information to a computer system when the products are returned to disassembly centers in a closed loop supply chain (CLSC) system. By means of this technology, content of each product and component conditions are known without disassembly and inspection. Life cycle information also makes it possible to estimate the remaining life of the components and enables the fulfillment of remaining lifetime-based demands. This paper presents an Advanced Repair-to-Order and Disassembly-to-Order (ARTODTO) model. ARTODTO model deals with the products that are embedded with sensors and RFID tags. The goal of the proposed model is to determine how to process each and every end-of-life product (EOLP) on hand to meet used product and component demands as well as recycled material demand. The model considers disassembly, repair, and recycling options for each EOLP in order to satisfy material and remaining-life-time-based (sophisticated) component/product demands and minimize the total cost. Outside component procurement option is also assumed to be available.

Coping with disassembly yield uncertainty in remanufacturing using sensor embedded products

This paper proposes and investigates the use of embedding sensors in products when designing and manufacturing them to improve the efficiency during their end-of-life (EOL) processing. First, separate design of experiments studies based on orthogonal arrays are carried out for conventional products (CPs) and sensor embedded products (SEPs). In order to calculate the response values for each experiment, detailed discrete event simulation models of both cases are developed considering the precedence relationships among the components together with the routing of different appliance types through the disassembly line. Then, pair-wise t-tests are conducted to compare the two cases based on different performance measures. The results showed that sensor embedded products improve revenue and profit while achieving significant reductions in backorder, disassembly, disposal, holding, testing and transportation costs. While the paper addresses the EOL processing of dish washers and dryers, the approach provided could be extended to any other industrial product.

An approach to quantify the financial benefit of embedding sensors into products for end-of-life management: a case study

ABSTRACT Reverse logistics (RL) involves all the activities required for the collection and recovery or disposal of end-of-life (EOL) products. Various models have been developed for the design and management of RL networks. In all these models, materials flow according to the principles of traditional push system which results in excessive inventories. While implementation of just-in-time (JIT) would normally be a viable alternative, it requires the arrival of on-time and high-quality materials. However, in RL networks, arrival times and quality as well as quantity of EOL products are highly stochastic. The conflicting characteristics of JIT and RL make it challenging to integrate these two initiatives in their current forms. To overcome the integration difficulties, we propose and analyze an RL system controlled by a multi-kanban system (MKS), a novel JIT-based methodology originally developed for disassembly lines. MKS is a superior system that tames and controls the chaos created by the stochastic behavior of RL networks. To further exploit the efficiency of MKS, we explore the benefit of sensors embedded in products for detecting non-functional and/or missing components before disassembling the products. Separate experimental design studies based on orthogonal arrays are carried out for the disassembly of conventional products and sensor-embedded products (SEPs). Then, the results of pair-wise t-tests comparing the two cases based on different performance measures are presented. The results show that SEPs provide significant improvements in total revenue and profit while reducing holding, backorder, disassembly, transportation, testing and disposal costs.

Joint Optimization of Transportation and Spare Parts Inventory Policies in a Reverse Logistics Network Using OptQuest

The aim of this study is the joint optimization of the transportation and spare parts inventory policies in a reverse logistics (RL) network designed for End of Life (EOL) television (TV) recyling. Besides recycling, Printed Circuit Boards (PCBs) recovered from EOL TVs are used to meet the spare PCB demand. In order to model this RL network with its disassembly, transportation and spare parts inventory related aspects, a discrete event simulation (DES) model has been developed in detail using Arena simulation software. Next, Arena OptQuest has been used to propose optimum number and size of trucks together with the optimum reorder (s) and order quantity (Q) levels for the spare PCBs based on the minimization of total cost which includes inventory holding, PCB recovery, new PCB acquisition, truck amortization and operating costs.© 2008 ASME

Use of sensor embedded products for end of life processing

Sensors embedded into products during the production process have a potential to decrease disassembly yield uncertainty by detecting non-functional or missing components prior to the actual disassembly process. The aim of this study is the quantitative evaluation of the impact of sensor embedded products (SEPs) on the performance of an appliance disassembly line. First, separate design of experiments studies based on orthogonal arrays are performed for the cases with and without SEPs. Discrete event simulation models of both cases were developed to calculate various performance measures under different experimental conditions. Then, the results of pair-wise t-tests comparing the two cases, based on different performance measures, are presented. The results show the superiority of SEPs over conventional products for all performance measures considered in the study.

The disassembly line: balancing and modeling, by S.M. McGovern and S.M. Gupta

Disassembly, the process of systematic separation of a product into its components, subassemblies, materials or other groupings, has gained a lot of attention in the literature during the past decade or so due of its role in product recovery. While disassembly is also an indispensable part of maintenance and repair operations, the main phenomenon fueling research in disassembly is the need for the environmentally benign processing of post-consumer products which, in recent years, are disposed of by the consumers at an ever-increasing rate due to rapid technological advancements. Almost all end-of-life (EOL) products processing options (e.g. recycling, remanufacturing and disposal) require some level of product disassembly. Hence, the profitability of EOL products processing operations is unavoidably dependent on the cost-effective planning of product disassembly. Although it is possible to carry out disassembly operations in a disassembly cell or in a single station, the highest efficiency is provided by a disassembly line. However, in order to obtain maximum output from a disassembly line, one has to deal with various problems including the disassembly sequencing of EOL products, the determination of the minimum number of workstations required and balancing the workload at these workstations. ‘The Disassembly Line: Balancing and Modeling’ is the first book in the world written exclusively to address the issues associated with disassembly lines. The authors, who are well-known in the area of disassembly research, provide a comprehensive and systematic coverage of disassembly lines and suggest ways to mathematically model them. They offer efficient techniques to address such problems as: how to determine the minimum number of workstations required or how to identify the disassembly sequence of EOL products on the disassembly line. Several techniques concentrate on balancing the disassembly lines. After defining the disassembly line balancing problem (DLBP) mathematically, search methods (e.g. depthfirst exhaustive search, a greedy algorithm), heuristics (e.g. greedy/hill climbing and greedy/2-optimal) and metaheuristics (e.g. genetic algorithm and ant colony optimisation) are used to solve four case study instances. Besides balancing, other disassembly line-related issues such as line and facility design, sequencing and scheduling, just-in-time, inventory, revenue, unbalanced lines and product planning are also discussed in the book. The book is divided into three parts. Part 1 contains six chapters and provides a background to many of the issues considered in the book. Chapter 1 presents the motivation, scope, objectives, format, notation and outline. Backgrounds in assembly and disassembly lines are provided in Chapters 2 and 3, respectively. Chapter 4 presents the literature review on environmentally conscious manufacturing, product recovery, assembly line balancing, manufacturing systems, disassembly, remanufacturing and various optimisation and search algorithms. Different product representation types used in the disassembly field are discussed in Chapter 5. Chapter 6 introduces the fundamental concepts of computational complexity. Part 2 is devoted to the DLBP. It has 15 chapters. Overview and objectives of DLBP are discussed in Chapter 7 while Chapter 8 provides the mathematical representation of DLBP. In Chapter 9, it is shown that DLBP belongs to the class of NP-complete problems. General information on seven search techniques employed in Part 2 is presented in Chapter 10. Chapter 11 introduces the four case study instances. Chapter 12 investigates the use of analytical methods as well as simulation in the evaluation of combinatorial optimisation searches. The details and numerical results associated with the application of combinatorial optimisation methodologies to the four case study instances are presented in Chapters 13–19 while Chapter 20 compares all these methodologies. An overview of extensions of DLBP, probabilistic considerations and future research directions in DLBP are discussed in Chapter 21. Disassembly line issues other than balancing are considered in Part 3, which has eight chapters. Chapter 22 provides an introduction to Part 3. Consideration of disassembly-related metrics in product design is explained with an example in Chapter 23. Chapter 24 focuses on the facility location and internal layout issues in disassembly. After presenting an overview of scheduling and sequencing techniques, Chapter 25 applies these techniques to the disassembly data. In Chapter 26, an overview of disassembly-related inventory models is presented with an emphasis on