- 著者
- Yuki KINOSHITA Tetsuo YAMADA Surendra M. GUPTA Aya ISHIGAKI Masato INOUE
- 出版者
- 一般社団法人 日本機械学会
- 雑誌
- Journal of Advanced Mechanical Design, Systems, and Manufacturing (ISSN:18813054)
- 巻号頁・発行日
- vol.10, no.3, pp.JAMDSM0052-JAMDSM0052, 2016 (Released:2016-07-01)
- 参考文献数
- 22
- 被引用文献数
- 8
For green supply chains, it is essential to disassemble and recycle end-of-life (EOL) assembled products for material circulation. In order to establish disassembly plants environmentally friendly and economical manner, a disassembly parts selection is often carried out. Each part has a different recycling rate and cost, and all parts have precedence relationships among disassembly tasks. Igarashi et al. (2014) [International Journal of Industrial Engineering and Management Systems, Vol.13, No.1, pp.52-66] proposed a disassembly parts selection method that is carried out in an environmentally friendly and economical manner with non-destructive or destructive disassembly with integer programming with ε constraint. However, calculated efforts are required to achieve optimum solutions for the ε constraint method. On the other hand, goal programming is well known as an effective way to solve multi-criteria decision-making problems. This study proposes a bi-objective disassembly parts selection with recycling rate and cost using goal programming, and analyzes multiple types of EOL assembled products and disassembly parts selection. First, an environmentally friendly and economical disassembly parts selection is addressed using a 3D-CAD and Recyclability Evaluation Method (REM) developed by Hitachi Ltd. Next, the environmentally friendly and economical disassembly parts selection is formulated with goal programming. Finally, a case study is quantitatively discussed by comparing different types of assembled products and goal programming parameters. It is demonstrated that the proposal method by goal programming in this study finds the same solutions with the lower number of numerical experiments as that with the ε constraint method.
- 著者
- Surendra M. GUPTA Prasit IMTANAVANICH
- 出版者
- バイオメディカル・ファジィ・システム学会
- 雑誌
- International Journal of Biomedical Soft Computing and Human Sciences: the official journal of the Biomedical Fuzzy Systems Association (ISSN:21852421)
- 巻号頁・発行日
- vol.15, no.1, pp.71-76, 2010 (Released:2017-09-04)
When a product reaches its end-of-life (EOL), it can be reused, remanufactured, recycled or disposed of. Often, in most of these processes, a certain level of disassembly may be necessary to separate components and materials. Therefore, optimal disassembly sequences are important to increase the efficiency of the disassembly. Since the complexity of the disassembly sequencing problem dramatically increases with the increase in the number of products and component types, we propose an evolutionary computational approach to solve it. Specifically, we use Genetic Algorithm (GA) to solve the problem. A numerical example is considered to illustrate the use of this methodology.
- 著者
- Ammar Y. ALQAHTANI Surendra M. GUPTA Kenichi NAKASHIMA
- 出版者
- ISCM Forum
- 雑誌
- Innovation and Supply Chain Management (ISSN:21870969)
- 巻号頁・発行日
- vol.8, no.4, pp.140-149, 2014-12-28 (Released:2015-03-15)
- 参考文献数
- 39
- 被引用文献数
- 1
In product recovery the disassembly process has an important role since it allows for separation and retrieval of desired parts and materials. End-of-life (EOL) products with missing and/or nonfunctional components increase the uncertainty associated with disassembly yield. Sensor-embedded products (SEPs) eliminate a majority of uncertainties involved in EOL management by providing life-cycle information of products. This information includes the content of each product and component conditions, and enables the estimation of remaining useful life of the components. Once the data on the products are captured, it is possible to make optimal EOL decisions without any preliminary disassembly or inspection operations. This paper presents an Advanced Remanufacture-To-Order, Disassembly-To-Order and Refurbishment-To-Order (ARTODTORTO) model with disassembly precedence relationships among components of an air conditioner (AC). It also inspects and analyzes the impact of using smart sensors in End-of-Life products (EOLPs) on system performance. Various experimental design studies are conducted based on orthogonal arrays (OAs). The customers' demands may be satisfied either by purchasing new components, reassembling components from the returned used products, refurbishing products, or remanufacturing used products based on customers' needs. Discrete event simulation models are used to calculate various performance measures under different experimental conditions.