| Title |
Cellular demanufacturing layout in a rail industry: End-of- life components reusability |
| ID_Doc |
9486 |
| Authors |
Phuluwa, HS; Mpofu, K; Trimble, JA |
| Title |
Cellular demanufacturing layout in a rail industry: End-of- life components reusability |
| Year |
2019 |
| Published |
|
| DOI |
10.1016/j.promfg.2020.01.040 |
| Abstract |
Rail manufacturing industry across the globe has been growing exponential since the inception of rail into transportation systems. Freight and passenger trains manufacturing contributes a greater proportion to the rail industry economic impact. The passenger trains are a mode of transport for both poor and rich people in Africa. Due to lack of appropriate demanufacturing plant layouts suited for recovering end-of-life (Eol) components, most of components are often neglected to the landfills. Most African countries have been importing trains for many years around the globe. Some of these trains have reached or are reaching Eol, which makes it difficult for countries to develop or have appropriate demanufacturing plant layouts or technologies for recovering Eol components. The study reviewed various literature on train life cycle management system and cellular demanufacturing layout configurations applied across various industries in the globe. The study further looked into different hybrid layout modalities and a simulation was used to determine efficient models, which can best suit an African context. The study used a case study of Southern Africa to assess the readiness of countries to gain benefits of circular economy through efficient layouts. The study proposes a sustainable cellular layout conceptual model that will accommodate train components variation. (C) 2019 The Authors. Published by Elsevier B.V. |
| Author Keywords |
Demanufacturing; cellular manufacturing system; End-of-life components |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000889468900039 |
| WoS Category |
Computer Science, Artificial Intelligence; Engineering, Manufacturing |
| Research Area |
Computer Science; Engineering |
| PDF |
https://doi.org/10.1016/j.promfg.2020.01.040
|