Applications of Swarm Intelligence in Remanufacturing

Applications of Swarm Intelligence in Remanufacturing

Bo Xing (Department of Mechanical and Aeronautical Engineering, University of Pretoria, South Africa) and Wen-Jing Gao (Mei Yuan Mould Design and Manufacturing Co., China)
DOI: 10.4018/978-1-4666-5888-2.ch007
OnDemand PDF Download:
$37.50

Chapter Preview

Top

2. Background

2.1. Remanufacturing

The remanufacturing is an end-of-life (EoL) strategy that reduces the use of raw materials and saves energy while preserving the value added during the design and manufacturing processes (Zwolinski, Lopez-Ontiveros, & Brissaud, 2006). A well-structured remanufacturing system should guarantee high efficiency, high functionality and a high customer orientation concerning the disposal of used household appliances. It should entail environmentally friendly solutions concerning energy consumption, emission of pollutants and noise as well as secure transportation.

The remanufacturable products can be sold at the secondary markets at a lower price, compared to the price of new products, e.g., tires (Ferrer, 1997), photocopiers (Ayres, Ferrer, & Leynseele, 1997), cell phones (Nikolaidis, 2009) or they can be used to satisfy demand of the same markets, e.g., single use cameras (Toktay, Wein, & Zenios, 2000), pallets and containers (Golany, Yang, & Yu, 2001; Kroon & Vrijens, 1995), car engines (Smith & Keoleian, 2004) and computer parts (Fleischmann, Nunen, & Gräve, 2003).

Key Terms in this Chapter

Particle Swarm Optimization (PSO): An evolutionary computation technique and usually used for optimization of continuous non-linear functions. The core procedure of PSO is to mimic the social behavior of bird flocking or fish schooling with the aim of solving optimization problems.

End-of-Life (EoL): The end of the product's lifetime. In the light of our chapter, this term is regarded as one of the recovery strategies/solutions which increase the concerns about EoL products treatments.

Ant Colony Optimization (ACO): One of the successful research directions in the SI domain. The main idea is that the self-organizing principles which allow a colony of artificial ants that cooperate to find good solutions.

Remanufacturing: Remanufacturing is a process involving three stages, i.e., used products retrieval, used products reproduction, and remanufactured products redistribution.

Used Product Retrieval: The process that companies collect them from product holders. It is one of the key concerns of the companies involved in product recovery due to it triggers the other activities of the recovery system.

Vehicle Routing Problem (VRP): One of the famous optimization problems. In VRP, the vehicle can either deliver or pick up goods from customers. The objective of VRP is to design a set of vehicle routes that minimizes the total traveled distances.

Bees-Inspired Algorithms: Belong to the class of SI. Based on the intelligent behaviors of bee swarm such as mating-flight, foraging, dance, nest site selection, navigation and task selection, several approaches haven been proposed and applied to deal with hard combinatorial optimization problems. The main idea is that all bee-inspired algorithms are characterized by autonomy, distributed functioning and self-organizing.

Swarm Intelligence (SI): Built on the core principles found in various natural systems which is composed of many agents who exploits local communication forms and highly distributed control. Informally, SI is a kind of computational metaphor inspired by different swarm examples such as ants, wasps, honey bees, fish, birds, sheep, wolves, and particles.

Reverse Logistic Network: A series of operations required to acquire used products from end users and reprocess them to the recovery facilities or dispose of them.

Complete Chapter List

Search this Book:
Reset