A Genetic Algorithm for Disassembly Process Planning

Copyright 2001 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.When a product reaches it’s end-of-life, there are several options available for processing it including reuse, remanufacturing, recycling, and disposing (the least desirable option). In almost all cases, a certain level of disassembly may be necessary. Thus, finding an optimal (or near optimal) disassembly sequence is crucial to increasing the efficiency of the process. Disassembly operations are labor intensive, can be costly, have unique characteristics and cannot be considered as reverse of assembly operations. Since the complexity of determining the best disassembly sequence increases with the increase in the number of parts of the product, it is extremely crucial that an efficient methodology for disassembly process planning be developed. In this paper, we present a genetic algorithm for disassembly process planning. A case example is considered to demonstrate the functionality of the algorithm.http://dx.doi.org/10.1117/12.45526

Assembly and Disassembly Planning by using Fuzzy Logic & Genetic Algorithms

The authors propose the implementation of hybrid Fuzzy Logic-Genetic Algorithm (FL-GA) methodology to plan the automatic assembly and disassembly sequence of products. The GA-Fuzzy Logic approach is implemented onto two levels. The first level of hybridization consists of the development of a Fuzzy controller for the parameters of an assembly or disassembly planner based on GAs. This controller acts on mutation probability and crossover rate in order to adapt their values dynamically while the algorithm runs. The second level consists of the identification of theoptimal assembly or disassembly sequence by a Fuzzy function, in order to obtain a closer control of the technological knowledge of the assembly/disassembly process. Two case studies were analyzed in order to test the efficiency of the Fuzzy-GA methodologies

A computer-based product classification and component detection for demanufacturing processes

This is an Author's Accepted Manuscript of an article published in International Journal of Computer Integrated Manufacturing, 24(10), 900-914, 2011 [copyright Taylor & Francis], available online at: http://www.tandfonline.com/10.1080/0951192X.2011.579169.The aim of this paper is to propose a novel computer-based product classification, component detection and tracking for demanufacturing and disassembly process. This is achieved by introducing a series of automated and sequential product scanning, component identification, image analysis and sorting – leading to the development of a bill of material (BOM). The produced BOM can then be associated with the relevant disassembly/demanufacture proviso. The proposed integrated image sorting and product classification (ISPC) approach can be considered as a step forward in automation of demanufacturing activities. The ISPC model proposed in this paper utilises and builds on the state-of-the-art technology and current body of research in computer-integrated demanufacturing and remanufacturing (CIDR). An appraisal of the latest research material and the factors that inhibit CIDR methods inpractice are presented. A novel solution for the integration of imaging and material identification techniques toovercome some of the existing shortcomings of automated recycling processes is proposed in this paper. The proposed product scanning and component detection ISPC software consists of four distinct models: the repertory database, the search engine, the product-attributes updater and the image sorting and classification algorithm. The software framework that integrates the four components is presented in this paper. Finally, an overall assessment of applying ISPC at various stages of CIDR processes concludes the article.University of Ibadan MacArthur Foundation Gran

Automatic generation of robot and manual assembly plans using octrees

This paper aims to investigate automatic assembly planning for robot and manual assembly. The octree decomposition technique is applied to approximate CAD models with an octree representation which are then used to generate robot and manual assembly plans. An assembly planning system able to generate assembly plans was developed to build these prototype models. Octree decomposition is an effective assembly planning tool. Assembly plans can automatically be generated for robot and manual assembly using octree models. Research limitations/implications - One disadvantage of the octree decomposition technique is that it approximates a part model with cubes instead of using the actual model. This limits its use and applications when complex assemblies must be planned, but in the context of prototyping can allow a rough component to be formed which can later be finished by hand. Assembly plans can be generated using octree decomposition, however, new algorithms must be developed to overcome its limitations

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Disassembly line scheduling with genetic algorithms.

International audienceDisassembly is part of the demanufacturing and it is meant to obtain components and materials from end-of-line products. An essential performance objective of a disassembly process is the benefits it brings, that is the revenue brought by the retrieved parts and material, diminished by the cost of their retrieval operations. A decision must be taken to balance an automatic disassembly line. A well balanced line will decrease the cost of disassembly operations. An evolutionary (genetic) algorithm is used to deal with the multi-criteria optimization problem of the disassembly scheduling

Disassembly sequence planning validated thru augmented reality for a speed reducer

The lifecycle of a product is getting shorter in today’s market realities. Latest developments in the industry are heading towards achieving products that are easy to recycle, by developing further technological advances in raw materials ought to include input from End of Life (EOL) products so a reduction of natural harm could be achieved, hence reducing the overall production environmental footprint. Therefore, the approach taken as a design for environment, a key request nowadays in order to develop products that would ease the reverse manufacturing process leading to a more efficient element recycling for later use as spare parts or remanufacturing. The methodology proposed compares three probable disassembly sequences following a comparison of literature-found procedures between genetic algorithms and as a “state space search” problem, followed by a hybrid approach developed by the authors. Time and evaluation of these procedures reached to the best performing sequence. A subsequent augmented reality disassembly simulation was performed with the top-scored operation sequence with which the user is better able to familiarize himself with the assembly than a traditional paper manual, therefore enlightening the feasibility of the top performing sequence in the real world

Development of the evaluation system for automobile remanufacturing

By 2015, the EU directives required the automobile manufacturers to produce a vehicle that contains reusable and / or recoverable parts at least 95% of total weight. In the developed countries, the legislative issue the take – back policy which requires the manufacturers to consider the end – of – life (EOL) of their products at early design stage. The goal of this paper is to propose a framework of development methodology that focuses on integrated design for remanufacturing evaluation system. This system supports the automobile product design and development at the early design phase. The proposed method is divided into two phases. The first phase aims to identify the suitable EOL process. The second phase aims to verify the most economical EOL process. The proposed method incorporates the Case base Reasoning [CBR] into the remanufacturing techniques. It is expected that the proposed method can provide the EOL with decision support during designing the automobile parts at the early design stage