Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10585
Title: Application of knowledge-based artificial immune system (KBAIS) for computer aided process planning in CIM context
Authors: Prakash, A
Chan, FTS 
Deshmukh, SG
Keywords: Artificial immune system
CAPP
Flexible manufacturing system
KBAIS
Issue Date: 2012
Publisher: Taylor & Francis
Source: International journal of production research, 2012, v. 50, no. 18, p. 4937-4954 How to cite?
Journal: International journal of production research 
Abstract: In the present era, several manufacturing philosophies like lean manufacturing, total quality management (TQM), etc., have the goal of providing a quality product at reduced cost. In this research paper the process planning problem of a CIM system has been discussed where minimisation of cost of the finished product is considered as the main objective. For determining the cost of the finished product, scrap cost, forgotten by most of the previous researchers, has been considered along with other costs like raw material cost, processing cost, etc. In the present environment of concurrent engineering, optimisation of process planning is an NPhard problem. To solve this complex problem a noble search algorithm, known as knowledge-based artificial immune system (KBAIS) has been proposed. The nobility of the proposed algorithm is that the inherent capability of AIS has been gleaned and incorporated with the property of the knowledge base. In this problem, the power of knowledge has been used for three stages in the algorithm: initialisation, selection and hyper-mutation. To demonstrate the efficacy of the proposed KBAIS, a bench mark problem has been considered. Intensive computational experiments have also been performed on randomly generated datasets to reveal the supremacy of the proposed algorithm over other existing heuristics.
URI: http://hdl.handle.net/10397/10585
ISSN: 0020-7543
EISSN: 1366-588X
DOI: 10.1080/00207543.2011.616234
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