Studies in Informatics and Control – ICI Bucharest
A Fuzzy Analysis Approach to Part Family Formation in Cellular Manufacturing Systems
V. DHANALAKSHMI
Department of Mechanical Engineering, Thiagarajar College of Engineering,
Madurai, 625015, India
S. ARUNACHALAM
School of Computing and Technology, Manufacturing Engineering,
University of East London, Longbridge Road, Dagenham, Essex RM8 2AS, UK
K. SANKARANARAYANASAMY
Department of Mechanical Engineering, Thiagarajar College of Engineering,
Madurai, 625015, India
T. PAGE
Department of Design and Technology, Loughborough University, Loughborough, UK
Abstract: Part family formation using fuzzy cluster analysis in Group Technology (GT) and feature recognition for tool access direction using relationship matrix in Computer Aided Process Planning (CAPP) have been presented in this paper. In the process of identifying part-families and machine groups, Fuzzy Cluster Analysis to form machine-part fuzzy relative matrix which converted into a zero-one conventional matrix. A new similarity coefficient, which involves all the entries of the machine-part fuzzy relative matrix resulting in a more realistic part family formation was suggested. The feature extraction system presented in this paper is designed to extract features from a STEP file in Boundary Representation (B-Rep) and Attributed Adjacency matrix. The system is able to automatically extract alternate tool axis directions (TADs). There is a potential applications in set-up change cost optimisation and fixture selection.
Keywords: CAD/CAM, GT, CAPP, part family formation, feature recognition.
R. Dhanlakshmi M.E, currently pursuing her PhD in Computer Science from Mother Teresa women’s University, Kodaikannal, Tamilnadu. Her research interests are in the areas of intelligent tutoring system, networking, internet protocols, data mining and cryptography. She received her Bachelor’s degree in Electrical and Electronics Engineering from Madras University, Master’s degree in Computer Science and Engineering from Madurai Kamaraj University. She has published 2 technical papers in the referred International journal and 8 papers in national and international conferences.
Subramaniam Arunachalam is a senior lecturer in Manufacturing Systems Engineering in university of East London, UK. He has many years of experience in teaching and developing course materials in manufacturing and operations management disciplines. His fields of research interest include lean concepts, manufacturing systems engineering, strategy and management, quality management, supply chain management, manufacturing simulation, production management, total quality management and project management. Dr. Arunachalam is a visiting professor at several universities abroad and has presented many invited papers in international conferences. He has published more than 160 articles in refereed journals and conferences. He has carried out several consultancy projects in productivity improvement using simulation techniques, designing quality management systems, implementation of lean systems, process reengineering, market penetration analysis, introduction of inventory control and MRP systems and developing training material for leans systems, six sigma and productivity improvement. Dr. Arunachalam is also actively involved in many international collaborative research projects.
Sankaranarayanasamy K. is currently Professor of Mechanical Engineering at NIT Trichy. He obtained his PhD from IIT Madras. His areas of interest are Gears, Tolerance analysis and Laser Welding. He has published over 30 research papers in international journals and 50 research papers in international conferences.
Tom Page, is a lecturer in Electronic Product Design in the department of Design and Technology at Loughborough University UK. He is an external examiner on Engineering and Manufacturing programmes at Sheffield Halllam University. Dr Page is a visiting scholar at Iceland University and the University of Lapland in Finland and has been an external examiner on undergraduate fields in Product Design and Manufacturing Engineering at the University of East London.
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CITE THIS PAPER AS:
V. DHANALAKSHMI, S. ARUNACHALAM, K. SANKARANARAYANASAMY, T. PAGE, A Fuzzy Analysis Approach to Part Family Formation in Cellular Manufacturing Systems, Studies in Informatics and Control, ISSN 1220-1766, vol. 17 (4), pp. 433-440, 2008.
1. Introduction
Researches have been done on part family formation based on the usage of binary classification logic (zero-one data) (Chandrasekaran and Rajagopalan, 1986); (Chandrasekaran and Rajagopalan, 1987); and a modified form of grouping heuristic in GT (Islam and Sarker, 2000). A new formula for similarity coefficient and new grouping heuristic to suit the proposed fuzzy method are suggested in this paper. The other researches have been done on feature recognition and process planning in CAPP in defining the tool access directions using a hierarchical structure (Gindy, 1989), generating the tool approach directions for grouping machines for set-ups (Ozturk, Kaya, Alanks, and Sevinc, 1996), determining the cutter sweep directions using a floor-based algorithm (Han and Requicha, 1998); (Han, Han, Lee and Juneho, 2001) introducing the concept of attributed adjacency graph (AAG) for the recognition of machining features from a B-rep of a solid model (Han, Kang, and Choi, 2001). A feature recognition system in Java language to automatically capture the candidate TADs is developed and presented in this paper.
4. Conclusion
4.1 Part family formation
A realistic approach to part family formation in cellular manufacturing systems using a new fuzzy approach in which the fuzzy relative values are used throughout the methodology instead of using them only in the first step is provided, which makes it possible to get a more realistic solution compared to earlier methods. A new formula for similarity coefficient and new grouping heuristic are used. Numerical example shows improvement of the grouping efficiency obtained for the proposed methodology is achieved.
4.2 Feature recognition for tool access direction
A feature recognition system that is developed to automatically capture the candidate TADs of a feature for a prismatic part. The system is developed in Java language to make it portable. Moreover, the system uses standard technologies like STEP, which is suitable for concurrent processes to enable interoperability. This work can be extended to integrate the feature recognition process with cost optimisation so that manufacturability is guaranteed during the extraction process itself.
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