PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Computational intelligence in computer aided process planning - a review

Autorzy
Identyfikatory
Warianty tytułu
PL
Inteligencja komputerowa w komputerowo wspomaganym projektowaniu procesów
Języki publikacji
EN
Abstrakty
EN
This paper first provides a general introduction to Computer Aided Process Planning (CAPP). In second section, a brief review of Computational Intelligence (CI) applications in machining process planning and related methods and problems will be presented. The overall applications can be classified as knowledge representation, features extraction, part classification for group technology, machining volume decomposition, tool path generation, machining condition optimization, operation sequencing, machine, setup and tool selection, modeling the EDM process, and others. It presents current state and perspectives on computational intelligence in CAPP.
PL
W pracy omówiono obszary zastosowania metod sztucznej inteligencji w komputerowo wspomaganym projektowaniu procesów wytwarzania w budowie maszyn. Podjęto próbę klasyfikacji tych obszarów. Przedstawiono najważniejsze zdaniem autora osiągnięcia inteligencji komputerowej w budowie efektywnych systemów CAPP. Określono tendencje i zadania w dalszym rozwoju systemów CAPP i rolę inteligencji komputerowej, jako narzędzia inżynierii wiedzy, w ich realizacji.
Rocznik
Strony
77--92
Opis fizyczny
Bibliogr. 63 poz., rys., tabl.
Twórcy
autor
  • University of Bielsko-Biała, Department of Manufacturing Technology and Automation, 43-309 Bielsko-Biała, ul. Willowa 2, r_stryczek@poczta.onet.pl
Bibliografia
  • [1] G. SOHLENIUS, T. KJELLBERG: Artificial intelligence and its potential USE in the manufacturing system. Annals of the CIRP, 35(1986)2, 425-432.
  • [2] D. POOLE, A. MACKWORTH, R. GOEBEL: Computational intelligence. Oxford University Press, New York 1998.
  • [3] L. ALTING, H. ZHANG: Computer aided process planning: the state-of-the-art survey. Int. J. of Production Research, 27(1989)4, 553-585.
  • [4] S.H. HUANG, H.C. ZHANG: Neural-hybrid approach for intelligent manufacturing: A Survey. Computer and Industry, 26(1995), 107-126.
  • [5] D. KIRITSIS: A review of knowledge-based expert systems for process planning. Methods and problems. J. of Adv. Manufacturing Technology, 10(1995), 240-261.
  • [6] H.C. LEUNG: Annotated Bibliography on Computer-Aided Process Planning. J. of Adv. Manufacturing Technology, 12(1996), 309-329.
  • [7] R. KNOSALA: Zastosowanie metod sztucznej inteligencji w inżynierii produkcji. WNT, Warszawa 2002.
  • [8] L. WANG, H.Y. FENG, N. CAI: Architecture design for distributed process planning. J. of Manufacturing Systems, 22(2003).
  • [9] S. KOLLI: Classification of research and applications in feature modeling and computer aided process planning. Thesis, Ohio University 2004.
  • [10] N. AHMAD, A.F.M.A. HAQUE, A.A. HASIN: Current trend in computer aided process planning. int. conf. the institution of engineers, Bangladesh, 2001, 81-92.
  • [11] L. LI, J.Y.H. FUH, Y.F. ZHANG, A.Y.C. NEE.: Application of genetic algorithm to computer-aided process planning in distributed manufacturing environments. Robotics and Computer-Integrated Manufacturing, 21(2005), 568-578.
  • [12] F. CAY, C. CHASSAPIS: An IT view on perspectives of computer aided process planning research. Computers in Industry, 34(1997) 307-337.
  • [13] S. PRABHAKAR: An experience: on the use of neural nets in form feature recognition. M. S. Thesis, Arizona State University, 1990.
  • [14] M. MARQUEZ, R. GILL, A. WHITE: Application of neural networks in feature recognition of moulded reinforced plastic parts. Concurrent Engineering: Research & Applications, 7(1999)2, 115-122.
  • [15] N. ÖZTÜRK, F. ÖZTÜRK: Neural network based non-standard feature recognition to integrate CAD and CAM. Computers in Industry, 45(2001), 23-135.
  • [16] Y.H. CHEN, H.M. LEE: A Neural network system feature recognition for two-dimensional. J. of Computer Integrated Manufacturing, 11(1998)2, 111-117.
  • [17] R. STRYCZEK: Raster graphics in feature recognition. Advances in Manufacturing Science and Technology, 29(2005)3, 21-33.
  • [18] R. STRYCZEK: Ekstrakcja elementarnych form obrabianych z wykorzystaniem automatów komórkowych. VI Szkoła Komputerowego Wspomagania Projekto-wania, Wytwarzania i Eksploatacji, Jurata 2002.
  • [19] Y.B. MOON, S.C. CHI: Generalized part family formation using neural network techniques. J. of Manufacturing Systems, 11(1992)3, 149-159.
  • [20] M.E. SSEMAKULA, D.S. NAU, R.M. RANGACHAR, Q. YANG: Optimal process sequencing in CAPP systems. AUTOFACT ’88, University of Maryland, 1988.
  • [21] G.M. KNAPP, H.P. WANG: Acquiring, storing and utilizing process planning knowledge using neural networks. J. of Intelligent Manufacturing, 5(1992)3, 333-344.
  • [22] N. AHMAD, A. HAQUE: Artificial neural network based process selection for cylindrical surface machining. Int. Conference on Manufacturing, ICM’2002, Dhaka 2002, 321-326.
  • [23] S. DEB, K. GHOSH, S. PAUL: A Neural network based methodology for machining operations selection in computer-aided process planning for rotationally symmetrical parts. J. of Intelligent Manufacturing, 17(2006), 557-569.
  • [24] X.G. MING, K.L. MAK: Intelligent setup planning in manufacturing by neural networks based approach. J. of Intelligent Manufacturing, 11(2000), 311-331.
  • [25] X.H. SHAN, A.Y.C. NEE, N. POO: Integrated application of expert systems and neural networks for machining operation sequencing. Neural Networks in Manufacturing and Robotics, ASME, 57(1992), 117-126.
  • [26] W.B. ZHANG, L.Z. HUA, Z.G. YU: Optimization of process route by genetic algorithms. Robotics and Computer-Integrated Manufacturing, 22(2006), 80-188.
  • [27] D. YIP_HOI, D. DUTTA: A Genetic algorithm application for sequencing operations in process planning for parallel machining. IIE Transactions, 28(1996), 55-68.
  • [28] D.H. LEE, D. KIRITSIS, P. XIROUCHAKIS: Operation sequencing in nonlinear planning: local search heuristic. Studies in Informatics and Control Journal, 11(2002)1.
  • [29] V. PANDEY, M.K. TIWARI, S. KUMAR: An Interactive approach to solve the operation sequencing problem using simulated annealing. J. of Advanced Manufacturing Technology, 29(2006), 1212-1231.
  • [30] T. DERELI, H.I. FILITZ: Optimization of process planning function by genetic Algorithm. Computers and Industrial Engineering, 36(1999), 281-308.
  • [31] S.G. KRISHNA, K.M. RAO: Optimization of operations sequence in capp using an ant colony algorithm. J. Adv. Manufacturing Technology, 9(2006), 159-164.
  • [32] J. SZADKOWSKI: Artificial intelligence approach to structural and parametrical optimization of multi-tool machining processes. Gepgyartastechnologia, 9(1992), 359-366.
  • [33] D.N. SORMAZ, B. KHOSHNEVIS: Intelligent process planning implemented as an integrated module of CIM. ASME Design Engineering Technical Conferences, Sacramento 1997.
  • [34] D. SORMAZ: Space search algorithm for incremental operation sequencing in computer aided process planning. 35th International Conference on Computers and Industrial Engineering, Istanbul 2005.
  • [35] S. H. HUANG, N. XU: Automatic set-up planning for metal cutting: an integrated methodology. J. of Production Research, 41(2003)18, 4339-4356.
  • [36] S. K. ONG, A. Y. C. NEE: Application of fuzzy set theory to set-up planning. Annals of the CIRP, 43(1994)1, 137-144.
  • [37] R. STRYCZEK: Wykorzystanie niektórych idei sztucznej inteligencji w projektowaniu operacji na frezarsko-wytaczarskie centra obróbkowe. Thesis, ATH, Bielsko-Biała 1990.
  • [38] B. AREZOO, K. RIDGWAY, A.M.A. AL-AHMARI: Selection of cutting tools and conditions of machining operations using an expert system. Computers in Industry, 42(2000), 43-58.
  • [39] J. JOO, Y.S. CHOI, S. PARK, H. CHO: Adaptive and dynamic process planning using neural network. EDA Conference, 1999, 74-81.
  • [40] J. BALIC, M. KOROSEC: Intelligent tool path generation for milling of free surface using neural networks. Int. J. of Machine Tools & Manufacture, 42(2002), 1171-1179.
  • [41] M. RAD-TOLOUEI, I.M. BIDHENDI: On the optimization of machining parameters for milling operations. J. of Machine Tools and Manufacture, 37(1997)1, 1-16.
  • [42] S.V. WONG, A.M.S. HAMOUDA: Machinability data representation with artificial neural network. J. of Materials Processing Technology, 138(2003), 538-544.
  • [43] Z. KHAN, B. PRASAD, T. SINGH: Machining condition optimization by genetic algorithms and simulated annealing. Computers& Operation Research, 24(1997)7, 647-657.
  • [44] F. CUS, J. BALIC: Optimization of cutting process by GA approach. Robotics and Computer Integrated Manufacturing, 19(2003), 113-121.
  • [45] M. R. ALAM, K. S. LEE, M. RAHMAN, Y. F. ZHANG: Process planning optimization for the manufacture of injection moulds using genetic algorithm. Int. J. of Computer Integrated Manufacturing, 16(2003)3, 181-191.
  • [46] L. JOO, G.R. YI, H. CHO, Y.S. CHOI: Dynamic Planning model for determining cutting parameters using neural network in feature-based process planning. J. of Intelligent Manufacturing, 12(2001), 13-29.
  • [47] K. HASHMI, M.A. EL BARADIE, M. RYAN: Fuzzy logic based intelligent selection of machining parameters. Computers Industrial Engineering, 35(2008), 571-574.
  • [48] F. KOLAHAN, M. LIANG: Optimization of hole-making operations: a Tabu-Search Approach. Int. J. of Machine Tools & Manufacture, 40(2000), 1735-1753.
  • [49] S. CAVALIERI, P. MACCARONE, R. PINTO: Parametric vs neural network models for the estimation of production costs. Int. J. of Production Economics, 91(2004), 165-177.
  • [50] E. SHEHAB, H. ABDALLA: An intelligent knowledge-based system for product cost modeling. Int. J. of Advanced Manufacturing Technology, 19(2002), 49-65.
  • [51] K. WANG, H.L. GELGELE, Y. WANG, Q. YUAN, M. FANG: A Hybrid intelligent method for modeling the EDM process. Int. J. of Machine Tools & Manufacture, 43(2003), 995-999.
  • [52] D. FONSECA, D. NAVARESSE: Artificial neural network for job shop simulation. Advanced Engineering Informatics, 16(2002), 241-246.
  • [53] H. LEE, S.S. KIM: Integration of process planning and scheduling using simulation based genetic algorithms. J. of Advanced Manufacturing Technology, 18(2001), 586-590.
  • [54] G.J. PALMER: A Simulated annealing approach to integrated production scheduling. J. of Intelligent Manufacturing, 7(1996), 163-176.
  • [55] W. D. LI, C. A. McMAHON: A Simulated annealing-based optimization approach for integrated process planning and scheduling. Int. J. of Computer Integrated Manufacturing, 20(2007)1, 80-95.
  • [56] P. T. CHANG, C. H. CHANG: An integrated artificial intelligent computer-aided process planning system. Int. J. of Computer Integrated Manufacturing, 13(2000)6, 483-497.
  • [57] H. C. ZHANG, S. H. MALLUR: Integration of process planning and scheduling functions. Control and Dynamic Systems, 61(1994), 155-195.
  • [58] H.C. ZHANG, S.H. HUANG: A fuzzy approach to process plan selection. Int. J. of Production Research, 32(1994)6, 1265-1275.
  • [59] F. GUERRERO, S. LOZANO, K. SMITH, D. CANCA, T. KWOK: Manufacturing cell formation using a new self-organization neural network. Computers & Industrial Engineering, 42(2002), 377-382.
  • [60] V. VENUGOPAL, T. T. NURENDRAM: A Genetic algorithm approach to the machine component grouping problem with multiple objective. Computers and Industrial Engineering, 22(1992)4, 469-480.
  • [61] S.M. AMAITIK, S.E. KILIÇ: An intelligent process planning system for prismatic parts using step features. J. of Advanced Manufacturing Technology, 31(2007), 978-993.
  • [62] I. ROJEK-MIKOŁAJCZAK, Z. WEISS: Sztuczna inteligencja w procesach technologicznych. CADCAM FORUM, 10(2001), 40-46.
  • [63] I. ROJEK-MIKOŁAJCZAK: Metody eksploracji danych w inteligentnej bazie danych wspomagającej projektowanie procesów technologicznych. Pro Dialog, Computer Programming and Applications, 19(2005), 1-9.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BOS4-0019-0029
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.