A Heuristic Procedure For Production Planning Of Modern Manufacturing Systems

The purpose of this paper is to present a new heuristic algorithm based on a feasible enumeration method, developed to solve the machine loading and product-mix decision problems for manufacturing systems based on group technology. It provides an efficient tool for machine load and product-mix analysis to optimally select parts to be manufactured in a limited amount of time available in a given production facility, by applying the group technology concept. A computational algorithm is developed, a sample numerical problem included, and computational results presented. It is shown that the algorithm herein proposed is very efficient from the computational view point. The heuristics imbedded in the feasible enumeration procedure is repreented by a priority rule which has been found to be independent of problem data and general for the class of problem analysed. © 1991.204475485Bazaraa, Shetty, (1979) Nonlinear Programming: Theory and Algorithms, , Wiley, New YorkBertsekas, Multiplier methods: a survey (1976) Automatica, 12, pp. 133-145. , Pergamon Press, OxfordCohon, (1978) Multiobjective Programming and Planning, , Academic Press, New YorkFernandes, Análise e Implementação de Métodos de Geração de Programas de Produçã o para Sistemas Modernos de Manufatura (1985) M. S. Thesis, , Universidade de Campinas, SP, Brazil, FEC 106/85Fernandes, Gomide, Planejamento e Sequenciamen to da Produção em Sistemas Modernos de Manufatura (1986) 6th Congresso Brasileiro de Automática, 2, pp. 686-691Giglio, Wagner, Approximate Solutions to the Three-Machine Scheduling Problem (1964) Operations Research, 12, pp. 305-324Hassman, Hess, A linear programming approach to production and employing scheduling (1980) Magmt Technol., 1Hitomi, Ham, Machine loading and production-mix analysis for group technology (1978) ASME—J. Engng Ind, 100, pp. 300-374Hitomi, (1979) Manufacturing Systems Engineering, , Taylor and Francis, LondonHitomi, Ham, Production-mix and machine loading analysis of multistage production systems for group technology (1982) ASME—J. Engng Ind, 104, pp. 363-368Manne, On the Job-Shop Scheduling Problem (1960) Operations Research, 8, pp. 219-223Stecke, Formulation and solution of nonlinear integer production planning problems for flexible manufacturing systems (1983) Magmt Sci., 29, pp. 273-28

Involving Objective And Subjective Aspects In Multistage Decision Making And Control Under Fuzziness: Dynamic Programming And Neural Networks

We extend the basic Bellman and Zadeh's [Manage. Sci., 17, 141-164 (1970)] model of multistage decision making (control) in a fuzzy environment to include both objective and subjective evaluations of how well fuzzy constraints on decisions (controls) applied and fuzzy goals on states (outputs) attained are satisfied. We discuss the solution by an extended fuzzy dynamic programming model. We present Francelin and Gomide's [Proc. of Second IEEE International Conference on Fuzzy Systems- FUZZ-IEEE'93, San Francisco, CA, Vol. 1, 1993, pp. 655-660] [cf. also Francelin, Gomide, and Kacprzyk [Proc. of Sixth IFSA World Congress, Saõ Paolo, Brazil, Vol. II, 1995, pp. 221-224] and Kacprzyk, Romero, and Gomide [Neuro-Fuzzy Techniques for Information Processing, Physica-Verlag (Springer-Verlag), Heidelberg-New York, forthcoming]] neural network implementing fuzzy dynamic programming, and then show its extension to cover both the objective and subjective evaluations involved in the proposed extension of the basic Bellman and Zadeh's [Manage. Sci., 17, 141-164 (1970)] model. We show its use for solving a socioeconomic regional planning problem proposed in Kacprzyk and Straszak [Applied Systems and Cybernetics, Pergamon, New York, 1982, Vol. 6, pp. 2997-3004; Recent Developments in Fuzzy Sets and Possibility Theory, Pergamon, New York, 1982, pp. 531-541; IEEE Trans. Syst. Man, Cybern., SMC-14, 310-313 (1984)] [cf. Kacprzyk's [Multistage Fuzzy Control, Wiley, Chichester, 1997] book], extending Kacprzyk, Romero, and Gomide [Neuro-Fuzzy Techniques for Information Processing, Physica-Verlag (Springer-Verlag), Heidelberg-New York, forthcoming]. © 1999 John Wiley & Sons, Inc.14179104Bellman, R.E., Zadeh, L.A., (1970) Manage Sci, 17, pp. 141-164Kacprzyk, J., (1997) Multistage Fuzzy Control, , Wiley, ChichesterKacprzyk, J., (1983) Multistage Decision Making under Fuzziness, , Verlag TÜV Rheinland, CologneKacprzyk, J., Straszak, A., (1982) Applied Systems and Cybernetics, 6, pp. 2997-3004. , Lasker, G. E., Ed.Pergamon, New YorkKacprzyk, J., Straszak, A., (1982) Recent Developments in Fuzzy Sets and Possibility Theory, pp. 531-541. , Yager, R. R., Ed.Pergamon, New YorkKacprzyk, J., Straszak, A., (1984) IEEE Trans Syst Man Cybern, SMC-14, pp. 310-313Kacprzyk, J., Esogbue, A.O., (1996) Fuzzy Sets Syst, 81, pp. 31-46Francelin, R.A., Gomide, F.A.C., A neural network for fuzzy decision making problems (1993) Proc. of Second IEEE International Conference on Fuzzy Systems - FUZZ-IEEE'93, pp. 655-660. , San Francisco, CA, Vol. 1Kacprzyk, J., Romero, R.A., Gomide, F.A.C., (1999) Neuro-Fuzzy Techniques for Information Processing, , Kasabov, N. and Kozma, R., Eds.Physica-Verlag (Springer-Verlag), Heidelberg-New YorkFrancelin, R.A., Gomide, F.A.C., Kacprzyk, J., A class of neural networks for dynamic programming (1995) Proc. of Sixth IFSA World Congress, pp. 221-224. , Saõ Paolo, Brazil, Vol. IINijkamp, P., (1986) Handbook of Regional and Urban Economics, , North-Holland, AmsterdamKacprzyk, J., (1978) Contr Cybern, 7, pp. 51-64Kacprzyk, J., (1979) Kybernetes, 8, pp. 139-147Kacprzyk, J., Multistage control of a fuzzy system using a genetic algorithm (1995) Proc. of Int. Joint Conf. of 4th IEEE Int. Conf. on Fuzzy Systems and 2nd Int. Fuzzy Engineering Symp. (FUZZ-IEEE/IFES'95), 2, pp. 1083-1088. , YokohamaKacprzyk, J., Multistage fuzzy control using a genetic algorithm (1995) Proc. of 6th IFSA World Congress, 2, pp. 225-228. , Saõ Paolo, BrazilKacprzyk, J., A modified genetic algorithm for multistage control of a fuzzy system (1995) Proc. of 3rd Eur Congress on Intelligent Techniques and Soft Computing - EUFIT'95, 1, pp. 463-466. , Aachen, German

Knowledge-based Environment For Intelligent Design And Supervision Of Control Systems

Most industrial processes have several particular characteristics, system requirements and performance which may not be obtained by classical control methodologies. In this case advanced control strategies must be considered. In face of different options, testing in simulation environments using software packages is a common practice. In this paper, an environment aimed at integrating different software resources in a consistent and uniform way is proposed. It is based on object-oriented approach implemented into a knowledge based shell. In addition, full potential of knowledge based systems can be used for intelligent decision.32680268

A Knowledge-based System For Disk-drive Diagnostics

A frame-based, backward-chaining knowledge-based system was developed to help the diagnostic process in the manufacture of computer high-end disk drives. The nature of the diagnostic and testing process is presented and the methodology used to develop the knowledge-based system is explained. The development and consultation environments are introduced and the final system is described. The improvements and results obtained with the utilization of this knowledge-based system in a factory environment are also included. © 1990.34282287Harker, Brede, Pattison, Santana, Taft, A Quarter Century of Disk File Innovation (1981) IBM Journal of Research and Development, 25 (5), pp. 677-689(1987) “Introduction to IBM 3380 Direct Access Storage Devices Family”, , IBM, International Business Machines CorporationWinston, (1984) Artificial Intelligence, , Addison Wesley Publishing CompanyNilsson, (1980) Principles of Artificial Intelligence, , Tioga Publishing CompanyArruda, A Knowledge Based Supervisor for Process Modeling (1988) Master Thesis, , 2nd ed., University of Campinas, BrazilWaterman, (1986) A Guide to Expert Systems, , Addison Wesley Publishing Company(1987) Personal Consultant Scheme, A Simple and Modern LISP—Tutorial, , Texas InstrumentsFavilla, Jr., “An Expert System for Disk Drives Testing Diagnostics” (1988) Master Thesis, , (in Portuguese), 2nd ed., State University of Campinas, Brazi

Object-oriented Environment For Control Systems In Oil Industry

Most industrial processes have several particular characteristics, system requirements and performance which may not be obtained by classical control methodologies. In this case advanced control strategies must be considered. In face of different options, testing in simulation environments using software packages is a common practice. In this paper, an environment aimed at integrating different software resources in a consistent and uniform way is proposed. It is based on object-oriented approach implemented in a knowledge based shell. In addition, full potential of knowledge based systems can be used for intelligent decision. Finally, an application example of an oil industry is given.21353135

Modelling, Optimization And Control Of Subway Systems.

A methodology that improves the operational use of reference schedules for the North-South line of the Metro Company of Sao Paulo is presented. Improvements with respect to the reference schedules are obtained by exploring the fact that the model used to generate reference schedules does not differentiate trains being dispatched from the Jabaquara yard. The strategy takes into account the maximum delay time possible with respect to the arrival time of each train in Jabaquara such that no train exceeds its capacity, and there is no violation of physical constraints imposed by the system or by maintenance requirements. Based on the limits determined above, the reference schedule is modified to adjust the arrival times at Jabaquara in order to redispatch trains. This methodology has been implemented and computer simulations have shown that it can improve further the operational utilization of trains.616516