نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار دانشکده علوم اداری و اقتصاد دانشگاه اصفهان

2 استادیار دانشکده علوم اداری و اقتصاد دانشگاه اصفهان،

3 کارشناسی ارشد مدیریت تولید و عملیات دانشگاه اصفهان

چکیده

طرح ریزی فرآیند شامل تعیین مناسبترین و کارآمدترین فرآیندهای ساخت )مونتاژ( و نیز تعیین توالی آنها به
منظور تولید یک محصول )قطعه(، مطابق با مشخصه های مورد نیازی است که در مستتندات طرا حی  محصول،
ذکر شده است. در مقاله حاضر در رویکردی یکپارچه به بهینه سازی برنامه ریزی فراینتد و زمانننتدی با در نظر
داشتن پارامترهای کیفی موثر در سیستم ساخت و تولید کارگاهی و انعطاف پذیر پرداخته شده است. برای حل
مسئله، از تلفیق الگوریتم های فراابتکاری و سیستم استنتاج فازی در قالب توابع هدف چندگانه و آرمانی شامل
کمینه سازی هزینه و زمان پردارش قطعات و بیشینه سازی مطلوبیت طرح فرایند )از نظر پارامترهای کیفی جریان
مواد، پایداری، سهولت جابه جایی و ارتباط نظارتی( با استفاده از پایگاه دانش فازی و با توجه به محدودیتهای
سیستمی و آرمانی استفاده شده است. نتایج مطالعه حاکی از آن است که الگوریتم فراابتکاری شبیه  سازی تبریدعسل
کارایی بهتری در حل مدل پیشنهادی دارد

کلیدواژه‌ها

عنوان مقاله [English]

Integrated Approach of Process Scheduling and Planning Based on Combining Fuzzy Knowledge Base and Meta Heuristic Method

نویسندگان [English]

  • Darush Mohamadi Zanjirani 1
  • Majid Esmailian 2
  • Saeedeh Jokar 3

چکیده [English]

Process planning involves determining the most suitable and efficient manufacturing (assembly) processes and their sequence in order to produce a product (part). These processes should be compatible with required attributes in product design documentation. Process planning and scheduling optimization is done with Considering qualitative parameters which are affective on job shop and flexible system. Fuzzy Inference System and Meta-heuristic algorithms with multiple objective and goal functions are used to solving problem. Objective functions include minimization of cost and time of processing parts and maximizing the utility of the process design. based on the illustrated numerical example simulated annealing algorithm has better efficiency than imperialist competitive algorithm, particle swarm, bee colony.

کلیدواژه‌ها [English]

  • Meta-Heuristic Algorithm
  • process planning
  • fuzzy knowledge base
  • Integrated approach
  • Scheduling
  • flexible manufacturing system
Adithan, M. (2007). Process Plsnning and Cost Estimation. Publishing for one world new age international (P) limited, publishers.
Chan, T. S ; Kumar,V; Tiwari ,M. K.(2006). Optimizing the Performance of an Integrated Process Planning and Scheduling Problem: An AIS-FLC based Approach, 1-4244-0023-6/06/$20.00 © IEEE
Khoshnevis, B.(2000). Integration of process planning and scheduling a review, Journal of Intelligent Manufacturing , 11, 51-63
Li, W. D; Mcmahan, C. A. (2007). A simulated annealing-based optimization approach for integrated process planning and scheduling. International Journal of Computer Integrated Manufacturing, 20:1, pp.80-95,
Lian, K; Zhang, Ch; Shao, X; & Gao,L. (2012). Optimization of process planning with various flexibilities using an imperialist competitive algorithm. International Journal Advanced Manufacturing Technology, vol. 59, pp. 815–828, DOI 10.1007/s00170-011-3527-8.
Wan, S.Y; Wong, T.N; Zhang,S; Zhang,L(2006). Integrated Process Planning and Scheduling whit Setup Time Consideration by Ant Colony Optimization. Proceedings of the 41st International Conference on Computers & Industrial Engineering
Wang, Y.F; Zhang, Y.F; & Fuh, J.Y.H. (2010). A PSO-based multi-objective optimization approach to the integration of process planning and scheduling. IEEE International Conference on Control and Automation, Xiamen, China, June 9-11.
Wang,Zh;Tian,j.(2008). The research about integration of process planning and production scheduling based on genetic algorithm, International Conference on Computer Science and Software Engineering
Zhao, F; Zhang,Q; & Yang,Y. ( 2006). An improved particle swarm optimization(PSO) algorithm and fuzzy inference systems based approach to process planning and production scheduling integration in holonic manufacturing system (HMS). Machine Learning and CyberneticsInternational Conference, 13-16 Aug, pp.396 – 401.
رویکرد یکپارچه زمانبندی و برنامهریزی فرایند بر مبنای تلفیق پایگاه... 616
Akgun, A., Sezer, E.A., Nefeslioglu, H.A., Gokceoglu, C., and Pradhan, B. (2011). An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm. Computers & Geosciences, Article in press.
Katambara, Z, and Ndiritu, J. (2009). A fuzzy inference system for modeling streamflow: Case of Letaba River, South Africa. Physics and Chemistry of the Earth, Vol. 34, pp. 688-700.
Mahapatra, S.S., Nanda, S.K., and Panigrahy, B.K. (2011). A Cascaded Fuzzy Inference System for Indian river water quality prediction. Advances in Engineering Software, Vol. 42, pp. 787-796.
Silvert, W. (2000). Fuzzy indices of environmental conditions, Ecological Modelling, Vol. 130, No. 1-3, pp. 111-119.
Atashpaz Gargari.E, (2008) "social optimization algorithm development and performance review," MS Thesis, School of Electrical and Computer Engineering Tehran University, In Persian
Zare mehrjerdi. Y,Barghi.sh, momeni. H, (2011), "The use of innovative methods to solve problems like slow cooling of the supply chain", Faculty of Engineering, University of Yazd, Journal of Operations Research and Applications, Issue 3, In Persian
Kashefi.A,Pormosavi.S.A,Jahanbani ardakani.A, (2007), "Training a multilayer neural networks using particle swarm algorithm", Amirkabir University of Technology, Faculty of Electrical Engineering, Intelligent Systems Conference, Ferdowsi University of Mashhad, In Persian