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A New Mathematical Model Towards the Cellular Manufacturing System Considering Multi-Functional Unreliable Machines in Uncertain Environment

Mohammaditalab, Atiyeh | 2016

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 48367 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Rafiee, Majid
  7. Abstract:
  8. Cellular Manufacturing System (CMS) is one of the most practical manufacturing systems based on the Group Technology (GT) concept. In this thesis, a CMS is evaluated and analyzed through the proposing new mathematical models. A cellular manufacturing system includes four main sub-problems; Cell formation (CF), Group Scheduling (GS), Group Layout (GL) and Resource Assignment (RA). In this paper two problems of CF and RA are studied and discussed.At first, a new mathematical model is proposed for a CF problem. The objectives are the minimization of inter-intra cell part trips, machine breakdown cost, tool consumption cost and the reconfiguration cost. Multi-functional machines unreliability is taken into account in this model.After solving the previous model and setting the related variables into their optimal values, another model is suggested to assign the operators –as main manufacturing resources- to machines and cells based on their skill levels. Operator related costs including the hiring, firing and salary costs are minimized by solving this model. The main novelty of the model is considering the learning and forgetting effect of an operator and his/her skill level changes. Actually an operator skill level can be changed during the time and based on the time he/she spent on a tool and machine. This feature has been regarded and analyzed in this stage. Then these two models are integrated by using the LP-metric method and is shown that the concurrent solution is better than or equal to the solution obtained by hierarchical solving of CF and RA models. Some numerical examples are generated randomly and used in order to evaluate the performance of proposed models.
    Parameter uncertainty is a new concern in many industrial plants for decision makers who want to obtain a stable manufacturing system. One of the main contribution of this thesis is to consider and analyzed this reality. So important factors uncertainty are discussed in this thesis through a robust optimization approach. Using the implemented approach, a change in a parameter can’t change the optimal solution feasibility even its optimality. Based on the numerical examples, the model can reach optimal solution in a reasonable computational time and can be implemented in industrial plants with the capability of being a CMS
  9. Keywords:
  10. Cellular Manufacturing ; Robust Optimization ; Machine Breakdown ; Multi-Functional Machines ; Operator Learning-Forgetiting

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