Fuzzy multi-criteria analysis for machine tool selection and optimal machine loading in flexible manufacturing cell / Nguyen Huu Tho

Nguyen , Huu Tho (2016) Fuzzy multi-criteria analysis for machine tool selection and optimal machine loading in flexible manufacturing cell / Nguyen Huu Tho. PhD thesis, University of Malaya.

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      The flexible manufacturing cell (FMC), a unit of FMS, has the potential to be adapted widely by the small and medium enterprises (SMEs) in the automotive industry due to the low investment costs and less risk levels. The implementation of FMC, however, is a challenging task requiring complete integration of numerous components coming from various vendors. In particular, production planning related to machine loading problem (MLP) should be firstly considered when starting production process. Machine selection and machine loading strongly affect the system's efficiency and flexibility, thus forms a very strategic planning decision to achieve substantial manufacturing efficiency in automotive industry. In this research, an integrated framework is developed for the selection of appropriate machine tools and suitable combinations of machines and operations for machining. Past research have focused on only the selection of machines for processing a particular part type in manufacturing cell, thus the issues of machines and operations have been addressed individually and superficially. In addition, the allocation of operations to the selected machine is solved without real evidence of consideration of multiple objectives which are more relevant in the actual manufacturing context of the manufacturing enterprise. This developed framework for machine tool selection and machine loading in FMC consists of three phases. In the first phase, a decision support system is developed for solving a model of preliminary machine tool evaluation based on integration of fuzzy AHP (Analytic Hierarchy Process) and fuzzy COPRAS (COmplex PRoportional Assessment) from database of potential machines in the market. Subsequently, the finalization of machine selection decisions were carried out based on the novel hybrid approach of fuzzy ANP (Analytic Network Process) and COPRAS-G (Grey COmplex iv PRoportional Assessment). In addition, the sensitivity analysis is conducted to check the robustness of the alternative ranking of newly designed approach. A database of machine tools was collected from a potential set of machines from the market based on their specifications described in product catalogues of vendors, experts' experience and literature. In the second Phase, the FMC is formulated based on the selected machine from Phase 1. Several steps are implemented to select the most suitable solution for machine loading in FMC, which is presented in the form of the most appropriate combination of machine tools and operations. Problem formulation is established by constructing a mathematical model for FMC loading issue comprising of three objectives of minimizing the system unbalance, makespan and total flow time with the constraints of machines and tool magazines. Then, the combination of biogeography-based optimization (BBO) and non-dominated sorting procedure is developed to solve the proposed model. Finally, in the third Phase, a simulation of proposed FMC is implemented to evaluate and observe the performance and the applicability of the newly designed cell with respect to selected strategy of allocation. It was also used to verify the numerical results and validate the practical applicability to manufacturing cells in SMEs. The numerical results obtained showed that the proposed method has a potential alternative when compared with other research and the results of simulation based on performance indices such as system unbalance, makespan and total flow time.

      Item Type: Thesis (PhD)
      Additional Information: Thesis (PhD) - Faculty of Engineering, University of Malaya, 2016.
      Uncontrolled Keywords: Flexible manufacturing cell (FMC); Automotive industry; fuzzy ANP (Analytic Network Process); Machines; Production process
      Subjects: T Technology > TJ Mechanical engineering and machinery
      Divisions: Faculty of Engineering
      Depositing User: Mr Mohd Safri Tahir
      Date Deposited: 06 Dec 2018 03:18
      Last Modified: 26 Feb 2019 03:58
      URI: http://studentsrepo.um.edu.my/id/eprint/9307

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