A decision support system based on artificial neural network and fuzzy analytic network process for selection of machine tools in a flexible manufacturing system

Sadeghian, Ramin; Sadeghian, Mohammad Reza

doi:10.1007/s00170-015-7440-4

Cited by 36 publications

(12 citation statements)

References 35 publications

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“…Additionally, the FANP has been employed to encompass the relationship between all the criteria affected by each other, thus making the relationship between selection criteria look more real. 27 The fuzzy numbers used in this method are triangular fuzzy numbers, and the fuzzy scale utilized is illustrated in Table 1.…”

Section: Fanp Methodsmentioning

confidence: 99%

Optimal maintenance strategy selection based on a fuzzy analytical network process

Borjalilu

Ghambari

2018

International Journal of Engineering Business Management

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Maintenance is one of the most crucial issues in today's competitive manufacturing environment. Nowadays, productive methods are used in manufacturing plants to improve operations capabilities, which alternatively change business environmental factors leading to a competitive market. Consequently, selection and illustration of an optimal maintenance strategy play a significant role in achieving these goals. Also, lack of an integrated model is felt, one that consists of available criteria and options, a systematic approach in setting maintenance instructions and robust maintenance decision-making. So, based on the fuzzy analytical network process (FANP) method, which composes criteria and options, a new approach to selecting optimal maintenance strategy is proposed in this article. Here, using multi-attribute decision-making in conjunction with application of fuzzy numbers structure has been regarded as an efficacious method for determining the significance of each criterion and option. The criteria that are considered in the FANP method are organization, safety, administration, staff, and technical requirements. The options (strategies) that are taken into consideration in this study are time-based preventive maintenance, corrective maintenance, condition-based maintenance, reliability-centered maintenance, and predictive maintenance. After implementing the method proposed for a 5-MW powerhouse (a case study undertaken for the purpose of this study), the predictive maintenance strategy was selected. According to expert opinions, it is the administrative and staff requirements that must be highlighted for selecting the best strategies.

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Section: Fanp Methodsmentioning

confidence: 99%

Optimal maintenance strategy selection based on a fuzzy analytical network process

Borjalilu

Ghambari

2018

International Journal of Engineering Business Management

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“…Scheduling of an FMS is NP-hard problem and it is more complex as compared to classical job shop scheduling problems. Different heuristic-based approaches including cuckoo search, PSO, GA and artificial neural network have been used in an FMS scheduling (Sankar et al 2003;Jerald et al 2005;Burnwal and Deb 2013;Sadeghian and Sadeghian 2016). A hybrid multi-objective GA was presented to optimize makespan, AGV travel time and penalty cost due to jobs lateness.…”

Section: Introductionmentioning

confidence: 99%

Role of batch size in scheduling optimization of flexible manufacturing system using genetic algorithm

2018

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Flexible manufacturing system (FMS) readily addresses the dynamic needs of the customers in terms of variety and quality. At present, there is a need to produce a wide range of quality products in limited time span. On-time delivery of customers' orders is critical in make-to-order (MTO) manufacturing systems. The completion time of the orders depends on several factors including arrival rate, variability, and batch size, to name a few. Among those, batch size is a significant construct for effective scheduling of an FMS, as it directly affects completion time. On the other hand, constant batch size makes MTO less responsive to customers' demands. In this paper, an FMS scheduling problem with n jobs and m machines is studied to minimize lateness in meeting due dates, with focus on the impact of batch size. The effect of batch size on completion time of the orders is investigated under following strategies: (1) constant batch size, (2) minimum part set, and (3) optimal batch size. A mathematical model is developed to optimize batch size considering completion time, lateness penalties and setup times. Scheduling of an FMS is not only a combinatorial optimization problem but also NP-hard problem. Suitable solutions of such problems through exact methods are difficult. Hence, a meta-heuristic Genetic algorithm is used to optimize scheduling of the FMS.

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“…Jamali et al (2015) presented an integration approach based on stepwise weight assessment ratio analysis method and complex proportional assessment of alternativesgrey for solving the advanced manufacturing systems problems. Sadeghian and Sadeghian (2016) presented a decision support system with artificial neural networks and fuzzy analytic network process to choose the most suitable flexible manufacturing system (FMS). Mittal et al (2017) utilising the fuzzy AHP and Shainin system for productivity improvement under manufacturing environments.…”

Section: Introductionmentioning

confidence: 99%

Solving group decision-making problems in manufacturing systems by an uncertain compromise ranking method

Mousavi

Foroozesh

Gitinavard

et al. 2018

IJADS

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The purpose of this paper is to introduce a new modified compromise ranking method (VIKOR), known as sorting the possible alternatives and determining the compromise solution under interval-valued hesitant fuzzy sets (IVHFSs) for solving group decision-making problems in manufacturing systems. By using numerical measure and crisp data, the decision making is complex in real-life situations because the decision makers (DMs)' judgments are usually hesitant and vague. A more applicable and realistic approach based on interval-valued hesitant fuzzy elements (variables) is presented and defined as the inputs to the presented VIKOR method. The proposed interval-valued hesitant fuzzy modified VIKOR (IVHF-MVIKOR)

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A decision support system based on artificial neural network and fuzzy analytic network process for selection of machine tools in a flexible manufacturing system

Cited by 36 publications

References 35 publications

Optimal maintenance strategy selection based on a fuzzy analytical network process

Optimal maintenance strategy selection based on a fuzzy analytical network process

Role of batch size in scheduling optimization of flexible manufacturing system using genetic algorithm

Solving group decision-making problems in manufacturing systems by an uncertain compromise ranking method

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