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An adaptive neuro-fuzzy inference system for makespan estimation of flexible manufacturing system assembly shop: a case study

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Abstract

This paper considers the use of combination of neural networks and fuzzy system i.e. adaptive neuro-fuzzy inference system (ANFIS) applied to the n job, m machine real flexible manufacturing system assembly shop problem with the objective of prediction of makespan. Assembly shop makespan is calculated by Nawaz, Enscor, and Ham (NEH) algorithm. On the basis of this algorithm, adaptive neuro-fuzzy inference system model is made to predict the makespan of the jobs. The purpose of this study is to find the makespan estimation in advance if processing time of machines is known. The purpose of this research is to gain the advantage of the capabilities of both Fuzzy systems, which is a rule-based approach and neural network which focus on the network training. This model has been verified by testing and actual data set with the average percentage accuracy achieved is 95.97%. Coefficient of determination and Correlation coefficient is 0.9310 and 0.9649 respectively. The derived values of ANFIS model output are found within the range after being verified practically. Therefore, it can be concluded that makespan calculation of the production system, by the proposed adaptive neuro-fuzzy inference system, can be used as a reliable approach in estimating the makespan of flexible manufacturing system assembly shop.

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Acknowledgement

We would like to thank everyone that participated in this research work, in particular Dr. Salim Heddam, Associate Professor, Faculty of Science, Agronomy Department, Hydraulic Division University 20 Août 1955 SKIKDA 21000 Route EL HADAIK, BP 26, SKIKDA, Algeria for the help in methodology. We express our gratitude all the anonymous reviewers of this paper for their valuable suggestions, who have helped to improve the quality of this paper.

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  1. Department of Mechanical Engineering, Amity University Haryana, Gurgaon, India

    Vineet Jain

  2. Department of Mechanical Engineering, YMCA University of Science and Technology, Faridabad, India

    Tilak Raj

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  1. Vineet Jain
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Correspondence to Vineet Jain.

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Jain, V., Raj, T. An adaptive neuro-fuzzy inference system for makespan estimation of flexible manufacturing system assembly shop: a case study. Int J Syst Assur Eng Manag 9, 1302–1314 (2018). https://doi.org/10.1007/s13198-018-0729-6

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  • DOI: https://doi.org/10.1007/s13198-018-0729-6

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