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An efficient integrated simulation–Taguchi approach for sales rate evaluation of a petrol station

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Abstract

This study proposed an incorporated simulation–Taguchi model to optimize a petrol station sales rate. In addition, it provided a regression model to forecast the sales rate. Initially, Witness 2014 simulation software© was used to simulate the operating system of a petrol station. Next, the obtained simulation results were used as the input for Taguchi method to optimize the process. Taguchi L 4 standard orthogonal array was taken to optimize the petrol station parameters including the number of pumps, number of cashiers and customers’ interarrival times (IATs) to obtain a better sales rate. Three noise factors such as petrol station location, different cashiers and different dispensers considered as potential factors affecting the response. Based on Taguchi methodology, number of pumps and IAT were identified as highly contributing factors on the sales rate. The remaining factor (number of cashier) similarly influences the response, but the effect is not very significant. Therefore, the importance sequence of the sales rate parameter is IATs > number of pumps > number of cashiers. The regression equation was formulated to maximize the sales rate (Liter) and then verified by the confirmation runs.

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Authors and Affiliations

  1. Department of Materials, Manufacturing and Industrial Engineering, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia (UTM), 81310, Johor Bahru, Johor, Malaysia

    Masoud Rahiminezhad Galankashi, Ehsan Fallahiarezoudar, Anoosh Moazzami, Syed Ahmad Helmi, Jafri Mohd Rohani & Noordin Mohd Yusof

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  1. Masoud Rahiminezhad Galankashi
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  2. Ehsan Fallahiarezoudar
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  3. Anoosh Moazzami
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  4. Syed Ahmad Helmi
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  5. Jafri Mohd Rohani
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  6. Noordin Mohd Yusof
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Correspondence to Masoud Rahiminezhad Galankashi.

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Galankashi, M.R., Fallahiarezoudar, E., Moazzami, A. et al. An efficient integrated simulation–Taguchi approach for sales rate evaluation of a petrol station. Neural Comput & Applic 29, 1073–1085 (2018). https://doi.org/10.1007/s00521-016-2491-5

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  • DOI: https://doi.org/10.1007/s00521-016-2491-5

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