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Improved MRO Inventory Management System in Oil and Gas Company: Increased Service Level and Reduced Average Inventory Investment

Author

Listed:
  • Usman Ali

    (Departmetnt of Industrial Engineering, Main Campus, University of Engineering and Technology, Peshawar 25100, Pakistan)

  • Bashir Salah

    (Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia)

  • Khawar Naeem

    (Departmetnt of Industrial Engineering, Main Campus, University of Engineering and Technology, Peshawar 25100, Pakistan)

  • Abdul Salam Khan

    (NUST Business School, National University of Science and Technology, Islamabad 44000, Pakistan
    Arts et Métiers Institute of Technology, Université de Lorraine, LCFC, F-57070 Metz, France)

  • Razaullah Khan

    (Department of Mechanical Engineering Technology, University of Technology, Nowshera 24100, Pakistan)

  • Catalin Iulian Pruncu

    (Mechanical Engineering, Imperial College London, Exhibition Road, South Kensington, London SW7 2AZ, UK
    Design, Manufacturing & Engineering Management, University of Strathclyde, Glasgow G1 1XJ, Scotland, UK)

  • Muhammad Abas

    (Departmetnt of Industrial Engineering, Main Campus, University of Engineering and Technology, Peshawar 25100, Pakistan)

  • Saadat Khan

    (Department of Industrial Engineering, Jalozai Campus, University of Engineering and Technology, Peshawar 25100, Pakistan)

Abstract

This study proposes a methodology for the oil and gas businesses to keep their production plant productive with a minimum investment in carrying maintenance, repair, and operating inventory planning. The goal is to assist the exploration and production companies in minimizing the investment in keeping maintenance, repair, and operating (MRO) inventory for improving production plant uptime. The MRO inventory is the most expensive asset and it requires substantial investment. It helps in keeping the oil and gas production plant productive by performing planned and unplanned maintenance activities. A ( Q , r ) model with a stock-out and backorder cost approach is combined with a continuous inventory review policy for the analysis of class A items of oil and gas production plant MRO inventory. The class A items are identified through popular ABC analysis based on annual dollar volume. The demand for the inventory is modeled through Poisson distribution with consideration of constant lead time. The ( Q , r ) model in both stock-out cost and backorder cost approaches assigned higher order frequency and lower service level to low annual demand and highly expensive items. The stock-out cost approach shows an 8.88% increase in the average service level and a 56.9% decrease in the company average inventory investment. The backorder cost approach results in a 7.77% increase in average service level and a 57% decrease in average inventory investment in contrast to the company’s existing inventory management system. The results have a direct impact on increasing plant uptime and productivity and reducing company maintenance cost through properly managing maintenance stock. The analysis is carried out on the oil and gas production plant’s MRO inventory data, but it can be applied to other companies’ inventory data as well. All the results reflected in this research are based on the inventory ordering policy of two orders per year. The inventory ordering frequency per year may be other than two orders per year depending on the type of organization.

Suggested Citation

  • Usman Ali & Bashir Salah & Khawar Naeem & Abdul Salam Khan & Razaullah Khan & Catalin Iulian Pruncu & Muhammad Abas & Saadat Khan, 2020. "Improved MRO Inventory Management System in Oil and Gas Company: Increased Service Level and Reduced Average Inventory Investment," Sustainability, MDPI, vol. 12(19), pages 1-19, September.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:19:p:8027-:d:421124
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    References listed on IDEAS

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    Cited by:

    1. Jindai Zhang & Jinlou Zhao, 2022. "Prediction-Driven Sequential Optimization for Refined Oil Production-Sales-Stock Decision-Making," Energies, MDPI, vol. 15(12), pages 1-19, June.

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