Improved MRO inventory management system in oil and gas company: increased service level and reduced average inventory investment

Usman Ali, Bashir Salah, Khawar Naeem, Abdul Salam Khan, Razaullah Khan, Catalin Iulian Pruncu, Muhammad Abas, Saadat Khan

Research output: Contribution to journalArticle

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.
Original languageEnglish
Article number8027
Number of pages19
JournalSustainability
Volume12
Issue number19
DOIs
Publication statusPublished - 29 Sep 2020

Keywords

  • MRO inventory management
  • spare parts management
  • ABC classification
  • (Q, r) model
  • EOQ model
  • oil and gas company

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