The method developed by Perm scientists will reduce downtime of broken equipment in companies and lower repair costs.

In all sectors of manufacturing, including oil extraction companies, a wide variety of equipment is utilized. The emergence of a malfunction or the breakdown of even a single machine results in costs and work interruptions while waiting for its replacement or repair. However, storing surplus spare parts at the facility is not practical. Therefore, alongside monitoring the condition of installations and predicting their failures, effective spare parts management is essential. Current methods rely on probabilistic approaches and complex mathematical models that require a substantial amount of input data. Researchers at Perm Polytechnic have optimized the service and ordering system for the necessary quantity of spare parts for modern industrial equipment. This method will minimize downtime of faulty machines and reduce operational costs for companies.

2024-12-27 10:00:12https://naked-science.ru/article/column/oborudovaniya-na-predpriy

The article was published in the journal "Reliability." The research was conducted as part of the strategic academic leadership program "Priority 2030."

The issue of improper management of equipment inventories at industrial enterprises spans all manufacturing sectors, particularly in oil extraction. Thus, the shutdown of a well is associated with enormous costs and leads to downtime of expensive installations during their replacement or repair.

Having excess devices on-site that can replace failures requires separate storage space and costs to maintain their operational readiness. Therefore, effective management of maintenance and spare parts is a crucial task that constitutes a significant portion of a company's operational expenses.

"The difficulty in accurately assessing the demand for spare parts and determining their necessary quantity in stock necessitates the development of an automated system that will allow for the most efficient and rapid execution of maintenance and repairs, thereby reducing financial costs and losses from downtime," explains Karina Leizgold, a senior lecturer at the Department of Microprocessor Automation Tools at PNRPU.

Scientists from Perm Polytechnic University have proposed a method for determining the optimal quantity of spare copies of failing assets. This method is based on data regarding the operation of the equipment in use and forecasting the probabilities of its failure. Unlike other similar methods, the proposed approach does not require a large amount of information or complex processing.

"To calculate the number of spare parts, data is collected on the operation of similar assets, specifically the time and volume of work completed by the installation. The probability of an asset failing is determined based on the number of days of operation, productivity is assessed at the beginning and end of the current ordering period, and the future volume of work until its failure is forecasted. Based on this, the necessary quantity of units to order in the next delivery is calculated. This method can be used as a standalone tool for planning the procurement of spare parts and machines or as the first step in analytics systems for maintenance and repair management," says Karina Leizgold.

Polytechnic specialists note that this approach only considers similar non-repairable assets that will be replaced with new ones upon failure. The proposed method was tested by calculating the required number of submersible electric motors for one of the oil fields. For this, a sample of data over six years regarding its failures at 18 wells was taken. For each supply period, precise figures for spare parts were calculated, which corresponded to reality.

The method developed by researchers at Perm Polytechnic University allows for the simple and accurate determination of the optimal number of spare parts for modern production equipment. Implementing this method in industrial enterprises will minimize the downtime of expensive machines during the replacement or repair of failed components.