Use of Non-linear Programming to Study Operational Efficiency of Maintenance on Railway Equipment
Year: 2024
Type: conference-paper
Abstract: The concept of optimization is generally associated with the strategic decision about the allocation of limited resources between competitive activities, aiming to obtain the best possible solution.In this context, Operations Research plays a fundamental role, in developing tools, processes and models that assist in decision-making.This study aimed to highlight the main maintenance management indicators and develop a mathematical model using non-linear programming, specifically the Lagrange method, to optimize two vital metrics in the railway sector: MTBF (Mean Time Between Failures) and MTTR (Mean Time to Repair).After collecting and structuring the data, the database was carefully designed to cover relevant aspects, such as recording months and dates of activities, detailed descriptions of the tasks performed, time dedicated to maintenance and identification of the equipment involved.This made it easier to perform specific calculations and see patterns over time.Based on the data collected, the analysis and manipulation of decision variables began.The objective function was modeled to maximize MTBF, increasing production and equipment reliability, while minimizing MTTR, and reducing downtime due to failures and repairs.This study highlights the importance of efficient management of industrial maintenance to ensure the availability and reliability of equipment, demonstrating the effectiveness of mathematical modeling in optimizing these processes.
Authors: DANIELY INÁCIO GALVÃO, LUCAS ROSENDO DOS SANTOS FARIAS, CARLOS JEFFERSON DE MELO SANTOS, CARLOS EDUARDO DA SILVA ALBUQUERQUE, ELAINE FERREIRA ROCHA
Institution: Universidade Federal do Vale do São Francisco
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4404138222