Discipline: Technology and Engineering
Subcategory: Civil/Mechanical/Manufacturing Engineering
Alejandro Najera-Acosta - New Mexico State University
Co-Author(s): Delia Julieta Valles-Rosales, New Mexico State University (NMSU), Las Cruces, NM
In today’s global market, only those companies that consider all aspects of processes or systems performance remain competitive. An important aspect of systems performance is maintenance. Different studies have indicated that for many components is a system, maintenance account for as much as 60% to 75% of their overall life cycle costs. Management of spare components is a key feature for the performance of maintenance activities. Spare parts constitute an essential element in all industries, they are designed for a specific use, its useful life is random and its propagation is difficult to determine. Then, to overcome such drawbacks, spare components inventories are established in order to allow rapid replacement of failed components and ensure a continuity of the operations.
However, management of spare parts inventory is a significant challenge because these components/parts have characteristics that differentiate them from other products. For the current work, it is proposed the survival model of proportional hazards, to estimate the failure risk of an equipment when it is subjected to its working conditions. The study was carried out in a local manufacturing company, utilizing engineering data to quantify the impact of influencing factors (covariates) on the reliability performance of non-repairable spare components and to estimate its required number to maintain in stock. The results show that the number of spare components required for an equipment can be effectively predicted on the basis of its reliability performance, nevertheless the reliability characteristics of an equipment are not influenced by the operating time only but also by various factors, such as the working environment (e.g. temperature, etc.), the condition-indicating parameters (e.g pressure, etc.), and human aspects (e.g. operators, etc.).
Summarizing, the proposed approach is a logical and systematic methodology considering survival modeling for the spare components prediction in manufacturing systems, which makes it easily portable into practice. According to the outcomes obtained, is concluded that the system’s working conditions has a significant influence on the system’s reliability characteristics and therefore on the management of spare components. Future research suggests investigation analyzing different components with other covariates, its formulation and integration when forecasting spare components.
?Ben-Daya, M., Duffuaa, S. O., & Raouf, A. (Eds.). (2012). Maintenance, Modeling and Optimization. Springer Science & Business Media.
?Ouali, M. S., Yacout, S., & Ait-Kadi, D. (Eds.). (2011). Replacement Models with Minimal Repair. Springer.
?Sheikh, A. K., Younas, M., & Raouf, A. (2000). Reliability based spare parts forecasting and procurement strategies. In Maintenance, Modeling and Optimization (pp. 81-110). Springer US.
Not SubmittedFunder Acknowledgement(s): -I wish to acknowledge the generous sustenance of the USDA I-DISCOVER Grant Funded by the US Department of Agriculture that make this research a reality. Award # 2015-38422-24112. -I would like to thank to my advisor Dr. Delia J. Valles-Rosales, without
Faculty Advisor: Delia Julieta Valles-Rosales, dvalles@ad.nmsu.edu
Role: I worked through all the steps of the proposed methodology (data collection, classification, calculation, etc.), I got involved in the area of maintainability where were addressed the concepts of maintenance, reliability, subtractive manufacturing, spare components inventory. The aim of the research contemplates the development of a practical and effective methodology that provide guidelines for engineers at the operation site for the requires spare components prediction for a system with respect to influencing factors. An approach considering survival modeling is proposed for its prediction to improve accuracy in the inventory management of spare pars, using Industrial Engineering (IE) thinking and techniques.