Discipline: Technology and Engineering
Subcategory: Civil/Mechanical/Manufacturing Engineering
Session: 3
Room: Senate
Alejandro Najera Acosta - New Mexico State University
Co-Author(s): Delia Julieta Valles-Rosales, Texas A&M University Kingsville (TAMUK), Kingsville, TX.Hansuk Sohn, New Mexico State University (NMSU), Las Cruces, NM.
In the manufacturing industry, the availability of production equipment is influenced by the time of its repair. The latter is also influenced by the time needed to obtain a spare component or replacement. Spare parts management 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, their useful life is random, and their propagation is difficult to determine. Then, to overcome such drawbacks, stocks of spare parts are established in order to allow rapid replacement of failed components and ensure continuity of the operations. Nevertheless, stock management of spare parts is a significant challenge because the level of the spare parts inventory is constrained by the cost of stock, and the penalty of having a lack of stock can also be influenced by the time for obtaining spare parts. Also, these components have characteristics that differentiate them from other products. For the present work, it is proposed the use of reliability 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, employing engineering data to quantify the impact of influencing factors 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 parts required for an equipment can be effectively predicted on the basis of its reliability performance. According to the outcomes obtained, is concluded that the system’s working conditions have a significant influence on the system’s reliability characteristics and therefore on the stock management of spare parts. Future investigation suggests analyzing different parts with other covariates, their formulation, and integration.
Funder Acknowledgement(s): • I wish to thank Dr. Delia J. Valles-Rosales for her advice on this research, without your guidance this research would not be possible. • We are grateful to Mr. Jose Carrera, for allowing us access to its facilities.• We would like to thank the National Institute of Food and Agriculture, U.S. Department of Agriculture “ALFA-IoT-Alliance for Smart Agriculture in the Internet of Things Era” Award #2018-38422-28564 for their support.• We appreciate the support of the Industrial Engineering Department of NMSU, especially to Dr. Hansuk Sohn.
Faculty Advisor: Hansuk Sohn, hsohn@nmsu.edu
Role: As the project is closely related to my graduate research, I contributed to every step of the work done: literature review, data collection, methodology, experimentation, analysis of the results, etc. However, I have been guided through the entire project by my Mentor and Advisor.