An Integrated Lean and Machine Learning Approach to Inventory Management in Automotive Accessories SMES
An Integrated Lean and Machine Learning Approach to Inventory Management in Automotive Accessories SMES |
||
 |
 |
|
| © 2025 by IJETT Journal | ||
| Volume-73 Issue-9 |
||
| Year of Publication : 2025 | ||
| Author : Adolfo Ochoa-González, Kevin Mendoza-Quintanilla, Juan Carlos Quiroz-Flores | ||
| DOI : 10.14445/22315381/IJETT-V73I9P125 | ||
How to Cite?
Adolfo Ochoa-González, Kevin Mendoza-Quintanilla, Juan Carlos Quiroz-Flores,"An Integrated Lean and Machine Learning Approach to Inventory Management in Automotive Accessories SMES", International Journal of Engineering Trends and Technology, vol. 73, no. 9, pp.288-308, 2025. Crossref, https://doi.org/10.14445/22315381/IJETT-V73I9P125
Abstract
In the Peruvian automotive accessories sector, low inventory turnover is a critical problem that hinders operational efficiency, increases storage costs, and reduces liquidity. This study aims to design and validate an integrated inventory management model to improve stock turnover in an automotive accessories warehouse. The model combines ABC classification, Economic Order Quantity (EOQ), slotting, 5S methodology, and machine learning-based demand forecasting. The methodology includes a systematic literature review, problem diagnosis, tool integration, simulation in Arena software, and pilot implementation. Key results revealed a 33.43% improvement in inventory turnover, a 30% reduction in average inventory, a 60% decrease in picking time, and a 19.95% reduction in total logistics costs. Additionally, the study achieved an 18.5% improvement in Inventory Record Accuracy (IRA) and a 22.69% increase in Location Record Accuracy (LRA). These findings highlight the effectiveness of integrating lean and technological tools in enhancing inventory management in automotive accessories warehouses. The study addresses a research gap in Latin America and offers a replicable model that contributes to improving operational efficiency and sustainability in similar industrial contexts.
Keywords
Inventory management, Stock rotation, Machine learning, Multi-criteria ABC, PYME, 5S, Slotting, Kardex.
References
[1] Sierra Bautista, and Fabian Mauricio, “Improvement Plan in the Storage and Dispatch Processes of the Company Electrical Distribution JE SAS,” Universidad Industrial de Santander, Bucaramanga, Colombia, pp. 17-130, 2017.
[Google Scholar] [Publisher Link]
[2] Edward Frazelle, Supply Chain Strategy: The Logistics of Supply Chain Management, McGraw-Hill Education, 2002.
[Google Scholar] [Publisher Link]
[3] Micro and Small Businesses in Peru Results in 2021, ComexPerú - Peruvian Foreign Trade Society, 2021. [Online]. Available: https://www.comexperu.org.pe/upload/articles/reportes/reporte-comexperu-001.pdf [4] Juan Carlos Capuñay, APEC Summit Bangkok 2022, El Peruano, 2022. [Online]. Available: https://www.elperuano.pe/noticia/198167-cumbre-apec bangkok-2022
[5] Editorial Management, 66% of Companies in the Country have an Incipient Level of Management in their Supply Chain, Gestion, 2021. [Online]. Available: https://gestion.pe/economia/el-66-de-empresas-en-el-pais-tiene-un-nivel-de-gestion-incipiente-en-su-cadena-de-suministros-nndc-noticia/
[6] Gastón Guillermo Suárez Gallegos, and Polet Denisse Cárdenas Miranda, “Inventory Turnover and its Impact on Cash Flow,” Latin American Economic Observatory Journal, Ecuador, 2017.
[Google Scholar] [Publisher Link]
[7] Pradeep Kumar Shetty, and C. Raghavendra Kamath, “A Study of Inventory Management at Manufacturing Industries in Rural India,” International Journal of Mechanical and Production Engineering Research and Development, Karnataka, India, vol. 9, no. 1, pp. 73-80, 2018.
[Google Scholar] [Publisher Link]
[8] Wisam AL-Dulaime, and Walid Emar, “Analysis of Inventory Management of Laptops Spare Parts by using XYZ Techniques and EOQ Model - A Case Study,” International Journal of Scientific and Technology Research, vol. 8, no. 10, pp. 3766-3774, 2019.
[Google Scholar] [Publisher Link]
[9] Usman Ali et al., “Improved MRO Inventory Management System in Oil and Gas Company: Increased Service Level and Reduced Average Inventory Investment,” Sustainability, vol. 12, no. 19, pp. 1-19, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Felix Weidinger, “Picker Routing in Rectangular Mixed Shelves Warehouses,” Computer & Operations Research, vol. 95, pp. 139-150, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Elia Oey, and Maulana Nofrimurti, “Lean Implementation in Traditional Distributor Warehouse - A Case Study in an FMCG Company in Indonesia,” International Journal of Process Management and Benchmarking, vol. 8, no. 1, pp. 1-15, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Ram Babu Verma, and Sanjay Kumar Jha, “Implementation of 5S Framework and Barriers modelling through Interpretive Structure Modelling in a Micro Small Medium Enterprise,” International Journal of Recent Technology and Engineering, Maharashtra, India, vol. 8, no. 3, pp. 7016-7017, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Ajay Johnson, Syamjith Prasad, and Ashok Kumar Sharma, “Manufacturing Lead Time Reduction in a Scaffold Making Industry using Lean Manufacturing Techniques - A Case Study,” International Journal of Mechanical Engineering and Technology, vol. 8, no. 2, pp. 137-148, 2017.
[Google Scholar] [Publisher Link]
[14] Pablo Viveros et al., “Slotting Optimization Model for a Warehouse with Divisible First-Level Accommodation Locations,” Applied Sciences, Switzerland, vol. 11, no. 3, pp. 1-30, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[15] D. Wu et al., “Vehicle Routing Problem with Time Windows using Multi-Objective Co-Evolutionary Approach,” International Journal of Simulation Modelling, Viena, Austria, vol. 15, pp. 742-753, 2016.
[Google Scholar] [Publisher Link]
[16] Vasiliki Kapou et al., “An Innovative Layout Design and Storage Assignment Method for Manual Order Picking with Respect to Ergonomic Criteria,” Logistics, Basilea, Suiza, vol. 6, no. 4, pp. 1-21, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Mehdi Keshavarz Ghorabaee et al., “Multi-Criteria Inventory Classification using a New Method of Evaluation Based on Distance from Average Solution (EDAS),” Informatica: An International Journal of Computing and Informatics, vol. 26, no. 3, pp. 435-451, 2015.
[Google Scholar] [Publisher Link]
[18] I.M.D.P. Asana et al., “Inventory Control using ABC and Min-Max Analysis on Retail Management Information System,” Journal of Physics: Conference Series, Bali, Indonesia, vol. 1469, no. 1, pp. 1-10, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Milan Jemelka et al., “ABC Analyses with Recursive Method for Warehouse,” 2017 4th International Conference on Control, Decision and Information Technologies (CoDIT), Barcelona, Spain, pp. 960-963, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Thanichkarn Phupattarakit, and Parames Chutima, “Warehouse Management Improvement for a Textile Manufacturer,” 2019 IEEE 6th International Conference on Industrial Engineering and Applications (ICIEA), Tokyo, Japan, pp. 235-239, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Jenny Gutierrez Lopez, Alvaro Freile, and Sofia Lopez Iglesias, “Reduction in Picking Times Orders for Delivery in a National Distribution Center: A Case Study,” 17th LACCEI International Multi-Conference for Engineering, Education, and Technology, Montego Bay, Jamaica, pp. 24-26, 2019.
[Google Scholar] [Publisher Link]
[22] Johanna Rodríguez-León, and Mateo Pachón-Rincón, “Forecast in Planning, a Case of Study in a Distribution Company of the Pharmaceutical Sector,” Revista UIS Ingenierías, vol. 20, no. 4, pp. 59-78, 2021.
[CrossRef] [Publisher Link]
[23] Jente Van Belle, Tias Guns, and Wouter Verbeke, “Using Shared Sell-through Data to Forecast Wholesaler Demand in Multi-Echelon Supply Chains,” European Journal of Operational Research, Brussels, Belgium, vol 288, no. 2, pp. 466-479, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[24] G. Sudheer, and A. Suseelatha, “Short Term Load Forecasting using Wavelet Transform Combined with Holt-Winters and Weighted Nearest Neighbor Models,” International Journal of Electrical Power & Energy Systems, vol. 64, pp. 340-346, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Qing-Zhou Wang et al., “Waste Tire Recycling Assessment: Road Application Potential and Carbon Emissions Reduction Analysis of Crumb Rubber Modified Asphalt in China,” Journal of Cleaner Production, vol. 249, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[26] Umamaheswaran Praveen, Ganjeizadeh Farnaz, and Ghasib Hatim, “Inventory Management and Cost Reduction of Supply Chain Processes using AI Based Time-Series Forecasting and Ann Modeling,” Procedia Manufacturing, vol. 38, pp. 256-263, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[27] R. Nigah, M. Devnani, and A.K. Gupta, “ABC and VED Analysis of the Pharmacy Store of a Tertiary Care Teaching, Research and Referral Healthcare Institute of India,” Journal of Young Pharmacists, vol. 2, no. 2, pp. 201-205, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[28] Sandeep Kumar Panda, and Sachi Nandan Mohanty, “Time Series Forecasting and Modeling of Food Demand Supply Chain Based on Regressors Analysis,” IEEE Access, vol. 11, pp. 42679-42700, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[29] Byung Soo Kim, and Jeffrey S. Smith, “Slotting Methodology using Correlated Improvement for a Zone-Based Carton Picking Distribution System,” Computers & Industrial Engineering, vol. 62, no. 1, pp. 286-295, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[30] Cristhian Alvarez et al., “Warehouse Model to Increase the OTIF by Applying BPM and Lean Warehousing in a SME in the Footwear Sector,” Proceedings of the 15th International Conference on Industrial Engineering and Operations Management, Singapore, pp. 1-7, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[31] Adithya Narayanan Rajesh, “Labor-Saving in Order Picking- A Real Time Study Advancing Lean Operations,” American Journal of Supply Chain Management, vol. 9, no. 3, pp. 16-25, 2024.
[Google Scholar] [Publisher Link]
[32] D. Battini et al., “Consignment Stock Inventory Model in an Integrated Supply Chain,” International Journal of Production Research, vol. 48, no. 2, pp. 477-500, 2010.
[CrossRef] [Google Scholar] [Publisher Link]