Application of ABC Classification, EOQ, Fuzzy AHP, Time Series Models to improve order fulfillment in a trading company of household appliances
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Most small and medium-sized enterprises (SMEs) do not survive more than five years in the Peruvian market and one of the main reasons is the inefficient logistics administration and inventory control. This represents a serious problem because these businesses play a fundamental role in the growth of the country's economy and trade. Therefore, this research focuses on the analysis of 4 engineering tools applied integrally to improve order fulfillment (identified as the main problem) of a trading company of household appliances. This model makes use of tools such as: ABC classification for the categorization of the merchandise, time series models for demand forecasting, fuzzy AHP methodology for the selection of suppliers and EOQ principle for definition of inventory policies. After model validation, it was observed that order fill rate increased from 80.40% to 95.61%, demonstrating the positive impact that could be generated for the business.
How to citeFlores-Perez, A., Valdivia-Seminario, C. & Marín-Becerra, F. (2023). Application of ABC Classification, EOQ, Fuzzy AHP, Time Series Models to improve order fulfillment in a trading company of household appliances. In Proceedings of the 10th International Conference on Industrial Engineering and Applications, ICIEA-EU 2023, Rome, Italy, January 2023, 253-259. https://doi.org/10.1145/3587889.3588208
PublisherAssociation for Computing Machinery
Category / SubcategoryPendiente / Pendiente
JournalACM International Conference Proceeding Series
- Ingeniería Industrial