TY - GEN
T1 - Application of ABC Classification, EOQ, Fuzzy AHP, Time Series Models to improve order fulfillment in a trading company of household appliances
AU - Valdivia Seminario, Carlos
AU - Flores Perez, Alberto Enrique
AU - Marin Becerra, Fiorella
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/1/9
Y1 - 2023/1/9
N2 - 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.
AB - 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.
KW - ABC Classification
KW - EOQ
KW - Fuzzy AHP
KW - Time Series Models
UR - http://www.scopus.com/inward/record.url?scp=85162878316&partnerID=8YFLogxK
U2 - 10.1145/3587889.3588208
DO - 10.1145/3587889.3588208
M3 - Articulo (Contribución a conferencia)
AN - SCOPUS:85162878316
T3 - ACM International Conference Proceeding Series
SP - 253
EP - 259
BT - Proceedings of the 2023 10th International Conference on Industrial Engineering and Applications, ICIEA-EU 2023
PB - Association for Computing Machinery
T2 - 10th International Conference on Industrial Engineering and Applications, ICIEA-EU 2023
Y2 - 9 January 2023 through 11 January 2023
ER -