Technological development of automotive MSEs in Peru as a catalyst for the Latin American Manufacturing Hub: A model with Machine Learning and DDMRP

The MSEs metal-mechanics in Peru are faced with the challenge of delivering the orders on time and complete, becoming a hard challenge to accomplish. In the case of CREATEM S.A.C. is a manufacturing MSE dedicated to the fabrication of replacement parts for motorized vehicles that present a low OTIF of 47.45% very low compared to the standard which is 80%. Currently, the metal-mechanic sector represents a 11% of the manufacturing industry and the MSEs cover a 99.2% of the total companies in Peru. However, the majority of that have problems with adequate inventory control of the raw material. To this end, in order to reduce its economic impact as a solution, a comprehensive DDMRP and Machine Learning model is proposed to forecast the demand and manage the inventory dynamically. After the validation of the model, we obtained an improvement of the OTIF of 79.45%, as well as a reduction in the stock out rate to 8.2%. The proposal proved to be robust to lead time variations and demand peaks thanks to the buffers adjustment. It not only improved CREATEM logistics performance but also contributed strategically to position Peruvian automotive MSEs as a catalysts of the Latin American Hub.