RESUMEN
Global competitiveness creates a challenge for manufacturing companies to maintain their market share with dynamic customer requirements. Capital investment in machinery does not allow facility expansion to accommodate large orders from customers but to reconfigure the manufacturing enterprise. Distributed manufacturing (DM) is embraced in order to increase facility utilization by decentralizing production. An enterprise in charge of a DM network allows customers to choose the best manufacturers available for their order based on their track record, which is available through historical and online performance data. Furthermore, manufacturers as members of this network may receive orders based on their past performance. Industry 4.0 with all necessary Industrial Internet of Things (IIoT) enables the online monitoring of production key parameters of manufacturers subscribed to a DM network. We develop a new network model of manufacturers teamed under specific terms and conditions to support a group of customers who have specific needs. The proposed model, known as the continuous supervised model, is created with the ARENA simulation software. We demonstrate the effectiveness of our model by contrasting it with the standard practice approach. To ensure the best possible performance, we continuously monitor the cost, quality, delivery time, and production rate indicators of the various manufacturers and update their performance ranking for current and future orders. Furthermore, using the analytic hierarchy process (AHP) approach, a single performance measure based on the four indicators is developed. Implementing the proposed model showed an improvement in the average performance by 51.3%.