Resource efficiency enhancement in sheet metal cutting industrial networks through cloud manufacturing

Abstract

In modern manufacturing industry, resource efficiency is negatively affected by the high fluctuations of demands within the global market. In this work, an intelligent cloud manufacturing platform is proposed to increase resource efficiency, productivity, and utilization rates in a smart manufacturing network by dynamically matching manufacturing services offers and requests through the broad sharing and on-demand delivery of distributed computational, software, digital, and physical manufacturing resources. The cloud platform is developed with particular reference to the sheet metal cutting sector and includes several modules. A database module is employed for users data input and storage. An intelligent assessment and optimization module performs the functional and geometrical assessments of the sheet metal cutting instances entered by customers and suppliers and makes use of a genetic algorithm to optimize the manufacturing solutions with specific attention to the surface utilization rate, as key performance index of resource efficiency. A decision-making module supports the supplier in the selection of the best production strategy and the customer in the evaluation and comparison of the best manufacturing solutions ranked according to the preferred criteria. To demonstrate the implementation of the proposed cloud manufacturing platform in a manufacturing network scenario, a case study including several customer and supplier instances is presented, showing the multiple manufacturing solutions proposed by the platform and the advantages in terms of industrial resource efficiency improvement.