Energy-efficient concurrent assessment of industrial robot operation based on association rules in manufacturing

While the manufacturing industry is flourishing, sustainable manufacturing has been highly valued by the world and has gradually become the trend of the manufacturing industry. Because of the high efficiency and high quality operation, the industrial robots (IRs) have been deployed in various industries, and the energy-efficient operation of IRs has become the focus of attention. Among this, the energy-efficient assessment of IRs operation performance can grasp the energy status and the manufacturing capacity during the production process. In addition, there is a close relationship between the production line level and the manufacturing cell level. From the view of manufacturing systems in a job shop, the concurrent assessment of IRs' operation performance will provide the support for the optimization of operation control and scheduling decision making as a whole. This paper proposes an energy-efficient concurrent assessment method for the manufacturing system of IRs based on association rules. A set of concurrent assessment model is established based on the relationship between the IRs production line level and the manufacturing cell level. A mining algorithm is used to mine association rules between the indicators. Furthermore, in order to improve the accuracy of the concurrent assessment, the correlation coefficient based on association rules between the indicators is used to correct the weights. Finally a case study is implemented to demonstrate the feasibility and effectiveness of the proposed method.