Proposing a Training Model on Energy Management of Compressed Air Systems with Artificial Intelligence of Things

Abstract

Technology 4.0 in the industry focuses on effective energy saving. There is an increase in the need for industrial worker training, especially in compressed air systems, air kept under more significant pressure than atmospheric pressure. It is an important medium for the transfer of energy in industrial processes. However, the new technology of energy management systems to enhance performance has yet to be widespread. Owing to the learning material for training is expensive. It is also not possible to simulate the operation of a comprehensive system. The employees lack an understanding of the big picture, causing problems in learning and lacking practical skills. Especially new employees may need more knowledge and experience and have operation errors or problem-solving skills. In this study, we proposed a training model consisting of a compressed air systems training kit based on the Artificial Intelligence of Things (AIoT), and the energy-saving scenarios consist of 1) controlling the compressed air pressure fed to the air cylinder while being subjected to loads of different sizes. 2) controlling the compressed air pressure supplied to the air cylinder while operating the air cylinder without load. 3) controlling the compressed air supplied to the machine while it is stopped. In addition, we use an outcome-based approach to drive training activities. The results show that the training model can simulate the process of energy management systems of compressed air systems and show it on the dashboard. It can be implemented in employee or engineer practical training in the future.