| Title | CI-MCMS: Computational Intelligence Based Machine Condition Monitoring System |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Bahel, Vedant, Mishra, Arunesh |
| Conference Name | 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE) |
| Keywords | composability, compositionality, Computational Intelligence, Computer architecture, condition monitoring, Hydraulic System, Industries, Industry 4.0, Machine Condition Monitoring, Neural networks, Production, pubcrawl, Sensor systems, Technological innovation |
| Abstract | Earlier around in year 1880's, Industry 2.0 marked as change to the society caused by the invention of electricity. In today's era, artificial intelligence plays a crucial role in defining the period of Industry 4.0. In this research study, we have presented Computational Intelligence based Machine Condition Monitoring system architecture for determination of developing faults in industrial machines. The goal is to increase efficiency of machines and reduce the cost. The architecture is fusion of machine sensitive sensors, cloud computing, artificial intelligence and databases, to develop an autonomous fault diagnostic system. To explain CI-MCMs, we have used neural networks on sensor data obtained from hydraulic system. The results obtained by neural network were compared with those obtained from traditional methods. |
| DOI | 10.1109/ICCIKE51210.2021.9410744 |
| Citation Key | bahel_ci-mcms_2021 |
CI-MCMS: Computational Intelligence Based Machine Condition Monitoring System