Abstract
Traditionally, In order to predict impending failures and mitigate downtime in their manufacturing facilities, we have to combine many techniques, both quantitative and qualitative, such as smart sensors, high-end intelligent equipment, smart networks, Internet of Thing (IOT), Artificial Intelligence (AI), business analysis decision-making and Internet of service IOS. Based on Industry 4.0 concept, Cognitive Maintenance (CM) or Intelligent Predictive Maintenance (IPdM) systems, which uses intelligent data analysis and decision making techniques, offers the maintenance professionals in high-end equipment the potential to optimize maintenance tasks in real time, maximizing the useful life of their equipment and manufacturing assets while still avoiding disruption to operations. In this paper, we will present the impact of CM to high-end equipment, the framework of Cognitive Maintenance (CM) system and a case study. Some lessons learned from the implementation of CM system in industry are discussed.
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Wang, Y., Wang, K., Dai, G. (2019). Cognitive Maintenance for High-End Equipment and Manufacturing. In: Wang, K., Wang, Y., Strandhagen, J., Yu, T. (eds) Advanced Manufacturing and Automation VIII. IWAMA 2018. Lecture Notes in Electrical Engineering, vol 484. Springer, Singapore. https://doi.org/10.1007/978-981-13-2375-1_49
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DOI: https://doi.org/10.1007/978-981-13-2375-1_49
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