Abstract
Industry 4.0 is the current trend in the technologies used in exchange of data in manufacturing. Product-service system is a concept that provides self-aware and self-learning machines, and consequently improve overall performance and maintenance management. Companies continually strive to increase production, but in recent years, the effects of this effort have demonstrated that provision of products alone with less resilient technology-enabled service industry is insufficient to remain competitive. The importance of leveraging flexibility and capabilities offered by cloud computing is inevitable, but adapting prognostics and health management algorithms to efficiently implement current data management technologies was research and develop in this study. In this paper, we present an integrated product-service system as a potential concept from a life-cycle perspective to reduce disruption, costs and associated services such as autonomous maintenance, through exchange of data to understand equipment degradation using sensors application, to aid timely services intervention for manufacturing processes transformation. The results is the knowledge base servitude backed by machine clusters generated data for different working conditions to improve operational efficiency using Cloud IoT to connect, process, store, and analyse data on the dashboard, locally and in the cloud for future health assessment.
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