A Unified Framework and Platform for Designing of Cloud-Based Machine Health Monitoring and Manufacturing Systems

Abstract

Cloud computing has brought about new service models and research opportunities in the manufacturing and service indus-tries with advantages in ubiquitous accessibility, convenient scal-ability, and mobility. With the emerging industrial big data prompted by the advent of the internet of things and the wide implementation of sensor networks, the cloud computing para-digm can be utilized as a hosting platform for autonomous data mining and cognitive learning algorithms. For machine health monitoring and prognostics, we investigate the challenges imposed by industrial big data such as heterogeneous data format and complex machine working conditions and further propose a systematically designed framework as a guideline for implement-ing cloud-based machine health prognostics. Specifically, to ensure the effectiveness and adaptability of the cloud platform for machines under complex working conditions, two key design methodologies are presented which include the standardized fea-ture extraction scheme and an adaptive prognostics algorithm. The proposed strategy is further demonstrated using a case study of machining processes. [DOI: 10.1115/1.4030669]

Cyber physical systems for predictive production systems

“…In fleet-sourced modeling, by taking advantage of similar assets, algorithms will become more reliable and robust for equipment health monitoring. In the time dimension, cyber level algorithms also need to be more adaptive to accommodate changed contexts and add robustness [29].…”

Post-prognostics decision in cyber-physical systems

“…Cloud computing can provide a powerful, secure and easy way to storage massive data and processing infrastructure to perform both online and offline analysis and mining of the heterogeneous sensor data streams [25]. In cloud computing distributed resources are encapsulated into cloud services, SaaS (Software as a Service), PaaS (Platform as a Service) and IaaS (Infrastructure as a Service) [23].…”

Lease-Oriented Opportunistic Maintenance for Multi-Unit Leased Systems Under Product-Service Paradigm

“…Normally, two types of maintenance actions, corrective maintenance (CM) and PM, are performed to maintain the upkeep of the leased system [2][3][4][5]. Corrective maintenance typically takes the form of minimal repair actions to bring back a failed machine to 1 its operational state without changing its failure rate.…”