A cloud-based cyber-physical system for adaptive shop-floor scheduling and condition-based maintenance. (April 2018)

• Record Type: Journal Article
• Authors: Mourtzis, Dimitris; Vlachou, Ekaterini
• Is Part Of: Journal of manufacturing systems. Volume 47(2018)
• Page Start: 179
• Page End: 198
• Publication Date: 2018-04
• Subjects: Cyber-physical system -- Cloud manufacturing -- Industry 4.0 -- Adaptive scheduling -- Condition-based maintenance; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2018.05.008
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: The paper presents a cyber-physical system for adaptive scheduling and condition-based maintenance. A reliable, inexpensive and reconfigurable monitoring system which captures and delivers meaningful information. The proposed work support industrial communication protocols (OPC-UA standard) to efficiently integrate with other systems. The captured data is utilized to effectively identify the status of the machine tools and calculate important KPIs. Abstract: Manufacturing, through the Industry 4.0 concept, is moving to the next phase; that of digitalization. Industry 4.0 enables the transition of traditional manufacturing systems to modern digitalized ones, generating significant economic opportunities by reshaping of industry. This procedure requires high-performance processes and flexible production systems. The adoption of the Internet of Things (IoT) in manufacturing will enable effective and adaptive planning and control of production systems. Towards that end, the proposed work presents a cloud-based cyber-physical system for adaptive shop-floor scheduling and condition-based maintenance. The proposed system demonstrated that it is possible to deploy a cost-effective and reliable real-time data collection, processing, and analysis from the shop floor. It also demonstrates that such collected data can be used in an adaptive decision making system, which includes a multi-criteria decision-making algorithm and a condition-based maintenance strategy aiming to improve factory performances when compared to traditional approaches. The proposed system consists of different modules (monitoring, adaptive scheduling, condition-based maintenance) interconnected through the cloud-based platform, enabled by communication protocols under the Industry 4.0 and IoT paradigms. The proposed system is applied and validated in a real-case study from a high-precision mold-making industry.