Industrial Big Data Analytics and Cyber-physical Systems for Future Maintenance & Service Innovation

By Jay Lee, H. D. Ardakani, Shanhu Yang, B. Bagheri. 2015

367 citations recorded by the source corpus.

Abstract With the rapid advancement of Information and Communication Technologies (ICT) and the integration of advanced analytics into manufacturing, products and services, many industries are facing new opportunities and at the same time challenges of maintaining their competency and market needs. Such integration, which is called Cyber-physical Systems (CPS), is transforming the industry into the next level. CPS facilitates the systematic transformation of massive data into information, which makes the invisible patterns of degradations and inefficiencies visible and yields to optimal decision-making. This paper focuses on existing trends in the development of industrial big data analytics and CPS. Then it briefly discusses a systematic architecture for applying CPS in manufacturing called 5C. The 5C architecture includes necessary steps to fully integrate cyber-physical systems in the manufacturing industry. Finally, a case study for designing smart machines through the 5C CPS architecture is presented.

Subfields: Hardware and Architecture, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/5e0027b1d64fa597964bb021817d19ff3723be72

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Hardware and Architecture

1. Wei Yu
2. Baicun Wang
3. Lian Duan
4. Yanhong Zhou
5. Ji Zhou
6. JiYuan Zang
7. Lida Xu

In Industrial and Manufacturing Engineering

1. Jiewu Leng
2. Baicun Wang
3. John Krogstie
4. Lian Duan
5. Ding Zhang
6. Yanhong Zhou
7. Ji Zhou
8. Qiang Liu

Citations in the corpus

• The Role of Big Data Analytics in Industrial Internet of Things (2019, neutral): “CPS and IoT devices act as the backbone of IIoT systems and thus generate massive amount of raw data streams, which result in big data [44].”
• Human–Cyber–Physical Systems (HCPSs) in the Context of New-Generation Intelligent Manufacturing (2019, background): “Intelligent services include user-centric services that are provided throughout the life-cycle of products via digital, networked, and intelligent technologies [63,74,78,79]; such services include customization and remote operation and maintenance, which extend to service-oriented manufacturing and ”
• A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective (2018, background): “For example, continuous monitoring on the condition and health status of large-scale industrial systems will generate a significant volume data [106], [107].”
• Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment (2019, positive): “…be leveraged to identify bottlenecks in supply chains (G. Wang et al., 2016), predict maintenance times for equipment with much greater accuracy (J. Lee, Ardakani, Yang, & Bagheri, 2015), and forecast demand and sales to allow better inventory management and production planning (Lim, Alpan, &…”
• A Digital Twin-Based Approach for Designing and Multi-Objective Optimization of Hollow Glass Production Line (2017, background): “The first challenge is to build a digital twin model combining product lifecycle management, manufacturing execution system, and operations management system [40], [41].”
• Big data for cyber physical systems in industry 4.0: a survey (2019, background): “Lee et al. (2015b) proposed a 5-layer CPS structure from the initial data acquisition, conversion, and analysis to intervention and self-adaptation.”