• Corpus ID: 6669549

Recent Advances and Trends of Cyber-Physical Systems and Big Data Analytics in Industrial Informatics

@inproceedings{Lee2014RecentAA,
  title={Recent Advances and Trends of Cyber-Physical Systems and Big Data Analytics in Industrial Informatics},
  author={J. Lee and Behrad Bagheri and Hung-An Kao},
  year={2014}
}
In today’s competitive business environment, companies are facing challenges in dealing with big data issues for rapid decision making for improved productivity. Many manufacturing systems are not ready to manage big data due to the lack of smart analytics tools. Germany is leading a transformation toward 4th Generation Industrial Revolution (Industry 4.0) based on Cyber-Physical System based manufacturing and service innovation. As more software and embedded intelligence are integrated in… 

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References

SHOWING 1-10 OF 20 REFERENCES

Enterprise Systems: State-of-the-Art and Future Trends

  • Lida Xu
  • Computer Science
    IEEE Transactions on Industrial Informatics
  • 2011
TLDR
The state of the art in the area of enterprise systems as they relate to industrial informatics is surveyed, highlighting formal methods and systems methods crucial for modeling complex enterprise systems, which poses unique challenges.

Systematic Design of Prognostics and Health Management Solutions for Energy Applications

TLDR
The Watchdog Agent® toolbox techniques are applied in a systematic way in each application to address the development of advanced predictive tools for near-continuous uptime of energy generating assets; mobility readiness and safety for next-generation electric vehicles via the Smart Battery Agent; and the application of low-cost, nonintrusive predictive solutions using equipment energy consumption.

A survey of Cyber-Physical Systems

TLDR
The features of CPSs are described, and the research progresses are summarized from different perspectives such as energy control, secure control, transmission and management, control technique, system resource allocation, and model-based software design.

Adaptive calibration for fusion-based cyber-physical systems

TLDR
This article proposes an adaptive system-level calibration approach for a class of CPS systems whose primary objective is to detect events or targets of interest and develops a routing algorithm for fusion-based multihop CPS systems that is robust to communication unreliability and delay.

Fault detection in a network of similar machines using clustering approach

Fault detection, which involves the estimation of the condition, health or degradation of an equipment or a process and a decision logic to determine whether an event that can be considered as a

A similarity-based prognostics approach for Remaining Useful Life estimation of engineered systems

TLDR
This approach is used to tackle the data challenge problem defined by the 2008 PHM Data Challenge Competition, in which, run-to-failure data of an unspecified engineered system are provided and the RUL of a set of test units will be estimated.

Implementing discrete wavelet transform and artificial neural networks for acoustic condition monitoring of gearbox

Introduction Reliability has always been an important aspect in the assessment of industrial products. By development of technology, cost of time-based preventive maintenance increased thus, new

Mahalanobis-Taguchi System as a Multi-Sensor Based Decision Making Prognostics Tool for Centrifugal Pump Failures

TLDR
Overall, the proposed solution provides a reliable multivariate analysis and real-time decision making tool that fuses data from multiple sensors into a single system level performance metric and offers a systematic way to determine the key parameters, thus reducing analysis overhead.