Lessons Learned and Practical Solutions for Equipment Health Management in the Chemical Industry

Author:

Smeraldo Simone1,Bendisch Stefan2,Hriskov Hristo2,Haager Sabina2,Ubl Andreas2,Noguera Arnau Serra3,Siemandel Bastian2,Morgenstern Thomas2,Warter Philipp1,Busboom Axel1,Prandini Maria4

Affiliation:

1. Munich University of Applied Sciences,Department of Engineering and Management,Munich,Germany

2. Equipment Health Center, Linde Gas,Pullach,Germany

3. Linde Gas,Department of Energy & Decarbonization EMEA,Pullach,Germany

4. Information and Bioengineering, Politecnico di Milano,Department of Electronics,Milan,Italy

Funder

Ministry of Economic Affairs

Publisher

IEEE

Reference19 articles.

1. Condition based maintenance: Theory, methodology, & application;Gillespie

2. Industrial automation equipment and systems – Predictive maintenance,2022

3. A survey of predictive maintenance: Systems, purposes and approaches;Ran,2019

4. Overview on hybrid approaches to fault detection and diagnosis: Combining data-driven, physics-based and knowledge-based models

5. Hybrid Data-Driven and Knowledge-Based Predictive Maintenance Framework in the Context of Industry 4.0

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