Mould wear-out prediction in the plastic injection moulding industry: a case study
Author:
Affiliation:
1. Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
2. Department of Business Administration, Technology and Social Sciences, Luleå University of Technology, Luleå, Sweden
Funder
Manufacturing Academy of Denmark
Publisher
Informa UK Limited
Subject
Electrical and Electronic Engineering,Computer Science Applications,Mechanical Engineering,Aerospace Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/0951192X.2020.1829062
Reference42 articles.
1. Survey of State-of-the-Art Mixed Data Clustering Algorithms
2. An overview of time-based and condition-based maintenance in industrial application
3. The use of Digital Twin for predictive maintenance in manufacturing
4. On the use of machine learning methods to predict component reliability from data-driven industrial case studies
5. Cost-effective condition-based maintenance using markov decision processes
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