From Prediction to Prescription: A Framework for Prescriptive Maintenance

DOI

10.2991/978-94-6239-813-9_20How to use a DOI?

Keywords

Predictive Maintenance; Prescriptive Maintenance; Optimisation

ABSTRACT

Industries need a maintenance strategy that not only predicts failure but also optimises machine operating conditions to maximise the lifespan. This work addresses this by introducing a new prescriptive maintenance strategy. This framework provides actionable recommendations to optimise the machine’s useful lifespan. It uses an ensemble of bagged decision trees for a predictive model. Next, diverse new mathematical functions are derived to construct an array of operational settings that realistically account for all possible operational profiles. Using an array, the model can predict a machine’s remaining life. Finally, it prescribes operating conditions that maximise machine lifespan, providing decision-makers with guidance for maintenance.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ruaridh McNair
AU  - Soham Jain
AU  - Amit Kumar Jain
PY  - 2026
DA  - 2026/10/29
TI  - From Prediction to Prescription: A Framework for Prescriptive Maintenance
BT  - Proceedings of the  Global Symposium on Adaptive Manufacturing (GSAM 2026)
PB  - Atlantis Press
SP  - 58
EP  - 60
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6239-813-9_20
DO  - 10.2991/978-94-6239-813-9_20
ID  - McNair2026
ER  -