Empirical risk assessment of maintenance costs under full-service contracts
Deprez, Laurens Antonio, Katrien Boute, Robert
Deprez, Laurens
Antonio, Katrien
Boute, Robert
Citations
Altmetric:
Publication Type
Journal article with impact factor
Editor
Supervisor
Publication Year
2023
Journal
European Journal of Operational Research
Book
Publication Volume
304
Publication Issue
2
Publication Begin page
476
Publication End page
493
Publication Number of pages
Collections
Abstract
We provide a data-driven framework to conduct a risk assessment, including data pre-processing, exploration, and statistical modeling, on a portfolio of full-service maintenance contracts. These contracts cover all maintenance-related costs for a fixed, upfront fee during a predetermined horizon. Charging each contract a price proportional to its risk prevents adverse selection by incentivizing low risk (i.e., maintenance-light) profiles to not renege on their agreements. We borrow techniques from non-life insurance pricing and tailor them to the setting of maintenance contracts to assess the risk and estimate the expected maintenance costs under a full-service contract. We apply the framework on a portfolio of about full-service contracts of industrial equipment and show how a data-driven analysis based on contract and machine characteristics, or risk factors, supports a differentiated, risk-based break-even tariff plan. We employ generalized additive models (GAMs) to predict the risk factors’ impact on the frequency (number of) and severity (cost) of maintenance interventions. GAMs are interpretable yet flexible statistical models that capture the effect of both continuous and categorical risk factors. Our predictive models quantify the impact of the contract and machine type, service history, and machine running hours on the contract cost. We additionally utilize the predictive cost distributions of our models to augment the break-even price with the appropriate risk margins to further protect against the inherently stochastic nature of the maintenance costs. The framework shows how maintenance intervention data can set up a differentiated tariff plan.
Research Projects
Organizational Units
Journal Issue
Keywords
Maintenance, Risk Assessment, Empirical Analysis, Predictive Analytics, Frequency-Severity Modeling