Author
Listed:
- Will Wascom
- Yili Hong
- Yisha Xiang
Abstract
Reliability analysis of repairable systems such as heating, ventilation, and air conditioning (HVAC) equipment must account for multiple failure modes and the reality of imperfect repairs. Traditional models like the non-homogeneous Poisson process (NHPP) or the classical renewal process assume extreme repair effects (minimal or perfect), which can misrepresent systems where maintenance actions return the equipment to an intermediate condition (neither “as good as new†nor “as bad as old†). To address this gap, we apply the Trend Renewal Process (TRP) model to capture the failure dynamics of HVAC systems with multiple failure modes (refrigerant leak, electrical, and mechanical failures), as a case study. The TRP generalizes conventional models by combining a time-dependent trend component with a renewal distribution; specifically, we develop a Weibull–Weibull TRP formulation and derive its conditional intensity function for each failure type. The model parameters for each failure mode are estimated through maximum likelihood estimation (MLE) using real-world failure data from NASA’s Rocket Propulsion Test Program HVAC systems. The results demonstrate that HVAC systems exhibit increasing failure rates and partial repair effectiveness, characterized by parameters indicating moderate aging trends and imperfect renewals. The Weibull–Weibull TRP model effectively captured the variability and dynamics of different HVAC failure modes, providing a realistic framework for reliability prediction and maintenance optimization. Despite limitations due to data availability and categorization accuracy, this approach is robust, highlighting opportunities for further refinement with more comprehensive datasets. The observed system-level failure stream aggregates heterogeneous component processes (a superposition). We therefore use the TRP as a parsimonious approximation rather than an exact superposition model. Adequacy is evaluated against a minimal-repair NHPP baseline via a likelihood-ratio test and residual diagnostics.
Suggested Citation
Will Wascom & Yili Hong & Yisha Xiang, 2026.
"Reliability analysis of heating ventilation and air conditioning systems using the trend renewal process,"
Journal of Risk and Reliability, , vol. 240(2), pages 438-451, April.
Handle:
RePEc:sae:risrel:v:240:y:2026:i:2:p:438-451
DOI: 10.1177/1748006X251404112
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:risrel:v:240:y:2026:i:2:p:438-451. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.