PHM Integration with Maintenance and Inventory Management Systems (Preprint)
Abstract
Prognostic techniques are intricately tied to the physics of incipient-fault-to-failure progression, and hence most prognostic research has focused on developing techniques for a range of components such as rotating machinery parts. The research and development of such techniques has relied on the theories of material science, structural mechanics, domain expertise, as well as empirical studies such as accelerated run-to-failure testing. Even after prognostic models have been developed and operationally validated for various components of a system, the challenge remains how prognostic assessments from individual components of a system (such as the aircraft engine) should be used to make maintenance and inventory management decisions. In this paper, we describe our research where the primary focus is to bridge the gap between the individual component prognostics and the system-level reasoning required to support maintenance and inventory management decisions. The research involves integration of component health assessment and an information fusion mechanism that operates in conjunction with a higher-level reasoning engine which utilizes system level structural and functional dependencies to generate a system availability analysis that leads directly actionable decision-making tasks for the inventory and maintenance management systems. The inventory management decision systems involve predicting spares requirements and when integrated with remote health monitoring and intelligent diagnostics and prognostics, can assess different spares allocation schemes and optimize inventory management by maximizing system availability within budget constraints.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 2006
- Accession Number
- ADA466108
Entities
People
- Fang Tu
- Gautam Biswas
- Jianhui Luo
- Kelly R. Navarra
- Link Jaw
- Sankaran Mahadevan
- Sudipto Ghoshal
Organizations
- Qualtech Systems Incorporation (United States)