Christopher Jaisa, Benjamin Wernera and Diganta Dasb
a US Army Material Systems Analysis Activity
b Center for Advanced Life Cycle Engineering (CALCE), University of Maryland
Reliability prediction methodologies, especially those
centred on Military Handbook (MIL-HDBK) 217 and its
progeny are highly controversial in their application. The use
of reliability predictions in the design and operation of
military applications have been in existence since the 1950's.
Various textbooks, articles, and workshops have provided
insight on the pros and cons of these prediction
methodologies. Recent research shows that these methods
have produced highly inaccurate results when compared to
actual test data for a number of military programs. These
inaccuracies promote poor programmatic and design
decisions, and often lead to reliability problems later in
Major reasons for handbook prediction inaccuracies include but are not limited to:
1) The handbook database cannot keep pace with the rapid advances in the electronic industry.
2) Only a small portion of the overall system failure rate is addressed.
3) Prediction methodologies rely solely on simple heuristics rather than considering sound engineering design principles.
Rather than rely on inaccurate handbook methodologies, a reliability assessment methodology is recommended. The reliability assessment methodology includes utilizing reliability data from comparable systems, historical test data, and leveraging subject-matter-expert input. System developers then apply fault-tree analysis (or similar analyses) to identify weaknesses in the system design. The elements of the fault tree are assessed against well-defined criteria to determine where additional testing and design for reliability efforts are needed. This assessment methodology becomes a tool for reliability engineers, and ultimately program managers, to manage the risk of their reliability program early in the design phase when information is limited.
Keywords: Military Handbook 217, reliability assessment, reliability predictions.
Complete article is available from the publisher and to the CALCE Consortium Members.