Optimization of reliability allocation strategies through use of genetic algorithms

Conference · Thu Aug 01 04:00:00 EDT 1996

OSTI ID:281882

Campbell, J E; Painton, L A

This paper examines a novel optimization technique called genetic algorithms and its application to the optimization of reliability allocation strategies. Reliability allocation should occur in the initial stages of design, when the objective is to determine an optimal breakdown or allocation of reliability to certain components or subassemblies in order to meet system specifications. The reliability allocation optimization is applied to the design of a cluster tool, a highly complex piece of equipment used in semiconductor manufacturing. The problem formulation is presented, including decision variables, performance measures and constraints, and genetic algorithm parameters. Piecewise ``effort curves`` specifying the amount of effort required to achieve a certain level of reliability for each component of subassembly are defined. The genetic algorithm evolves or picks those combinations of ``effort`` or reliability levels for each component which optimize the objective of maximizing Mean Time Between Failures while staying within a budget. The results show that the genetic algorithm is very efficient at finding a set of robust solutions. A time history of the optimization is presented, along with histograms or the solution space fitness, MTBF, and cost for comparative purposes.

• Research Organization: Sandia National Labs., Albuquerque, NM (United States)
• Sponsoring Organization: USDOE, Washington, DC (United States)
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 281882
• Report Number(s): SAND--96-1998C; CONF-9609208--1; ON: DE96013823
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
ALGORITHMS
DESIGN
FAILURES
NONLINEAR PROGRAMMING
NUMERICAL SOLUTION
OPTIMIZATION
RELIABILITY