Impact of Nonoperating Periods on Equipment Reliability

Abstract

The objective of this study was to develop a procedure to predict the quantitative effects of nonoperating periods on electronic equipment reliability. A series of nonoperating failure rate prediction models were developed at the component level. The models are capable of evaluating component nonoperating failure rate for any anticipated environment with the exception of a satellite environment. The proposed nonoperating failure rate prediction methodology is intended to provide the ability to predict the component nonoperating failure rate and reliability as a function of the characteristics of the devices, technology employed in producing the device, and external factors such as environmental stresses which have a significant effect on device nonoperating reliability. The prediction methodology is presented in a form compatible with MIL-HDBK-217 as an Appendix to the technical report. Additional keywords: Dormancy; Power on off cycling; Tables(Data); Data acquisition; Mathematical models; Microcircuits; Discrete semiconductors; Resistors; Capacitors; Inductive devices; Lasers; Tubes; Mechanical/electromechanical devices; and Circuit interconnectors.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1985
Accession Number
ADA158843

Entities

People

  • David W. Coit
  • Mary G. Priore

Organizations

  • IIT Research Institute

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Computational Science
  • Databases
  • Electronic Components
  • Electronics Industry
  • Electronics Laboratories
  • Factor Analysis
  • Failure Mode And Effect Analysis
  • Fighter Aircraft
  • Information Science
  • Klystrons
  • Laser Target Designators
  • Modules (Electronics)
  • Regression Analysis
  • Semiconductor Devices
  • Semiconductors
  • Servomechanisms
  • Spacecraft

Fields of Study

  • Engineering

Readers

  • Integrated Circuit Design and Technology.
  • Regression Analysis.
  • Software Engineering

Technology Areas

  • Directed Energy
  • Microelectronics
  • Space