Optimum Accelerated Life Testing Models With Time-varying Stresses
eBook - ePub

Optimum Accelerated Life Testing Models With Time-varying Stresses

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  1. 444 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Optimum Accelerated Life Testing Models With Time-varying Stresses

0

About this book

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Today's manufacturers are under tremendous pressure to develop new technological and high reliability products in record time. This has motivated reliability engineers to evaluate the reliabilities of such products. Reliability testing under accelerated environment — accelerated life testing helps to meet this challenge.

This comprehensive and must-have edition provides a broad coverage of the optimal design of Accelerated Life Test Plans under time-varying stress loadings. It also focuses on the formulation of Accelerated Life Test Sampling Plans (ALTSPs) which integrate accelerated life tests with quality control technique of acceptance sampling plans. These plans help to determine optimal experimental variables such as appropriate stress levels, optimal allocation at each stress levels, stress change points, etc, depending on the stress loading scheme. ALTSPs determine optimal plans such that the producers' and consumers' risks are safeguarded.

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Yes, you can access Optimum Accelerated Life Testing Models With Time-varying Stresses by Preeti Wanti Srivastava in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Industrial Engineering. We have over one million books available in our catalogue for you to explore.

CHAPTER 1

DIFFERENT ASPECTS OF ALT MODELS

If your contribution has been vital there will always be somebody to pick up where you left off, and that will be your claim to immortality.
Walter Gropius

1.1INTRODUCTION

Reliability of a unit is its ability to perform required operations successfully. Quantitatively it is the probability that the unit will perform satisfactorily at least for a specified period of time without a major breakdown. The unit may refer to a manufactured product or its components, manufacturing and assembly systems, mechanical, electrical, and electronic systems. Reliability is related to quality of performance of a unit and signifies dependability. The better the performance, higher the reliability and greater the satisfaction to the manufacturer as well as the consumer. It is an important consideration in planning, design and management of such units.
Modern products have become increasingly more sophisticated in the light of rapid technological advances. Very detailed and complex equipment has been researched, designed, developed, and implemented for space exploration, military applications, and commercial uses. In general, each piece of equipment is composed of numerous elementary components and/or subsystems that work as a unit either to achieve specific objectives or to perform a variety of functions. As a consequence, increasing attention has been focused on evaluation of whether a given device successfully performs its intended function. Studies of operating data for pieces of equipment are used in these evaluations. The requirements of higher-reliability have increased the need for more up-front testing of materials, components, and systems. This is commensurate with the generally accepted modern quality philosophy of producing high-reliability products by improving the design and manufacturing processes, and moving away from reliance on inspections to achieve high reliability.
Many modern products are high-reliability products designed to operate without failure for years. Thus, few units will fail or degrade in a test at normal use conditions. For example, during the design and construction of a communications satellite, there may be only six months available to test components that are expected to be in service for 15 or 20 years. For this reason, accelerated tests (ATs) are used widely in manufacturing industries, particularly to obtain timely information on the reliability of products, components, and materials. Generally, information from tests at high levels of stress (usage rate, temperature, voltage, or pressure) is extrapolated, through a physically reasonable model, to obtain estimates of life or long-term performance at normal level of stress. In some cases, stress is increased or otherwise changed during the course of a test. AT results are used in the design-for-reliability processes to assess or demonstrate component and subsystem reliability, certify components, detect failure modes, compare different manufacturers, and so forth. ATs have become increasingly important because of rapidly changing technologies, more complicated products with more components, and higher customer expectations for better reliability.
ATs comprise
(i) Accelerated Life Tests (ALTs) and
(ii) Accelerated Degradation Tests (ADTs).

1.1.1Difference between ALT and ADT

ALT introduced by Chernoff (1962) and Bessler, Chernoff, and Marshall (1962) is undertaken to shorten the test duration and save cost of testing by subjecting all or some of the test units to a more severe environment (increased or decreased stress levels) than the normal operating environment. The test data so obtained at accelerated conditions are extrapolated by means of an appropriate model to estimate the characteristics of life distribution at design condition. In ALT, physical failures are observed during the experiment, i.e., when a test unit stops working it is said to have failed. For example, when the resistance of a resistor deviates too much from its nominal value, causing the oscillator in an electric circuit to stop oscillating or when an incandescent light bulb burns out. Such failures are called hard failures, i.e., catastrophic failures.
However, for some highly reliable products even accelerated life testing yield little failure data of units in a feasible amount of time. In such cases, Accelerated Degradation Testing is carried out. In an ADT, a performance characteristic of the product whose degradation over time can be related to reliability, is measured, and the degradation data obtained at higher stress level is extrapolated by means of an appropriate model for performance degradation to a certain normal stress level to obtain reliability information about the product. Here, failure is defined in terms of performance characteristic of the product exceeding its critical (threshold) value. For example, decreasing light output from a fluorescent light bulb where in failure may be defined as performance characteristic exceeding a specified level of degradation such as 60% of initial output. Such a failure is called a soft failure (Tseng, Hamada, and Chiao, 1995), i.e., degradation of product performance to an unacceptable level. Other examples in which ADTs can be applied include Light Emitting Diode (LED), mechanical products, chemical processes, and materials where the rate of degradation is usually governed by mechanisms such as fatigue, diffusion, oxidation, and shock. For instance, bearings used in automobiles wear mechanically until the loss of their function; batteries with a limited amount of chemicals to react finally run down; materials in aeronautical pro...

Table of contents

  1. Cover Page
  2. Title
  3. Copyright
  4. Contents
  5. Preface
  6. Acronyms
  7. List of Figures
  8. List of Tables
  9. About the Author
  10. 1. Different Aspects of ALT Models
  11. 2. Optimum Step-Stress Accelerated Life Test Models
  12. 3. Optimum Step-Stress Partially Accelerated Life Test Plans with Type-I and Type-II Censoring
  13. 4. Optimum Ramp-Stress Fully Accelerated Life Test Plans Under Type-I Censoring
  14. 5. Optimum Fully Accelerated Life Test Plans with Modified Stress Loading Schemes under Type-I Censoring
  15. 6. Optimum Time-Censored Step-Stress Fully ALT with Competing Risks For Failure
  16. 7. Product Control and Accelerated Life Testing
  17. 8. Optimum Time-Censored Ramp-Stress ALTSPs
  18. 9. Optimum Time-Censored Step-Stress PALTSP with Warranty Using Tampered Failure Rate Model
  19. 10. Optimum Time-Censored Step-Stress PALTSP with Competing Causes of Failure Using Tampered Failure Rate Model
  20. Appendix A
  21. Appendix B
  22. Appendix C
  23. Appendix D
  24. References
  25. Index