Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/14629
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dc.titleContributions to planning and analysis of accelerated testing
dc.contributor.authorYANG GUIYU
dc.date.accessioned2010-04-08T10:45:09Z
dc.date.available2010-04-08T10:45:09Z
dc.date.issued2005-04-27
dc.identifier.citationYANG GUIYU (2005-04-27). Contributions to planning and analysis of accelerated testing. ScholarBank@NUS Repository.
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/14629
dc.description.abstractWith the prevailing interest in saving time and expense,Accelerated Life Testing (ALT) and/or Accelerated Degradation Testing (ADT) are becoming an integral part of many programs for improving productsa??quality and reliability.However,appropriate analysis of ALT/ADT data and planning of ALT/ADT experiments are still a challenging task in the face of cost and estimation precision considerations.This dissertation first reviews the basic concepts and existing methods related to ALTs/ADTs,and then proposes a new approach to designing Constant Stress ALT (CSALT) by using some measure to quantify the departure from optimal solution values. Employing stochastic processes to model degradation paths,an efficient method is proposed for Step Stress ADT (SSADT) data analysis.A general formulation for planning both non-destructive Constant Stress ADT (CSADT) and non-destructive SSADT is also conceived by considering the trade-off between total cost of testing and the attainable estimate precision.This planning strategy is further extended to destructive-CSADT. Finally,concluding remarks are composed with highlights.
dc.language.isoen
dc.subjectAccelerated Testing, Test Planning, Data Analysis, Stochastic Models, Cost Functions, Precision Constraint
dc.typeThesis
dc.contributor.departmentINDUSTRIAL & SYSTEMS ENGINEERING
dc.contributor.supervisorTANG LOON CHING
dc.contributor.supervisorXIE MIN
dc.description.degreePh.D
dc.description.degreeconferredDOCTOR OF PHILOSOPHY
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Ph.D Theses (Open)

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