RELIABILITY AND MODELING OF SYSTEMS INTEGRATED WITH FIRMWARE AND HARDWARE

2005 ◽  
Vol 12 (03) ◽  
pp. 227-239 ◽  
Author(s):  
TIELING ZHANG ◽  
MIN XIE ◽  
LOON CHING TANG ◽  
SZU HUI NG
Keyword(s):  
Weibull Distribution ◽  
Failure Rate ◽  
Software Reliability ◽  
Integrated System ◽  
System Failure ◽  
Application Software ◽  
Critical Systems ◽  
Exponentiated Weibull Distribution ◽  
Exponentiated Weibull ◽  
Safety Critical Systems

Firmware is embedded software in hardware devices and they play important role for many critical systems' function. Firmware failure rate in operation should be quite lower than the application software which is operating on it. Most of the study on software reliability deals with systems during development, and it is also important to study the integrated system during operation. Complex systems usually have a bathtub-shaped failure rate over the lifecycle of the product. This paper discusses the parametric analysis of model given by Haupt and Schäbe (1992), exponentiated Weibull distribution and models generated from Pareto and Weibull distribution, as well as their possible application to modeling firmware system failure. In addition, the Safety Integrity Levels (SIL) stipulated in IEC 61508 are taken into account in the modeling since the safety-critical systems in general are firmware-dominated.

scholarly journals Design of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Srinivasa Rao Gadde ◽  
Arnold K. Fulment ◽  
Josephat K. Peter
Keyword(s):  
Weibull Distribution ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Sampling Plan ◽  
Exponentiated Weibull Distribution ◽  
Exponentiated Weibull ◽  
Single Sampling Plan ◽  
Truncated Life Test ◽  
Dependent State

The proposed sampling plan in this article is referred to as multiple dependent state (MDS) sampling plans, for rejecting a lot based on properties of the current and preceding lot sampled. The median life of the product for the proposed sampling plan is assured based on a time-truncated life test, when a lifetime of the product follows exponentiated Weibull distribution (EWD). For the proposed plan, optimal parameters such as the number of preceding lots required for deciding whether to accept or reject the current lot, sample size, and rejection and acceptance numbers are obtained by the approach of two points on the operating characteristic curve (OC curve). Tables are constructed for various combinations of consumer and producer’s risks for various shape parameters. The proposed MDS sampling plan for EWD is demonstrated using the coronavirus (COVID-19) outbreak in China. The performance of the proposed sampling plan is compared with the existing single-sampling plan (SSP) when the quality of the product follows EWD.

Prognostics and Health Management of Mechanical Systems

2013 ◽  
Vol 694-697 ◽  
pp. 872-875
Author(s):  
Jiang Chang ◽  
Fang Wei
Keyword(s):  
Health Management ◽  
Mechanical Systems ◽  
Smart Sensors ◽  
Electronic Systems ◽  
System Failure ◽  
Prognostics And Health Management ◽  
Critical Systems ◽  
Embedded Sensing ◽  
Safety Critical Systems ◽  
Self Test

Reliability is an important issue to consider for mechanical systems. The state of art is regular checkup and maintenance to ensure normal operations. This is not good enough for safety-critical systems like gearboxes in vehicles and helicopters because the risk of system failure still exists, let alone the manpower and monetary cost required. Prognostics and health management (PHM) was first raised by the U.S. armed force, which should ideally be able to predict faults and schedule maintenance only when necessary by monitoring the system condition. In this paper, inspired by the idea of Built-In Self Test (BIST) in electronic systems, we propose a novel framework to fulfill the task of prognostics and health management with a set of smart sensors, consisting of embedded sensing elements, wireless communication modules and micro-controllers. Both the significance and challenges of the framework are discussed.

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