A. H. S. Garmabaki

A reliability decision framework for multiple repairable units

In practice, the analyst is often dealing with multiple repairable units, installed in different positions or functioning under different operating conditions, and maintained by different disciplin ...

Multi up-gradation software reliability growth model with faults of different severity

In todays environment of global competition where each company is trying to prove itself better than its competitors, software company have to continually do up-gradation or add-ons in their software to survive in the market. Each succeeding up-gradation offers some innovative performance enhancement or some new functionality etc distinguishing itself from the past release. But at the same time the amount of risk involved in up-gradation/add-ons of software with regard to introducing new faults or increasing the fault number in the software is also formidable. This model categorizes faults in two types: Type-1 and Type-2 (simple fault, hard fault namely) with respect to time which they take for isolation and removal after their observation. In this paper, we propose new model and new concept of multi release software development environment. The model developed is validated on real data sets for software which has been released in the market with new features.

Reliability Modelling of Multiple Repairable Units

This paper proposes a model selection framework for analysing the failure data of multiple repairable units when they are working in different operational and environmental conditions. The paper pr ...

MODELING TWO-DIMENSIONAL SOFTWARE MULTI-UPGRADATION AND RELATED RELEASE PROBLEM (A MULTI-ATTRIBUTE UTILITY APPROACH)

The todays fast-paced, competitive environment in the field of Science and Technology, demands highly reliable hardware and software in order to achieve new breakthroughs in quality and productivity. In this scenario, first release of software products includes enough features and functionality to make it useful for the customers. Later, software companies have to come up with upgradation or add-ons in their software to survive in the market through a series of releases. Each succeeding upgradation offers some innovative performance or new functionality, distinguishing itself from the past releases. In one-dimensional Software Reliability Growth Models (SRGM) researcher used one factor such as Testing-Time, Testing-Effort or Coverage, etc. but within a two-dimensional SRGM environment, the process depends on two-types of reliability growth factors like Testing-time and Testing-effort. In addition, we also consider the combined effect of bugs encountered during testing of present release and user reported bugs from the operational phase. The model developed in the paper takes into consideration the testing and the operational phase where fault removal phenomenon follows, logistic and Weibull model, respectively. The paper also comprises of formulating an optimal release problem based on Multi-Attribute Utility Theory (MAUT). Lastly, the model validation is done on real dataset of software already released in the market with successive generations.

Modelling diffusion of successive generations of technology: a general framework

In todays market where each company is trying to prove itself better than its competitors, companies have to continually bring new generations of their products so as to survive in the market. Each succeeding generation offers some innovative performance or new functionality, distinguishing itself from the past generation. Based on the behavioural assumptions of diffusion theory, this paper proposes an extension of the Bass diffusion model that separates substitution from switching as well as leapfrogging. We also present a relationship between our model and Norton-Bass model. Empirical implications of the proposed model have been validated on data collected from two industries (semiconductor industry dynamic random access memory shipments of six generations, mainframe industry (USA)). The model describes the growth of these generations quite effectively.

Maintenance Optimization Using Multi-attribute Utility Theory

Several factors such as reliability, availability, and cost may consider in the maintenance modeling. In order to develop an optimal inspection program, it is necessary to consider the simultaneous effect of above factor in the model structure. In addition, for finding the optimal maintenance interval it is necessary to make trade-offs between several factors, which may conflicting each other as well. The study comprises of mathematical formulating an optimal interval problem based on Multi-Attribute Utility Theory (MAUT). The aim of the proposed research is to develop a methodology with supporting tools for determination of optimal inspection in a maintenance planning to assure and preserve a desired level of performance measure such as reliability, availability, risk, etc. For verification and validation purposes, the proposed methodology (analysis approach) and tools (models) will be applied in a real case which given by the literature.

Multi Up-Gradation Reliability Model for Open Source Software

Nowadays, software companies have to continuously do up-gradation or add-ons in their software to survive in the market. This paper presents an effective reliability model for multi release open source software (OSS), which derived based on software lifecycle development process (SDLC) proposed by Jorgensen [1]. Most of OSS reliability models proposed in the literature are based on closed-form methodology and do not consider the properties of OSS in the model structure. The proposed model, incorporate bugs removed from two different phases, namely a pre-commit test and parallel debugging test. Furthermore, the proposed model is based on the assumptions that the overall fault removal of the new release depends on the reported faults from the previous release of the software and on the faults generated due to adding some new functionalities to the existing software system. The parameters of model have been estimated on real software failure dataset with three releases and goodness of fit of values have been calculated. Results show that the proposed model fits the data reasonably well and present better accuracy in comparison with other methods.

Reliability modeling of successive release of software using NHPP

This paper presents an effective reliability model for multi-release open source software (OSS), which derived based on software lifecycle development process (SDLC) proposed by Jørgensen [1]. Most of OSS reliability models do not consider the unique characteristic of OSS in the model. This model, combine bugs removed from pre-commit test and parallel debugging test phases. Furthermore, the proposed model is based on the assumptions that the total number of fault removal of the new release depends on the reported faults from the previous release and on the faults generated due to adding some new adds-on to the existing software system. The parameters of model have been estimated using three releases of the Apache project. In addition, three models in the literature are selected to compare with the proposed model. Comparison indicates that the proposed model is a suitable reliability model that fits the data across all the releases of the Apache project.

Maintainability analysis of equipment using point process models

The maintenance cost can be reduced significantly by applying the maintainability principle in the design and operation phase. An effective maintainability prediction can help the designer to improve performance and safety of equipment. The analysis of historical repair by an affective statistical approach provides essential information for decision-making regarding the planning of operation and maintenance activities of the plant. However, the literature on field repair data is quite scarce and they are not detailed. This paper will try to provide step by step guideline for field repair data using point process models by a case study.

Performance evaluation for maximum likelihood and moment parameter estimation methods on classical two Weibull distribution

The two-parameter Weibull distribution is the most widely used distribution in reliability engineering. Parameter estimation is a key issue to apply the Weibull to practical engineering. This paper aims to compare the performance of the maximum parameter estimation method (MLE) and the moment parameter method. It firstly investigates some mathematical properties such as solution uniqueness, estimators equivariance and the confidence interval, that are important to practice. Later on their performances have been evaluated by using simulation. In the simulation, data sets ranged from extreme small to large have been considered. Weibull distribution with increasing, constant and deceasing failure rate have been chosen in the simulation to ensure the simulations results concrete.