Maintainability

The purpose of this work is to present the proposal of a new algorithm to diagnose
domestic washing machines faults using their sound as standalone parameter. To
achieve this and optimize decision making, artificial neural networks are used in line.
A group of actual washing machines noise samples are obtained, with or without
faults, and by comparing and classifying the training samples the failure patterns are
obtained. Finally, a series of tests are performed with another set of samples to
validate the system. The results show a correct detection and classifying of the faults,
and it can be concluded that the proposed algorithm is strong enough to adequately
diagnose incipient faults in the washing machines models tested.
Keywords: neural networks, washing machines, predictive maintenance, incipient
faults

Software Maintainability is one of the most important quality attributes. To increase quality of a software, to manage software more efficient and to decrease cost of the software, maintainability, maintainability estimation and maintainability evaluation models have been proposed. However, the practical use of these models in software engineering tools and practice remained little due to their limitations or threats to validity. In this paper, results of our Literature Review about maintainability models, maintainability metrics and maintainability estimation are presented. Aim of this paper is providing a baseline for further searches and serving the needs of developers and customers.

Software defects often lead to bugs, runtime errors and software maintenance difficulties. They should be systematically prevented, found, removed or fixed all along the software lifecycle. However, detecting and fixing these defects is still, to some extent, a difficult, time-consuming and manual process. In this paper, we propose a two-step automated approach to detect and then to correct various types of maintainability defects in source code. Using Genetic Programming, our approach allows automatic generation of rules to detect defects, thus relieving the designer from a fastidious manual rule definition task. Then, we correct the detected defects while minimizing the correction effort. A correction solution is defined as the combination of refactoring operations that should maximize as much as possible the number of corrected defects with minimal code modification effort. We use the Non-dominated Sorting Genetic Algorithm (NSGA-II) to find the best compromise. For six open source projects, we succeeded in detecting the majority of known defects, and the proposed corrections fixed most of them with minimal effort.

In mobile communications age, environment changes rapidly, the requirements change is the software project must face challenge. Able to overcome the impact of requirements change, software development risk can be effectively decreased. In order to reduce software requirements change risk, the paper investigates the major software development models and recommends the adaptable requirements change
software development. Agile development applied the Iterative and Incremental Development (IID) approach, focuses on workable software and client communication. In software development, agile development is a very suitable approach to handle the requirements change. However, agile development
maintenance existed many defects that include development documents control, user story inspection and CM system. The maintenance defects of agile development should be improved. Analysing and collecting the critical quality factors of agile development maintainability, in this paper proposes the Agile Development Maintainability Measurement (ADMM) model. Based on ADMM model, the Agile Development Maintainability Enhancement (ADME) procedure can be defined and deployed for reducing the risk of requirements change.

Maintainability assessment is an essential aspect of software development. However it is a cumbersome process. Many methodologies are proposed so far to estimate maintainability of software. Artificial neural network is one of the sophisticated techniques which have a great predictive capability. This paper investigated the application of neural networks to predict maintainability of the software using object-oriented metrics. In this study maintenance effort was chosen as the dependent variable and principal components of object-oriented metrics as the independent variables. Maintainability is predicted using Multi Layer Perceptron (MLP) neural network. The results of the study are also compared with other models and it is revealed that the presented model is more useful than the previous one.

School facilities have the important role to ensure the quality of teaching and learning with respect to achieve quality of education. The performance of school facilities significantly affected on student achievement. Therefore, the study on measuring school facility performance is basically important to be taken in order to provide appropriate teaching and learning environment. This paper aims to discuss about framework on measuring the performance of school facilities in public primary school in Batubara district in Indonesia. The concept of facility conditions that identified by Schneider is applied as a basis to measure school facilities performance. The proposed framework is structured through distributed questionnaire spread over Batubara district in order to find the level of school facilities performance from stakeholder perspective, in this case for those who work in school that using facilities. The level of school performance will be ranged from poor to excellent. The results are expected to be used as a guide for school to improve school facilities in public primary school in Indonesia concurrently leading to the improvement of the quality of education in Indonesia in the future.

High equipment reliability is a choice and not an accident of fortune. To a great extent you can choose how long you want between equipment failures. You can deliver high equipment reliability by ensuring the chance of incidents that cause failures of equipment parts are low. The secret to remarkably long and trouble-free equipment lives is to keep parts and components at low stress, within good local environmental conditions, so there is little risk they are unable to handle their design duty. If there is nothing to cause a failure, the failure will not happen and your equipment continues in service at full capacity and full availability. For maintenance practitioners, it is the use of precision maintenance backed-up with condition monitoring applied as a tool to prove maintenance work is done precisely, that provides the foundation for exceptional equipment reliability.

Probability distributions play an important role in the reliability studies and have many applications in engineering. Estimation of the distribution parameters is also significant for making a decision. It is difficult to trap the global solution for the estimation of parameters by the traditional methods such as maximum likelihood estimator (MLE), as these methods trap a local solution. To get the global values of these parameters is complicated. In this paper, we have developed a two-phase approach by taking the advantages of one of the evolutionary algorithms, namely the particle swarm optimization (PSO) for getting the global values of the distribution parameters. PSO exploits the concept of the moment method to estimate the distribution parameters by using mean, standard deviation, coefficient of variation (CV) and Anderson–Darling (AD) statistics for the best fitting of the distribution to failure data. In comparison with the widely used algorithms, a meta-heuristic algorithm (PSO) offers much more choices for system designers.

Reliability, availability and maintainability (RAM) analysis of a system is helpful in carrying out design modifications, if any, and it is required to achieve minimum failures or to increase mean time between failures (MTBF), and thus it is used to plan maintainability requirements, optimise reliability and maximum equipment availability. To this effect, this paper presents the application of RAM analysis in the process industry. Fuzzy Lambda?Tau methodology is used here to model the system behaviour. Each system components, failure rate and repair time are represented by triangular fuzzy numbers with known spread. The methodology uses Petri nets to model the system instead of fault tree because it allows efficient simultaneous generation of minimal cuts and path sets. Various reliability parameters such as MTBF, expected number of failures (ENOF), reliability, availability, etc. are calculated. The computed results are presented to plant personnel for their performance considerably by adopting and practicing suitable maintenance policies/strategies.

Software program developers need to go from beginning to ending and understand source code of the program and other software attributes. The software complexities and length of the program exceedingly affects many design level quality attributes, specifically Simplicity, Testability and software Maintainability. Incomplete design of any software generally leads to misunderstanding and ambiguities and therefore to gives faulty design and development results. This is mainly seeming and appears owing to the absence of it's an appropriate observation, design and development control. However, high level design and program simplicity are very necessary and one of the vital attributes of the system development cycle. This research paper highlights the impact and significance of design level software simplicity in common and as a one of the most useful key factor or index of software quality assurance and testing. In this research work principally there are three major efforts are made. As a first contribution, a valuable relationship between software design quality factor simplicity and related object oriented design properties, this has been set up. In the second contribution, using design level corresponding metrics a simplicity evaluation model for object oriented software is developed. Subsequently, the developed simplicity model has been rationally authenticated by means of experimental data try-out.

This article introduces the problem of collocative integ-rity present in long-lived classification schemes thatundergo several changes. A case study of the subject “eugenics” in the Dewey Decimal Classification is pre-sented to illustrate this phenomenon. Eugenics isstrange because of the kinds of changes it undergoes. The article closes with a discussion of subject ontogenyas the name for this phenomenon and describes impli-cations for information searching and browsing

Service dependability has been recognized in the transportation literature as an effective measure of transit systems quality. Dependability models link this measure of service quality with reliability, availability and maintainability characteristics of the subsystems operating in the transport system. The purpose of this paper is to present a dependability model for the analysis of the impact of power electronics reliability on the service dependability in the case of a vehicle for high speed railway applications

Service dependability has been recognized in the transportation literature as an effective measure of transit systems quality. Dependability models link this measure of service quality with reliability, availability and maintainability characteristics of the subsystems operating in the transport system. The purpose of this paper is to present a dependability model for the analysis of the impact of power electronics reliability on the service dependability in the case of a vehicle for high speed railway applications

Decision on a strategy for effective predictive Reliability, Availability, Maintainability and Safety (RAMS), by the application of Bayesian networks, while ensuring a better preserving of the operators and installation safety in its entirety. A Bayesian network is an acyclic directed graph where nodes represent discrete random variables value (True, False), and the links influences between the variables or conditional dependencies. Relations between variables are deterministic or probabilistic. In a context of risk management, the causal relationships between different events (cause-effect) that can save any installation dysfunction should be taken into account, integrating the conditional probabilities, based on the opinions of experts' field and on the data mining. Bayesian Networks have become a tool for uncertain reasoning, monitoring tasks such as diagnosis, prediction, and decision making. This makes Bayesian networks a subject of research of artificial intelligence. The processing of data through inference allows us to analyze up-and-down and enrich the basis of feedback through the acquisition of observations (evidence). In this study we present the contribution of Bayesian networks to production and processing of natural gas and an application example will be given for a component (boiler) of the liquefied natural gas complex GL4z industrial facility located in Arzew, western Algeria.

Maintenance based on equipment operability checks is widely used for technical systems of various physical nature. For commercial and military aircraft such checks are carried-out after a certain amount of time according to specific maintenance programs. Therefore, great attention in the research literature is paid to the mathematical modeling of maintenance on the basis of equipment operability checks. In this study, a mathematical model of corrective maintenance with operability checks at discrete times for the safety critical systems is considered. The criterion of the corrective maintenance effectiveness is proposed to provide a given level of operational reliability with minimum maintenance costs. A finite time interval is considered for modeling the moments of the system operability checks. The graph of decision making is analyzed for imperfect operability checks and the probabilities of possible decisions are determined. Analytical equations for the operational reliability and expected maintenance costs are derived for an arbitrary distribution of time to failure. The criteria of determining optimal policies of sequential checks are formulated. Numerical examples illustrate the developed theory. For the first time it has been shown that conditional probabilities of correct and incorrect decisions when checking system operability are dependent on the time of failure and parameters of the degradation model. Numerical calculations have shown that in the case of mixing deteriorating systems with different initial time points of operation, the interval between operability checks converges to a constant periodicity.

Model-based software development, particularly when it utilizes unified modeling language (UML) tools, provides artifacts that make programs more transparent. We use these capabilities to automate major steps in the generation of a software FMEA. Automation not only reduces the labor required but also makes the process repeatable and removes many subjective decisions that can impair the credibility of a software

Service dependability has been recognized in the transportation literature as an effective measure of transit systems quality. Dependability models link this measure of service quality with reliability, availability and maintainability characteristics of the subsystems operating in the transport system. The purpose of this paper is to present a dependability model for the analysis of the impact of power electronics reliability on the service dependability in the case of a vehicle for high speed railway applications

Considering maintainability in the design phase is a practice that allows facility managers to conduct maintenance activities easily, accurately, safely, and at minimum cost by incorporating operations and maintenance experience into project planning, design, and construction. It requires designers to consider specific considerations to prevent building defects and reduce the cost of labor and material throughout a building's life cycle. Maintainability issues caused by negligence and poor decisions made during the design phase can result in extra costs over the life cycle of buildings. In fact, one of the most common problems faced by facility managers is the inability to maintain some components of both new and remodeled buildings. In the current practice, the facility manager's first involvement in the project starts with the occupancy phase where the contribution to the design is very little and when the most influential facility design decisions have already been made. Even though facility managers' involvement in the design phase is expected to improve design for maintainability, it is not realistic because facility management teams are usually not set in the design phase. While facility management practitioners are not present during design, their knowledge and requirements can still be implemented in the design phase. This study conducts a comprehensive literature review of maintainability issues and proposes possible solutions for preventing maintainability-related problems and bridging the gap between the building design and facility management processes.

During the course of the industrial 4.0 era, companies have been exponentially developed and have digitized almost the whole business system to stick to their performance targets and to keep or to even enlarge their market share. Maintenance function has obviously followed the trend as it’s considered one of the most important processes in every enterprise as it impacts a group of the most critical performance indicators such as: cost, reliability, availability, safety and productivity. E-maintenance emerged in early 2000 and now is a common term in maintenance literature representing the digitalized side of maintenance whereby assets are monitored and controlled over the internet. According to literature, e-maintenance has a remarkable impact on maintenance KPIs and aims at ambitious objectives like zero-downtime.

This paper would narrate about reliability of structure and review of the history, current position and future development in reliability based approaches. The structure chosen is bridge and the title was given “Reliability Approach in Management of Highway Bridge”. In this paper, will more discuss and explain the approach in highway bridge management in USA starting before 1960s until today and predict with a better solution in reliability based for future bridge management. Firstly, the studies will touch a little bit introduction about the title, importance of using reliability based in structural especially bridge in management and also several importance definitions to make reader know the idea and understand it well. After that, the studies will explain briefly towards history in bridge management approach in order to manage bridge reliability in past and present until 2012. The explanation will starting on how their approach in 1960s until several failure on bridges occurred in USA which make them change their approach in bridge management to maintain bridges reliability. Explanation included the agencies involved and what the effort that they are implemented to find tools and techniques until the both of PONTIS and BRIDGIT Bridge Management System developed (known as USA National BMS). In this history section also will narrate how and what makes PONTIS became a dominant and primary Bridge Management System in USA until today. Besides, the next will explain about National Bridge Inventory (NBI) and PONTIS Bridge Management System software application and it capability for helping in bridge management with efficiently and effectively in summary. Then, next topic will explain about bridge management approach in future. It will be focused on new tool (BridgeWatch) that can help improving bridge management reliability based in future. BridgeWatch is not too new software but it utilization not spread widely in USA (others will explain in that topic). It has a function that PONTIS not have, which if both of these software using together in bridge management approach would give a lot of benefits and also improving the bridge management in future. Lastly, in the last section of this paper, the writer will discuss overall to conclude it.