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The current evolution of 'cloud neuroscience' leads to more efforts with the large-scale EEG applications, by using EEG pipelines to handle the rapidly accumulating EEG data. However, there are a few specific cloud platforms that seek to address the cloud computational challenges of EEG big data analysis to benefit the EEG community. In response to the challenges, a WeBrain cloud platform (https://webrain.uestc.edu.cn/) is designed as a web-based brainformatics platform and computational ecosystem to enable large-scale EEG data storage, exploration and analysis using cloud high-performance computing (HPC) facilities. WeBrain connects researchers from different fields to EEG and multimodal tools that have become the norm in the field and the cloud processing power required to handle those large EEG datasets. This platform provides an easy-to-use system for novice users (even no computer programming skills) and provides satisfactory maintainability, sustainability and flexibility for IT administrators and tool developers. A range of resources are also available on https://webrain.uestc.edu.cn/, including documents, manuals, example datasets related to WeBrain, and collected links to open EEG datasets and tools. It is not necessary for users or administrators to install any software or system, and all that is needed is a modern web browser, which reduces the technical expertise required to use or manage WeBrain. The WeBrain platform is sponsored and driven by the China-Canada-Cuba international brain cooperation project (CCC-Axis, http://ccc-axis.org/), and we hope that WeBrain will be a promising cloud brainformatics platform for exploring brain information in large-scale EEG applications in the EEG community.

Good domain-modeling enables an appropriate separation of concerns that improves quality properties in the simulation models, such as modifiability and maintainability. In this paper, the interplay of abstraction and concreteness in advancing the theory and practice of Modelling and Simulation is improved using the Model-Driven Engineering levels for building simulation models devoted to routing processes. The definition of this type of processes is detailed as a domain-model conceived as an abstraction defined in a graph model. Such abstraction turns into a set of formal simulation models that are (later) translated into an executable implementation. The final simulation models are specified using Routed DEVS formalism. The methodological proposal is accomplished with the development of a Modelling and Simulation graphical software tool that uses the set of models (defined in terms of the Model-Driven Engineering approach) as the core of its operation. This graphical software tool is developed as a plug-in for Eclipse Integrated Development Environment with aims to take advantage of existent Modeling and Simulation software. Therefore, the usefulness of graphical modeling for supporting the development of the simulation models is empowered with a Model-Driven Engineering process. The main benefit obtained when the Model-Driven Engineering approach is used for modeling an abstraction of the final simulation model is a clear reduction of formalization and implementation times. Fil: Blas, María Julia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina Fil: Gonnet, Silvio Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina

Safety instrumented system is the independent layer of protection. Safety instrumented systems have been used for many years to detect hazardous events, and to perform required safety instrumented functions (SIFs) in the process industries to maintain or bring the process back to a safe state. If instrumentation is to be effectively used for SIFs, it is essential that this instrumentation achieves certain minimum standards and performance levels. Safety instrumented systems are used in all process industries. It also requires a process hazard and risk assessment to be carried out to enable the specification for SISs to be derived. Other safety systems are only considered so that their contribution can be taken into account when considering the performance requirements for the SISs. The SIS includes all components and subsystems necessary to carry out the SIF, from sensor(s) to final element(s). To achieve the required function, reliability and maintainability is very important. The aim of this chapter is to design a reliable system and perform regular maintenance to sustain the achieved reliability. To achieve reliability, we have to calculate the average probability of failure on demand and while doing so we take into consideration the PFD value of all the components used in the safety instrumented function (SIF), the allowed spurious trip in a year and also the proof-test interval for testing the individual SIF in a SIS system. The failure of the SIS to achieve the desired function could result in huge consequences for the safety of the monitored system and also for the production availability due to spurious trips. The SIS system in a chemical plant is used to automatically stop the final element (valve or pump) and get the process under control. Fault-tree analysis (FTA) is widely used for identifying the root causes of undesired failures in a system. The traditional static fault trees with AND, OR gates cannot capture the dynamic behavior of system failure, such as sequence-dependent events, spares, and dynamic-redundancy management. In order to overcome this difficulty, the concept of dynamic Fault tree is introduced by adding sequential notion to the traditional FT approach. System failures can then depend on component failure order as well as combination. We have applied the dynamic fault tree concept in this chapter. In the traditional fault tree for the SIS system, we usually assume that exact failure probabilities of events are collected. We mean to say that during design or development stage we do the FTA and during that time we may add new component, which may not have failure date and there may be environment impact on this component during operation. In this chapter, we find the critical components in the SIS system based on FTA and determine the weak paths in the SIS system, where action should be taken to reduce failure.

In this chapter, we adopt Six Sigma (SS) approach and reliability, availability, and maintainability (RAM) analysis in a plastic industry. We present a step-by-step application of the SS methodology for identifying and reducing the downtimes in the industry and examine the current operations management. Thus, failure and repair data are analyzed on the basis of statistical techniques. Histograms, box plots, and descriptive statistics on line-level failure data are conducted. The mathematical distribution parameters that best fit the fault data are calculated. Models for reliability, maintainability, failure rate, and repair rate have been established for the entire system. The models could be a useful tool for determining current conditions as well as forecasting the performance of improving the line's operations management policies. The main goals of the applicable approach are to understand the nature of the downtime dynamics and to measure accurately quantitatively the RAM characteristics of the industrial system. The analysis determines the system's critical points needing additional improvement through an appropriate maintenance plan. The benefit of the approach is that the production process is constantly tracked by relevant indices, the use of which contributes to a continuous improvement process.

Reliability design is an important work in the early design stage of offshore wind turbines. Due to the incomplete considerations and poor feasibility of the drawbacks for existing methods, a set of the practical reliability design method is proposed in this paper. The time characteristics and many influential factors of units are considered in the design process. The influential factors of the system's units are scored by several experts with extensive engineering experience. Based on this, the reliability allocation and the maintainability prediction of the repairable system are performed using different methods. To realistically evaluate the reliability level of each unit obtained by three different methods, a fuzzy reliability evaluation method is developed to rank the reliability level of each unit with considerations of the mean time between failure (MTBF), mean time to repair (MTTR), failure frequency and availability using the compound weight and fuzzy membership function. Following this, redundant design is used to eliminate weaknesses to keep the system reliability at a high level. Using the reliability data obtained above, a time-dependent reliability model of the system considering load sharing is built to explore the influences of reliability allocation on the system reliability in the 20-year service life. The effectiveness and feasibility of the proposed approaches are demonstrated with a 5MW offshore wind turbine.

We consider reliability engineering in modern civil aviation industry, and the related engineering activities and methods. We consider reliability in a broad sense, referring to other system characteristics that are related to it, like availability, maintainability, safety and durability. We covered the entire lifecycle of the equipment, including reliability requirement identification, reliability analysis and design, verification and validation of reliability requirements (typically involved in the equipment design and development phase), quality assurance (which typically enters in the manufacturing phase), and fault diagnosis and prognosis and maintenance (which are connected to the operation phase). Lessons learnt from reliability engineering practices in civil aviation industry are given, which might serve as reference for reliability managers and engineers, also from other industries with high reliability requirements. Keywords: Civil aviation, Commercial aircraft, Fault diagnosis and prognosis, Human reliability analysis, Maintenance, Quality control, Reliability design, Reliability engineering

Wind energy, with an exponential growth in the last years, is nowadays one of the most important renewable energy sources. Modern wind turbines are bigger and complex to produce more energy. This industry requires to reduce its operating and maintenance costs and to increase its reliability, safety, maintainability and availability. Condition monitoring systems are beginning to be employed for this purpose. They must be reliable and cost-effective to reduce the long periods of downtimes and high maintenance costs, and to avoid catastrophic scenarios caused by undetected failures. This paper presents a survey about the most important and updated condition monitoring techniques based on non-destructive testing and methods applied to wind turbine blades. In addition, it analyses the future trends and challenges of structural health monitoring systems in wind turbine blades. Wind energy, with an exponential growth in the last years, is nowadays one of the most important renewable energy sources. Modern wind turbines are bigger and complex to produce more energy. This industry requires to reduce its operating and maintenance costs and to increase its reliability, safety, maintainability and availability. Condition monitoring systems are beginning to be employed for this purpose. They must be reliable and cost-effective to reduce the long periods of downtimes and high maintenance costs, and to avoid catastrophic scenarios caused by undetected failures. This paper presents a survey about the most important and updated condition monitoring techniques based on non-destructive testing and methods applied to wind turbine blades. In addition, it analyses the future trends and challenges of structural health monitoring systems in wind turbine blades.

Research into software architecture and design has become more and more prominent since the 1990s. Since then, companies have reported how software architecting helped them to tackle various challenges in system design, especially related to system-level quality properties such as scalability and maintainability. Academic research in software architecture has focused on several areas, including architecture description through views and architecture description languages, and on methods for evaluating architectural designs. While much of the contribution of research in software architecture was inspired by industrial experiences, little of the research was validated beyond individual case studies. Many scientific disciplines are currently harvesting fruits from large-scale data collection about their subjects of study. Therefore, this chapter contributes a discussion of challenges and directions for Big Data-driven studies of software architecture. Given the large amount of effort that is needed for this type of research, a promising direction is to look into a community-based infrastructure for enabling and supporting this type of research. We share lessons learned through building various tools that could form building blocks in such an infrastructure. Based on these, we synthesize a reference architecture for creating such a community-wide infrastructure for Big Data-based research in software architecture.

Context:Kotlin is a new programming language representing an alternative to Java; they both target the same JVM and can safely coexist in the same application. Kotlin is advertised as capable to solve several known limitations of Java. Recent surveys show that Kotlin achieved a relevant diffusion among Java developers. Goal:We planned to empirically assess a few typical promises of Kotlin w.r.t. known Java’s limitations, in terms of development effectiveness, maintainability, and ease of development. Method:Our experiment involved 27 teams of 4 people each that completed a set of maintenance tasks (both defect correction and feature addition) on Android apps written in either Java or Kotlin. In addition to the number of fixed defects, effort, and code size, we collected, though a questionnaire, the participants’ perceptions about the avoidance of known pitfalls. Results:We did not observe any significant difference in terms of maintainability between the two languages.We found a significant difference regarding the amount of code written, which constitutes evidence of better conciseness of Kotlin. Concerning ease of development, the frequency of NullPointerExceptions reported by the subjects was significantly lower when developing in Kotlin. On the other hand, no significant difference was found in the occurrence of other common Java pitfalls. Finally, the IDE support was deemed better for Java than Kotlin. Conclusions:Some of the promises of Kotlin to be a ”better Java” have been confirmed by our empirical assessment. Evidence suggests that the effort in transitioning to Kotlin can provide some advantages to Java developers, especially regarding code conciseness.Our results may serve as the basis for further investigations on the properties of the language.

Sustainable organizations show effective long haul execution in the midst of the limitations forced by financial, social, and ecological frameworks by building up a procedure that economically produces and catches an incentive into the future. The sharing economy gives a perfect focal point to investigate and add to the manageable advancement nature. While the sharing economy can add to manageable advancement and has a lot of space to create reasonable issues in driving manageability, there is an absence of sharing economy maintainability experimental investigations. Circular economy has without a doubt ended up noticeably as one of the hotly debated issues in broad daylight wrangles about new and more practical modern ideal models and methodologies. In this regard, the design of circular economy is in the way that it goes for beating the prevailing direct take, influence, transfer economy model. Circular economy bases on the foundation of shut creation frameworks, where assets are reused and kept in a circle of creation and use, permitting producing more esteem and for a more extended period. Circular economy pushes the wildernesses of natural sustainability by stressing changing items such that there are workable connections between environmental frameworks and monetary development. This chapter presents approaches to reexamine and update business in the textile and clothing field by offering an overview on a few outline methodologies that exist today in specialty markets.

Complex driver-assistance systems that analyze driving situations based on a range of sensors enable autonomous driving vehicles—a key aspect of smart cities. This massive automation necessitates computationally powerful and energy-efficient hardware devices available in each individual driving unit. Heterogeneous multiprocessor system-on-chips provide excellent performance-to-power characteristics for the use in driver-assistance applications. Since these programmable chips use flexible software, they theoretically feature high maintainability and portability. However, due to the lack of programmability of different parallel and heterogeneous processing units, developers can barely fully exploit all computational capabilities. To overcome the gap between theoretical peak performance and the effectively gained speedup, diverse programming approaches and supportive tools have emerged. This work presents an overview of the most important trends and contributes a middleware approach for abstracting, and thus unifying, the programming for homogeneous and heterogeneous architectures.

The global energy production model is changing from fossil fuels to renewable and nuclear energies. Concentrated solar power is one of the growing technologies that is leading this process. This growth implies the sophistication and size of the systems and, therefore, it requires an increase in maintenance tasks to ensure reliability, availability, maintainability and safety. The aim of this paper is to describe the current context of concentrated solar power, to summarise and analyse the main degradation mechanisms and the main techniques to detect, prevent and mitigate these faults. An exhaustive literature study is presented, considering the most advanced techniques and approaches. A novel qualitative and quantitative analysis of the literature is provided. Finally, the current trends and the future challenges in this field are gathered from this study.

Junction boxes provide an important function of providing a safe transition of power produced from the photovoltaic (PV) cells in the laminate to the external wiring system for interconnecting modules and loads. Junction boxes, also referred to as “jboxes,” are used in a wide variety of electrical applications and serve to protect the connections between wires and cables. In a PV module, however, the jbox also houses the bypass diode that provides a PV cell-protective function and it is prewired and terminated for rapid interconnection of modules in the field. The junction box enclosure consists of a body enclosure and lid both of which are almost exclusively made of injection-molded polymeric construction and are adhered to the substrate of the module with an adhesive compatible with both the junction box polymer and PV module substrate. The combination of the enclosure, bypass diode, transitioning wiring, connectors, and adhesive makes the jbox a complex component that appears deceptively simple and is not designed to be maintained or serviced. This combination of system behavior and lack of maintainability poses a reliability challenge for the PV module manufacturer, where a service lifetime of 25-years is expected. The importance of design, characterization of the failure and degradation modes, sufficient qualification and durability testing, and manufacturing quality control for the Jbox system (box and connectors) cannot be overestimated since failures of this system account for approximately 18% of 180 fire incidents studied from 1995 to 2012. This study indicates that the jbox with its associated PV connector was the number one cause for a fire, with the second being inverters at 16%. The International Energy Agency’s 2014 report suggests that PV connectors alone may be responsible for up to one-third of PV module fire incidents suggesting that special attention to this component is required.

The photovoltaic solar energy industry is expanding, and there is therefore a need to increase and improve its maintainability, operating costs, availability, reliability, safety, life cycle, etc. The aim of this article is to design, develop and check a new condition monitoring system to detect dust in solar photovoltaic panels. The condition monitoring system uses a radiometric sensor connected to an Arduino platform. This novel approach is based on emissivity analysis produced over a surface and characterized with a low emissivity value when dust appears. A thermographic camera is also employed to validate the results provided by the radiometric sensor. The system is designed to be embedded in an unmanned aerial vehicle. Radiometric data is sent and analysed, Internet of Things is employed, and thermograms are stored for further processing. Several scenarios with a real solar panel are used in the experiments, in which the angles and distances of the sensors and surface conditions are studied. An analysis of the radiometric sensor provides accuracy results, and the presence of dust is identified in all scenarios.

Quality assurance and long-term usability throughout the life cycle of a model, simulation, and its data (M&S) is a general but increasingly important demand. Regarding flexible use of increasingly complex simulation models and data (M&S) requires M&S modularity, scalability, maintainability, and reusability for M&S operation and development teams, and above all effective M&S management tools. Such tools should facilitate and automate not only the coordination of those teams but also the easy, reliable and traceable reuse of model components, in particular regarding model repository search functions and developer team guidance, with emphasis on quality assurance and comprehensive life cycle documentation. After justifying the need for a collaborative platform integrating all team and M&S management tasks as well as documenting every phase of an M&S life cycle in a standardized manner, a generic concept and system architecture meeting these requirements are introduced (model management system, MMS). Beside this MMS concept and architecture, we introduce briefly its implementation in form of a demonstrator compatible with institutional quality assurance approaches such as documentation of all relevant M&S development stages including verification, validation, and accreditation (VV&A).

Heterogeneous manycore performance-portable programming models and libraries, such as Kokkos, have been developed to facilitate portability and maintainability of high-performance computing codes and enhance their resilience to architectural changes. Here we investigate the suitability of the Kokkos programming model for optimising the performance of the high-order mesh generator NekMesh, which has been developed to efficiently generate meshes containing millions of elements for industrial problem involving complex geometries. We describe the variational approach for a posteriori high-order mesh optimisation employed within NekMesh and its parallel implementation. We discuss its implementation for modern manycore massively parallel shared-memory CPU and GPU platforms using Kokkos and demonstrate that we achieve increased performance on multicore CPUs and accelerators compared with a native Pthreads implementation. Further, we show that we achieve additional speedup and cost reduction by running on GPUs without any hardware-specific code optimisation.

Polyglot persistence facilitates use of most suitable database technology based on the requirement of an application. There are lots of use cases as well as huge potential for Polyglot Persistence in e-Commerce web portals, Search Engines, and Healthcare Information Ecosystem applications. But, designing and implementation of an application in a Polyglot environment is not a straightforward task, since adding more data storage technologies increases complexity in programming. Further knowledge of multiple programming languages, maintainability of the Polyglot application, and tool support for Polyglot persistence are the challenges of Polyglot Persistence. This chapter discusses the various aspects of Polyglot persistence with a focus on NoSQL database.

Virtual Analysers are used in industrial processes due to its capacity to replace essential equipment by mathematical models. In order to guarantee the precision of the model output, one has to assure the model input will be available and reliable, implying greater efforts to sustain a high maintainability of the measuring devices used to generate model input. Thus, there is a significant trade-off between model costs and output reliability. This work introduces a new index, called Ana-Braga-Barbosa-Adelmo (ABBA), which embodies such economic trait when selecting an empirical model for virtual analysers. Associated costs of different Partial-Least-Square (PLS) models used to estimate the content of contaminants in a trickle bed reactor are simulated through Monte Carlo assuming a Poisson distribution for instrument failure. The performance of different PLS models are analysed in light of the new proposed index, which indicates the most adequate one. Such is different from the PLS model developed based on selection of variables through Variable Importance in Projection (VIP) as the latter relies on a greater number of input variables for similar performance.

Vegetables and other row-crops represent a large share of the agricultural production. There is a large variation in crop species, and a limited availability in specialized herbicides. The robot presented here utilizes systematic growing techniques to navigate and operate in the field. By the use of machine vision it separates seeded vegetable crops from weed. Each weed within the row is treated with individual herbicide droplets, without affecting the crop. This results in a significant reduction in herbicide use, and allows for the use of herbicides that would otherwise harm the crop. The robot is tailored to this purpose with cost, maintainability, efficient operation and robustness in mind. The three-wheeled design is unconventional, and the design maintains maneuverability and stability with the benefit of reduced weight, complexity and cost. Indoor pot trials with four weed species demonstrated that the Drop-on-Demand system (DoD) could control the weeds with as little as 7.6 μg glyphosate or 0.15 μg iodosulfuron per plant. The results also highlight the importance of liquid characteristics for droplet stability and leaf retention properties. The common herbicide glyphosate had no effect unless mixed with suitable additives. A field trial with the robot was performed in a carrot field, and all the weeds were effectively controlled with the DoD system applying 5.3 μg of glyphosate per droplet. The robot and DoD system represent a paradigm shift to the environmental impact and health risks of weed control, while providing a valuable tool to the producers.

This chapter provides an overview of the main challenges of modeling for very demanding systems, such as wind turbine systems, which require reliability, availability, maintainability, and safety over power conversion efficiency. These issues have begun to stimulate research and development in the wide control community particularly for the installations that need a high degree of sustainability. This represents a key point for offshore wind turbines and wind park installations, since they are characterized by expensive and/or safety critical maintenance work. In this case, a clear conflict exists between ensuring a high degree of availability and reducing maintenance times, which affect the final energy cost. On the other hand, wind turbines have highly nonlinear dynamics, with a stochastic and uncontrollable driving force as input in the form of wind speed, thus representing an interesting challenge also from the modeling point of view. Moreover, a proper mathematical description of the wind turbine system should be able to capture the complete behavior of the process under monitoring, thus providing an important impact on the control design itself. In this way, the fault diagnosis and control schemes could guarantee prescribed performance, whilst also giving a degree of tolerance to possible deviation of characteristic properties or system parameters from standard conditions, if properly included in the wind turbine model itself.

Until recently decisions were mostly modelled within the process. Such an approach was shown to impair the maintainability, scalability, and flexibility of both processes and decisions. Lately, literature is moving towards a separation of concerns between the process and decision model. Most notably, the introduction of the Decision Model and Notation (DMN) standard provides a suitable solution for filling the void of decision representation. This raises the question whether decisions and processes can easily be separated and consistently integrated. We introduce an integrated way of modelling the process, while providing a decision model which encompasses the process in its entirety, rather than focusing on local decision points only. Specifically, this paper contributes formal definitions for decision models and for the integration of processes and decisions. Additionally, inconsistencies between process and decision models are identified and we remedy those inconsistencies by establishing FivePrinciples for integrated Process and Decision Modelling (5PDM). The principles are subsequently illustrated and validated on a case of a Belgian accounting company. We address the question of consistent integration of process and decision models.We provide a formalisation on which the integration is based.We list possible inconsistencies between process and decision models.We provide modelling guidelines for consistent integration.Our guidelines are applied and illustrated on a real life case.

Reliability and maintainability of mining industry is more in focus than ever, and the mining systems are becoming more complex and the equipment more expensive to repair or modify. Unplanned failures can result in significant costs, especially when the machinery is hard to repair or spare parts are far away. This paper presents a case study describing a reliability and maintainability analysis of the main conveyor system of the Svea Coal Mine located in Svalbard, Norway. The conveyor system includes several separate conveyors. In this study, the main six conveyors of the whole system were selected for the analysis. The failure and repair data of the conveyors were collected for the whole year of 2010 using maintenance and daily reports. The date was analyzed and the result shows that the availability of six conveyers is 96.44% for one year of operation. However, reliability of these conveyers needs to be improved in order to reduce the number of failures. Keywords: Reliability, Maintainability, Availability, Conveyor, Coal mine

Publisher Summary This chapter discusses a cost-effective approach to quality, reliability and safety. The costs associated with acquiring, operating and maintaining equipments are stated to be important factors and the total costs incurred over the period of ownership of equipment is referred to as life-cycle costs. The life-cycle costs can be separated into acquisition cost, ownership cost, operating cost and administration cost and the costs are influenced by reliability, maintainability and safety factors. The life-cycle costs will be reduced by improving reliability, maintainability and safety but will be increased by the activities needed to achieve them. Several figures are presented that illustrates the optimum set of parameters for minimizing total cost. The cost of risk reduction is discussed and the concept of ALARP (As Low As Reasonably Practicable). A risk is said to be ALARP, if the cost of further risk reduction is disproportionate to the benefit. This is determined by comparing the cost per life saved, from any proposed risk reduction with some agreed criterion. The costs and savings involved with safety engineering and the cost of quality are further discussed.

A safety instrumentation system (SIS) demands a fault tolerant design to ensure high availability and system integrity. The discussions on fault tolerance cover various fault tolerant measures, including fault tolerant characteristics, redundancies, and hardware and software. The discussions start with faults and failure types along with other related issues like availability, maintainability, and countermeasures suitable for each. Discussions are completed with a focus on fault tolerant networks including fault tolerant Ethernet. Minute details on independent protection layer characteristics and their effect on SIS are covered. The role of a firewall and demilitarized zone in combating a cyber attack is very important and discussions on these are included. In view of current demands for commercial off-the-shelf and integrated networks, cyber security is extremely important and special discussions on these are necessary because cyber security of industrial automation and control systems is different from information technology cyber security. Special discussions are included to focus on zone conduit and Open Platform Communications firewalls in line with the upcoming international standard ISA/IEC 62443 series.

The complexity of Business Intelligence activities has driven the proposal of several approaches for the effective modeling of Extract-Transform-Load (ETL) processes, based on the conceptual abstraction of their operations. Apart from fostering automation and maintainability, such modeling also provides the building blocks to identify and represent frequently recurring patterns. Despite some existing work on classifying ETL components and functionality archetypes, the issue of systematically mining such patterns and their connection to quality attributes such as performance has not yet been addressed. In this work, we propose a methodology for the identification of ETL structural patterns. We logically model the ETL workflows using labeled graphs and employ graph algorithms to identify candidate patterns and to recognize them on different workflows. We showcase our approach through a use case that is applied on implemented ETL processes from the TPC-DI specification and we present mined ETL patterns. Decomposing ETL processes to identified patterns, our approach provides a stepping stone for the automatic translation of ETL logical models to their conceptual representation and to generate fine-grained cost models at the granularity level of patterns.

This chapter gives an overview of the important stochastic failure distributions and reliability analysis models.

This chapter focuses on the history of reliability and safety engineering. There is no human activity or equipment that has zero rate of failure and safety technology has emerged to optimize the risk of failure. Safety technology attempts to balance the risk of a given activity against its benefits and seeks to assess the need for further risk reduction depending upon the cost. Reliability engineering, beginning in the design phase, attempts to select the design compromise that balances the cost of reducing failure against value of enhanced performance. The design of safety-related systems has evolved partly in response to technological innovations, but largely as a result of lessons learnt from failures. The application of technology to hazardous areas requires the formal application of this feedback principle in order to maximize the rate of reliability improvement. System modeling, using failure mode analysis and fault tree analysis methods, has been developed over the last thirty years and it now involves numerous software tools which enable predictions to be updated and refined throughout the design cycle. Achieving reliability, safety and maintainability is mentioned to be a result from activities in three main areas: design, manufacture and field use.

This chapter gives an overview of reliability and maintainability program that is implemented in A380 aircraft.

This paper provides an overview of the current technical issues and challenges associated with the design of hypersonic vehicles. Two distinct classes of vehicles are reviewed; Hypersonic Transports and Space Launchers, their common features and differences are examined. After a brief historical overview, the paper takes a multi-disciplinary approach to these vehicles, discusses various design aspects, and technical challenges. Operational issues are explored, including mission profiles, current and predicted markets, in addition to environmental effects and human factors. Technological issues are also reviewed, focusing on the three major challenge areas associated with these vehicles: aerothermodynamics, propulsion, and structures. In addition, matters of reliability and maintainability are also presented. The paper also reviews the certification and flight testing of these vehicles from a global perspective. Finally the current stakeholders in the field of hypersonic flight are presented, summarizing the active programs and promising concepts.

A key ITER maintenance activity is the exchange of the divertor cassettes. One of the major focuses of the EU Remote Handling (RH) programme has been the study and development of the remote handling equipment necessary for divertor exchange. The current major step in this programme involves the construction of a full scale physical test facility, namely DTP2 (Divertor Test Platform 2), in which to demonstrate and refine the RH equipment designs for ITER using prototypes. The major objective of the DTP2 project is the proof of concept studies of various RH devices, but is also important to define principles for standardizing control hardware and methods around the ITER maintenance equipment.This paper focuses on describing the control system hardware design optimization that is taking place at DTP2. Here there will be two RH movers, namely the Cassette Multifuctional Mover (CMM), Cassette Toroidal Mover (CTM) and assisting water hydraulic force feedback manipulators (WHMAN) located aboard each Mover. The idea here is to use common Real Time Operating Systems (RTOS), measurement and control IO-cards etc. for all maintenance devices and to standardize sensors and control components as much as possible.In this paper, new optimized DTP2 control system hardware design and some initial experimentation with the new DTP2 RH control system platform are presented. The proposed new approach is able to fulfil the functional requirements for both Mover and Manipulator control systems. Since the new control system hardware design has reduced architecture there are a number of benefits compared to the old approach. The simplified hardware solution enables the use of a single software development environment and a single communication protocol. This will result in easier maintainability of the software and hardware, less dependence on trained personnel, easier training of operators and hence reduced the development costs of ITER RH.

The modern approach to product design calls for product quality to be considered during the initial development stage. This chapter first expounds the relationship between product quality and reliability, provides definitions of comprehensive reliability, and addresses related theory. Second, the reliability design method of aircraft hydraulic system, including its electrical and mechanical components, is discussed in detail. This chapter introduces maintainability design by allocation of the monitoring sensors for fault detection, diagnosis, and isolation. Afterward, typical safety assessment methods, including failure modes analysis, fault tree analysis, Markov analysis, and common cause analysis are introduced. Finally, this chapter presents integrated reliability evaluation and its effect on the aircraft hydraulic system.

The aim of this chapter is to demonstrate the concept of system performance indexes such as reliability, availability, and production efficiency as well as the approach to predict such performance indexes. Therefore reliability, availability, and maintainability (RAM) analysis is the basis of complex system performance analysis. To demonstrate such methodology the RAM analysis steps, such as scope definition, lifetime data analysis, modeling, simulation, critical analysis, sensitivity analysis, and conclusions, will be discussed. In fact, RAM analysis simulates the system behavior in terms of subsystem and equipment failures along the life cycle, To perform such simulation the reliability diagram block model is very necessary, as will be demonstrated. In addition, the main object of study in RAM analysis rather than predicting the performance index is to analyze the influence of external factors on system performance, such as logistics, spare parts, redundancy configuration, as well as the effect of preventive maintenance in performance indexes. Each of such factors influence in asset performance will be demonstrated by example in this chapter. Moreover, to predict the necessary performance improvement the improvement allocation and optimization concepts will be discussed. The chapter will present different case studies applied to real asset project and operation phase solutions to improve different system performances.

CyberInfrastructures (CIs) are complex socio-technical-economical systems that are difficult to describe, design, analyze, and evaluate. As one example, E-Health CIs are patient-centric community-serving systems that have particular regulations for information security, governance, resource management, scalability, and maintainability. We have built multiple successful E-Health interdisciplinary projects at the University of California, San Diego, including CY berinfrastructure for CO mparative effectiveness REsearch (CYCORE) for cancer clinical trials, P ersonal A ctivity L ocation M easurement S ystem (PALMS) for studying human activity patterns, CitiSense for sensing city pollution, and I ntegrating D ata for A nalysis, A nonymization, and SH aring (iDASH), which is a National Center for Biomedical Computing. These CIs have served their user communities well with respect to their projects’ goals and durations. Due to their shared requirements, these systems were all designed around the service bus-based Rich Services software architecture. However, there are also significant differences in how these CIs were designed and implemented, which might be informative to the community of CI developers. In this chapter, we detail our experience with developing E-Health CIs from the software quality perspective. We start from generic CI requirements along with domain and application-specific requirements, and we analyze the tradeoffs of development and deployment choices and propose a blueprint for next generation CIs. The main question that we answer is: How can we improve the quality of the next CIs by capitalizing on lessons learned, the best architectural and implementation choices, and reusing elements from previously existing systems? We present three contributions. First, we identify a set of activities and attributes that enable us to assess the quality of a CI with regard to important maintenance activities that are common to all CIs. These activities and attributes and the way we perform the evaluation are generic and can be applied to other projects and domains. Second, we analyze multiple projects and identify a set of common requirements for CIs and applications in the E-Health domain. We separate these requirements into common requirements that apply to all CIs, E-Health specific requirements that apply to CIs and most applications in the Health domain, and application-specific requirements. This separation makes many requirements reusable, and we expect that they will inform the development of future E-Health CIs and applications. Finally, we identify a set of architectural and implementation recommendations that will help developers create higher quality CIs for the E-Health domain.

In Chapter 3, we identified that the dependability of a system must be managed through the entire lifecycle from requirement analysis to the decommissioning of the system.

Reliability, availability, maintainability and safety (RAMS) of wind turbines in cold climates are closely related to ice accretion. The deterioration of RAMS of the wind turbines involves costs such as Operation and Maintenance costs and energy losses. Systems to monitor the condition of the wind turbines play a key role in the wind energy industry to decrease the costs mentioned above and to improve the maintenance management. This research presents an economic study of the life cycle cost (LCC) for ice condition monitoring systems in wind turbines. In particular, the paper studies the economic feasibility of different commercial ice detection systems through a LCC model when wind turbines are exposed to different scenarios. To date, the scientific literature does not collect any study about the LCC for ice detection systems using different annual rates of return, and providing a map with numerical solution. The study is extended by including a bank loan for a real point of view. The findings of this study reveal the ice detection systems that are more profitable and the selection criteria to decide the use of a bank loan. Finally, it is shown that predictive costs are much smaller than corrective cost reaching a reduction of these corrective costs with the ice detection systems.

In recent years, all systems (mechanical, electrical, automatic, electronic, physical, etc.), irrespective of their domain (energy, transport, production, banking, etc.), have seen the emergence of software. Introduction of software has been carried out in various forms, ranging from a simple addition of functionality to complete replacement of the initial system by a software-based system.

This chapter introduces some of the modern aircraft hydraulic system technologies that will make the next generation of aircraft greener, cheaper, and safer. This chapter first introduces the intelligent hydraulic power supply system, which can generate pressure and flow rate according to the system requirements, manage the energy, reduce the power loss, and improve the efficiency of the hydraulic system. The new architecture of the power transmission system based on two hydraulic power supplies and two electrical power supplies (2H/2E) is then introduced. This new architecture can reduce the overall system weight, increase power efficiency, improve the reliability, and keep fail-safe modes. Finally, the chapter introduces prognostics and health management, which can guarantee the high reliability, safety, and maintainability of the aircraft through automatic detection, diagnosis, and prognosis of the adverse events during flight.

This chapter explains the techniques of quantified reliability prediction. For any reliability assessment to be meaningful it is vital to address a specific system failure mode. Predicting the “spurious shutdown” frequency of a safety (shutdown) system involves a different logic model and different failure rates from predicting the probability of failure to respond. When modeling the “failure to respond” event the “1 out of 2” arrangement represents redundancy and the two sub-systems are said to be “parallel” in that they both need to fail to cause the event. Furthermore the component failure rates used are those which lead to ignoring a genuine signal. On the other hand, if one chooses to model the “spurious shutdown” event the position is reversed and the sub-systems are seen to be “series” in that either failure is sufficient to cause the event. Furthermore the component failure rates are for the modes which lead to a spurious signal. Finally, in addition to random coincident hardware failures, and their associated dependent failures, it is frequently necessary to include human error in a prediction model.

This chapter presents a helicopter accident and fatality statistics to provide a comparison with other activities. Following this, it illustrates an example of a quantified risk assessment, which required an input from the foregoing statistics. These statistics are based on the Robinson R22 and R44 machines, which account for 25% of the rotorcraft flying hours in the UK (based on CAA statistics 1996–2009). They are used mainly for training and private helicopter flights. The incident data obtained from the AAIB (Air Accident Investigation Bureau) cover just over 800,000 flying hours (1996–2008). This chapter summarizes the rates for R22s and R24s in a tabular form. This chapter also compares the risk of fatality with a number of other activities. The term FAFR refers to the number of fatalities per 100,000 hours (108 hrs) of exposure to the activity in question. For voluntary activities where exposure varies between activities, it is a more representative metric than fatalities per calendar year (which take no account of relative exposure). The comparative FAFRs are obtained from reliability, maintainability and risk.

A domain-specific language (DSL) aims to support software development by offering abstractions to a particular domain. It is expected that DSLs improve the maintainability of artifacts otherwise produced with general-purpose languages. However, the maintainability of the DSL artifacts and, hence, their adoption in mainstream development, is largely dependent on the usability of the language itself. Unfortunately, it is often hard to identify their usability strengths and weaknesses early, as there is no guidance on how to objectively reveal them. Usability is a multi-faceted quality characteristic, which is challenging to quantify beforehand by DSL stakeholders. There is even less support on how to quantitatively evaluate the usability of DSLs used in maintenance tasks. In this context, this paper reports a study to compare the usability of textual DSLs under the perspective of software maintenance. A usability measurement framework was developed based on the cognitive dimensions of notations. The framework was evaluated both qualitatively and quantitatively using two DSLs in the context of two evolving object-oriented systems. The results suggested that the proposed metrics were useful: (1) to early identify DSL usability limitations, (2) to reveal specific DSL features favoring maintenance tasks, and (3) to successfully analyze eight critical DSL usability dimensions., This work was funded by B. Cafeo CAPES PhD Scholarship, and CNPq scholarship grant number 141688/2013-0; A. Garcia FAPERJ - distinguished scientist grant (number E-26/102.211/2009), CNPq - productivity grants (number 305526/2009-0 and 308490/2012-6), Universal project grants (number 483882/2009-7 and 485348/2011-0), and PUC-Rio (productivity grant)., info:eu-repo/semantics/publishedVersion

This chapter deals mainly with the maintenance and management systems of Chinese high-speed turnouts. The management policies and maintenance standards of Chinese high-speed turnouts are first introduced, and several calculation methods for track quality assessment are given in detail. Then, high-speed turnout inspection and monitoring technologies, including track dynamic inspection car, rail detection car, and turnout inspection systems, are introduced. Maintenance technologies are also mentioned here. In addition, the application of Permanent Way Management Information System (PWMIS), developed independently by China, and Reliability, Availability, Maintainability and Safety (RAMS) in the management of high-speed turnout in China are detailed in this chapter.

Code comments contain a rich amount of information that can be leveraged to improve software maintainability and reliability. This chapter on studying and analyzing free-form and semistructured code comments will help practitioners, researchers, and students learn about (1) the characteristics and content of code comments, (2) the techniques, tools, and measures for studying and analyzing code comments automatically or semiautomatically, and (3) future research directions and challenges. Readers will acquire a unique blend of interdisciplinary techniques, including natural language processing, machine learning, and program analysis, which are also useful for analyzing other software engineering text. This chapter can serve as an introduction to comment study and analysis for practitioners, researchers, and students who are interested in conducting research in this area, applying comment analysis techniques in industry, and learning about this area.

Code readability and maintainability can frequently be enhanced through the use of mnemonic names and global text substitutions. Verilog supports several different methods for these techniques, as well as providing for design reuse and scalability.

The cumulative distribution functions of the first passage time from the given states to a subset of states and expected values and second moments corresponding to them are considered in this chapter. The equations for these quantities are presented. Moreover, the concept of interval transition probabilities is discussed and the corresponding equations are also derived. These equations allowed obtaining the interval transition probabilities for the alternating process and also for the Poisson and Furry-Yule processes. Furthermore, the reliability and maintainability characteristics and parameters in semi-Markov models are considered in the chapter. At the end of the chapter, numerical illustrative examples and proofs of some theorems are shown.

This chapter deals with the structural selection and design of rail members of high-speed turnouts. First, the principle of structural selection is introduced, which requires high-speed turnouts to meet the requirements of ride safety, quality and reliability, manufacturing feasibility, laying convenience and maintainability, and technological maturity and reliability. Second, the study of structural selection and rail member design is discussed. Finally, the technical and manufacturing requirements for high-speed railway rails are introduced.

Increase in energy usage, particularly from fossil fuel sources is widely understood to be responsible for the environmental problems (Climate Change) experienced globally today. Response to mitigating this anthropogenic induced consequence created the need for innovative low carbon and renewable technologies in buildings. In the UK presently, every new building is expected to be low-carbon and energy-efficient. However, it is widely acknowledged that significant differences often exist between designed and in-use performances of the buildings. Clients and end-users of these technologies appear not to be getting long term value for their investments; much attention has not been given to how these innovative technologies can be operated and maintained long into the future. Recent researches also underpin the fact that the wide information gap existing between designers and building end-users is one of the factors responsible for the performance-gap. This paper therefore presents excerpts of a research aimed at exploring a best practice approach to operability and maintainability of low-carbon-buildings. The research methodology involved the use of interviews, surveys and case study. Findings suggest that a properly prepared O&M manual is a potential document that that could bridge this gap and that it is an indispensable tool for the effective and efficient operation and maintenance of low carbon buildings.