964 resultados para Quality engineering


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The risk of failure of the software development process remains high despite many attempts to improve the quality of software engineering. Contemporary approaches to process assurance, such as the capability maturity model have not prevented systemic failures, nor have project management methodologies provided guarantees of software quality. The paper proposes an approach to software quality assurance based on a knowledge mediated concurrent audit, which incorporates essential feedback processes. Through a tightly integrated approach to quality audit, programmers would be empowered to use any chosen methodology to advantage, supported by intelligent monitoring of the essential interactions which occur in the development process. An experimental application implementing some aspects of the proposal is described

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The accuracy and reliability of urban stormwater quality modelling outcomes are important for stormwater management decision making. The commonly adopted approach where only a limited number of factors are used to predict urban stormwater quality may not adequately represent the complexity of the quality response to a rainfall event or site-to-site differences to support efficient treatment design. This paper discusses an investigation into the influence of rainfall and catchment characteristics on urban stormwater quality in order to investigate the potential areas for errors in current stormwater quality modelling practices. It was found that the influence of rainfall characteristics on pollutant wash-off is step-wise based on specific thresholds. This means that a modelling approach where the wash-off process is predicted as a continuous function of rainfall intensity and duration is not appropriate. Additionally, other than conventional catchment characteristics, namely, land use and impervious surface fraction, other catchment characteristics such as impervious area layout, urban form and site specific characteristics have an important influence on both, pollutant build-up and wash-off processes. Finally, the use of solids as a surrogate to estimate other pollutant species was found to be inappropriate. Individually considering build-up and wash-off processes for each pollutant species should be the preferred option.

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Surface water and groundwater are the most important water sources in the natural environment. Land use and seasonal factors play an important role in influencing the quality of these water sources. An in-depth understanding of the role of these two influential factors can help to implement an effective catchment management strategy for the protection of these water sources. This paper discusses the outcomes of an extensive research study which investigated the role of land use and seasonal factors on surface water and groundwater pollution in a mixed land use coastal catchment. The study confirmed that the influence exerted on the water environment by seasonal factors is secondary to that of land use. Furthermore, the influence of land use and seasonal factors on surface water and groundwater quality varies with the pollutant species. This highlights the need to specifically take into consideration the targeted pollutants and the key influential factors for the effective protection of vulnerable receiving water environments.

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Urbanisation significantly changes the characteristics of a catchment as natural areas are transformed to impervious surfaces such as roads, roofs and parking lots. The increased fraction of impervious surfaces leads to changes to the stormwater runoff characteristics, whilst a variety of anthropogenic activities common to urban areas generate a range of pollutants such as nutrients, solids and organic matter. These pollutants accumulate on catchment surfaces and are removed and trans- ported by stormwater runoff and thereby contribute pollutant loads to receiving waters. In summary, urbanisation influences the stormwater characteristics of a catchment, including hydrology and water quality. Due to the growing recognition that stormwater pollution is a significant environmental problem, the implementation of mitigation strategies to improve the quality of stormwater runoff is becoming increasingly common in urban areas. A scientifically robust stormwater quality treatment strategy is an essential requirement for effective urban stormwater management. The efficient design of treatment systems is closely dependent on the state of knowledge in relation to the primary factors influencing stormwater quality. In this regard, stormwater modelling outcomes provide designers with important guidance and datasets which significantly underpin the design of effective stormwater treatment systems. Therefore, the accuracy of modelling approaches and the reliability modelling outcomes are of particular concern. This book discusses the inherent complexity and key characteristics in the areas of urban hydrology and stormwater quality, based on the influence exerted by a range of rainfall and catchment characteristics. A comprehensive field sampling and testing programme in relation to pollutant build-up, an urban catchment monitoring programme in relation to stormwater quality and the outcomes from advanced statistical analyses provided the platform for the knowledge creation. Two case studies and two real-world applications are discussed to illustrate the translation of the knowledge created to practical use in relation to the role of rainfall and catchment characteristics on urban stormwater quality. An innovative rainfall classification based on stormwater quality was developed to support the effective and scientifically robust design of stormwater treatment systems. Underpinned by the rainfall classification methodology, a reliable approach for design rainfall selection is proposed in order to optimise stormwater treatment based on both, stormwater quality and quantity. This is a paradigm shift from the common approach where stormwater treatment systems are designed based solely on stormwater quantity data. Additionally, how pollutant build-up and stormwater runoff quality vary with a range of catchment characteristics was also investigated. Based on the study out- comes, it can be concluded that the use of only a limited number of catchment parameters such as land use and impervious surface percentage, as it is the case in current modelling approaches, could result in appreciable error in water quality estimation. Influential factors which should be incorporated into modelling in relation to catchment characteristics, should also include urban form and impervious surface area distribution. The knowledge created through the research investigations discussed in this monograph is expected to make a significant contribution to engineering practice such as hydrologic and stormwater quality modelling, stormwater treatment design and urban planning, as the study outcomes provide practical approaches and recommendations for urban stormwater quality enhancement. Furthermore, this monograph also demonstrates how fundamental knowledge of stormwater quality processes can be translated to provide guidance on engineering practice, the comprehensive application of multivariate data analyses techniques and a paradigm on integrative use of computer models and mathematical models to derive practical outcomes.

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Process variability in pollutant build-up and wash-off generates inherent uncertainty that affects the outcomes of stormwater quality models. Poor characterisation of process variability constrains the accurate accounting of the uncertainty associated with pollutant processes. This acts as a significant limitation to effective decision making in relation to stormwater pollution mitigation. The study undertaken developed three theoretical scenarios based on research findings that variations in particle size fractions <150µm and >150µm during pollutant build-up and wash-off primarily determine the variability associated with these processes. These scenarios, which combine pollutant build-up and wash-off processes that takes place on a continuous timeline, are able to explain process variability under different field conditions. Given the variability characteristics of a specific build-up or wash-off event, the theoretical scenarios help to infer the variability characteristics of the associated pollutant process that follows. Mathematical formulation of the theoretical scenarios enables the incorporation of variability characteristics of pollutant build-up and wash-off processes in stormwater quality models. The research study outcomes will contribute to the quantitative assessment of uncertainty as an integral part of the interpretation of stormwater quality modelling outcomes.

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Uncertainty inherent to heavy metal build-up and wash-off stems from process variability. This results in inaccurate interpretation of stormwater quality model predictions. The research study has characterised the variability in heavy metal build-up and wash-off processes based on the temporal variations in particle-bound heavy metals commonly found on urban roads. The study outcomes found that the distribution of Al, Cr, Mn, Fe, Ni, Cu, Zn, Cd and Pb were consistent over particle size fractions <150µm and >150µm, with most metals concentrated in the particle size fraction <150µm. When build-up and wash-off are considered as independent processes, the temporal variations in these processes in relation to the heavy metals load are consistent with variations in the particulate load. However, the temporal variations in the load in build-up and wash-off of heavy metals and particulates are not consistent for consecutive build-up and wash-off events that occur on a continuous timeline. These inconsistencies are attributed to interactions between heavy metals and particulates <150µm and >150µm, which are influenced by particle characteristics such as organic matter content. The behavioural variability of particles determines the variations in the heavy metals load entrained in stormwater runoff. Accordingly, the variability in build-up and wash-off of particle-bound pollutants needs to be characterised in the description of pollutant attachment to particulates in stormwater quality modelling. This will ensure the accounting of process uncertainty, and thereby enhancing the interpretation of the outcomes derived from modelling studies.

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The discussion of possible scenarios for the future of Quality is on the priority list of major Quality Practitioners Societies. EOQ – European Organization for Quality (EOQ, 2014) main team for its 58th EOQ-Congress held June 2014 in Göteborg was “Managing Challenges in Quality Leadership” and ASQ - American Society for Quality (ASQ, 2015) appointed “the Future of Quality” for Quality Progress Magazine November 2015 issue. In addition, the ISO 9001:2008 revision process carried by ISO/TC 176 aims to assure that ISO 9001:2015 International Standard remains stable for the next 10 years (ISO, 2014) contributing to an increased discussion on the future of quality. The purpose of this research is to review available Quality Management approaches and outline, adding an academic perspective, expected developments for Quality within the 21st Century. This paper follows a qualitative approach, although data from international organizations is used. A literature review has been undertaken on quality management past and potential future trends. Based on these findings a model is proposed for organization quality management development and propositions for the future of quality management are advanced. Firstly, a state of the art of existing Quality Management approaches is presented, for example, like Total Quality Management (TQM) and Quality Gurus, ISO 9000 International Standards Series (with an outline of the expected changes for ISO 9001:2015), Six Sigma and Business Excellence Models.Secondly, building on theoretical and managerial approaches, a two dimensional matrix – Quality Engineering (QE - technical aspects of quality) and Quality Management (QM: soft aspects of quality) - is presented, outlining five proposed characterizations of Quality maturity levels and giving insights for applications and future developments. Literature review highlights that QM and QE may be addressing similar quality issues but their approaches are different in terms of scope breadth and intensity and they ought to complement and reciprocally reinforce one another. The challenges organizations face within the 21st century have stronger uncertainty, complexity, and differentiation. Two main propositions are advanced as relevant for 21st Century Quality: - QM importance for the sustainable success of organizations will increase and they should be aware of the larger ecosystem to be managed for improvement, possibly leading to the emergence of a new Quality paradigm, The Civilizacional Excellence paradigm. - QE should get more attention from QM and the Quality professionals will have to: a) Master and apply in wider contexts and in additional depth the Quality Tools (basic, intermediate and advanced); b) Have the soft skills needed for its success; c) Be results oriented and better understand and demonstrate the relationships between approaches and results These propositions challenge both scholars and practitioners for a sustained and supported discussion on the future of Quality. “All things are ready, if our mind be so.” (Shakespeare, Henry V, circa 1599).

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The business philosophy of Mass Customisation (MC) implies rapid response to customer requests, high efficiency and limited cost overheads of customisation. Furthermore, it also implies the quality benefits of the mass production paradigm are guaranteed. However, traditional quality science in manufacturing is premised on volume production of uniform products rather than of differentiated products associated with MC. This creates quality challenges and raises questions over the suitability of standard quality engineering techniques. From an analysis of relevant MC and quality literature it is argued the aims of MC are aligned with contemporary thinking on quality and that quality concepts provide insights into MC. Quality issues are considered along three dimensions - product development, order fulfilment and customer interaction. The applicability and effectiveness of conventional quality engineering techniques are discussed and a framework is presented which identifies key issues with respect to quality for a spectrum of MC strategies.

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International audience

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Quality management provides to companies a framework to improve quality in overall systems, reduction of costs, reallocation of resources efficiently, correct planning of strategies, prevent or correct errors in the right time and increase the performance of companies. In this text, we discuss the different theories in this field, their obligatory or non-obligatory compliance, the importance of quality management for exporting companies and a case study of a Colombian firm that its main objective is to manage quality. In conclusion, we find out that there is different types of quality management systems such as Juran’s trilogy, Deming 14 points, Six sigma, HACCP, and so on; also that companies have to manage suppliers and that quality has a positive influence on exports volume; in the case of Colombian small and medium enterprises, it can be mentioned that the majority has implemented tools regarding quality management but is not enough.

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The relationship between the themes of Total Quality Management (TQM) and Social Responsibility (CSR) through the concepts, approaches and models of excellence is a reality of sustainable and stable companies. Being organizations, people, act correctly and rightly do in society go through a quality management and social responsibility thereof. It is based on these two philosophies (Total Quality Management and Corporate Social Responsibility), which developed this literature review work, essentially based on a relational analysis in two papers, namely: "TQM and CSR Nexus" by Ghobadian et al. (2007) and "The Corporate Social Responsibility Audit Within the Quality Management Framework," de Kok et al. (2001) and applied to an organizational situation in concrete: the Nabeiro Delta Cafés Group - SGPS, SA.