906 resultados para Process capability analysis


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This paper investigates relationship between traffic conditions and the crash occurrence likelihood (COL) using the I-880 data. To remedy the data limitations and the methodological shortcomings suffered by previous studies, a multiresolution data processing method is proposed and implemented, upon which binary logistic models were developed. The major findings of this paper are: 1) traffic conditions have significant impacts on COL at the study site; Specifically, COL in a congested (transitioning) traffic flow is about 6 (1.6) times of that in a free flow condition; 2)Speed variance alone is not sufficient to capture traffic dynamics’ impact on COL; a traffic chaos indicator that integrates speed, speed variance, and flow is proposed and shows a promising performance; 3) Models based on aggregated data shall be interpreted with caution. Generally, conclusions obtained from such models shall not be generalized to individual vehicles (drivers) without further evidences using high-resolution data and it is dubious to either claim or disclaim speed kills based on aggregated data.

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In this conceptual article, we extend earlier work on Open Innovation and Absorptive Capacity. We suggest that the literature on Absorptive Capacity does not place sufficient emphasis on distributed knowledge and learning or on the application of innovative knowledge. To accomplish physical transformations, organisations need specific Innovative Capacities that extend beyond knowledge management. Accessive Capacity is the ability to collect, sort and analyse knowledge from both internal and external sources. Adaptive Capacity is needed to ensure that new pieces of equipment are suitable for the organisation's own purposes even though they may have been originally developed for other uses. Integrative Capacity makes it possible for a new or modified piece of equipment to be fitted into an existing production process with a minimum of inessential and expensive adjustment elsewhere in the process. These Innovative Capacities are controlled and coordinated by Innovative Management Capacity, a higher-order dynamic capability.

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Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using Intra-class Correlation Coefficient (ICC) and Deviance Information Criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time, in good street lighting condition, involving pedestrian injuries are associated with a lower severity, while those in night time, at T/Y type intersections, on right-most lane, and installed with red light camera have larger odds of being severe. Moreover, heavy vehicles have a better resistance on severe crash, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries.

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Denaturation of tissues can provide a unique biological environment for regenerative medicine application only if minimal disruption of their microarchitecture is achieved during the decellularization process. The goal is to keep the structural integrity of such a construct as functional as the tissues from which they were derived. In this work, cartilage-on-bone laminates were decellularized through enzymatic, non-ionic and ionic protocols. This work investigated the effects of decellularization process on the microarchitecture of cartiligous extracellular matrix; determining the extent of how each process deteriorated the structural organization of the network. High resolution microscopy was used to capture cross-sectional images of samples prior to and after treatment. The variation of the microarchitecture was then analysed using a well defined fast Fourier image processing algorithm. Statistical analysis of the results revealed how significant the alternations among aforementioned protocols were (p < 0.05). Ranking the treatments by their effectiveness in disrupting the ECM integrity, they were ordered as: Trypsin> SDS> Triton X-100.

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Most approaches to business process compliance are restricted to the analysis of the structure of processes. It has been argued that full regulatory compliance requires information on not only the structure of processes but also on what the tasks in a process do. To this end Governatori and Sadiq[2007] proposed to extend business processes with semantic annotations. We propose a methodology to automatically extract one kind of such annotations; in particular the annotations related to the data schema and templates linked to the various tasks in a business process.

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In this paper, a class of fractional advection–dispersion models (FADMs) is considered. These models include five fractional advection–dispersion models, i.e., the time FADM, the mobile/immobile time FADM with a time Caputo fractional derivative 0 < γ < 1, the space FADM with two sides Riemann–Liouville derivatives, the time–space FADM and the time fractional advection–diffusion-wave model with damping with index 1 < γ < 2. These equations can be used to simulate the regional-scale anomalous dispersion with heavy tails. We propose computationally effective implicit numerical methods for these FADMs. The stability and convergence of the implicit numerical methods are analysed and compared systematically. Finally, some results are given to demonstrate the effectiveness of theoretical analysis.

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Data mining techniques extract repeated and useful patterns from a large data set that in turn are utilized to predict the outcome of future events. The main purpose of the research presented in this paper is to investigate data mining strategies and develop an efficient framework for multi-attribute project information analysis to predict the performance of construction projects. The research team first reviewed existing data mining algorithms, applied them to systematically analyze a large project data set collected by the survey, and finally proposed a data-mining-based decision support framework for project performance prediction. To evaluate the potential of the framework, a case study was conducted using data collected from 139 capital projects and analyzed the relationship between use of information technology and project cost performance. The study results showed that the proposed framework has potential to promote fast, easy to use, interpretable, and accurate project data analysis.

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Purpose – In the context of global knowledge economy, knowledge-based urban development (KBUD) is seen as an effective development strategy for city-regions to survive, flourish and become highly competitive urban agglomerations – i.e., a knowledge city-region. This paper aims to evaluate the KBUD dynamics, capacity and potentials of a rapidly emerging knowledge city-region of Finland – Tampere region. Design/methodology/approach – The paper undertakes a review of the literature on regional development in the knowledge economy era. It adopts a qualitative analysis technique to scrutinize the dynamics, capacity and potentials of Tampere region. The semi-structured interview process starts with the pre-determined key actors of the city-region with an aim of determining the other key players. Next, with the participation of all key players to the interviews, the research reveals the principal issues, assets and mechanisms that relate to KBUD, and portrays the strengths, weaknesses, opportunities and threats of the city-region. A critical analysis of the findings along with the previous studies is undertaken to provide a clear picture of the dynamics, capacity and potentials of the emerging knowledge city-region. Originality/value – This paper reports the findings of a pioneering study focusing on the investigation of the KBUD dynamics, capacity and potentials of Tampere region. The paper critically evaluates the city-region from the knowledge perspective with the lens of KBUD, and the lessons learned and the methodological approach of the paper shed light to other city-regions seeking such development. Practical implications – The paper discusses the findings of a study from Tampere region that critically scrutinizes the KBUD experience of the city-region. The research provides an invaluable opportunity to inform the regional decision-, policy- and plan-making mechanisms by determining key issues, actors, assets, processes and potential development directions for the KBUD of Tampere region.

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Business process management (BPM) is becoming the dominant management paradigm. Business process modelling is central to BPM, and the resultant business process model the core artefact guiding subsequent process change. Thus, model quality is at the centre, mediating between the modelling effort and related growing investment in ultimate process improvements. Nonetheless, though research interest in the properties that differentiate high quality process models is longstanding, there have been no past reports of a valid, operationalised, holistic measure of business process model quality. In attention to this gap, this paper reports validation of a Business Process Model Quality measurement model, conceptualised as a single-order, formative index. Such a measurement model has value as the dependent variable in rigorously researching the drivers of model quality; as antecedent of ultimate process improvements; and potentially as an economical comparator and diagnostic for practice.

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The demand for Business Process Management (BPM) is rapidly rising and with that, the need for capable BPM professionals is also rising. Yet, only a very few structured BPM training/ education programs are available, across universities and professional trainers globally. The ‘lack of appropriate teaching resources’ has been identified as a critical issue for BPM educators in prior studies. Case-based teaching can be an effective means of educating future BPM professionals. A main reason is that cases create an authentic learning environment where the complexities and challenges of the ‘real world’ can be presented in a narrative enabling the students to develop crucial skills such as problem solving, analysis and creativity-within-constraints, and to apply the tools and techniques within a richer and real (or proxy to real) context. However, so far well documented BPM teaching cases are scarce. This article aims to contribute to address this gap by providing a comprehensive teaching case and teaching notes that facilitates the education of selected process improvement phases, namely identification, modelling, analysis, and improvement. The article is divided into three main parts: (i) Introductory teaching notes, (ii) The case narrative, and (iii) Student activities from the case and teaching notes.

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There is an increased interested in Uninhabited Aerial Vehicle (UAV) operations and research into advanced methods for commanding and controlling multiple heterogeneous UAVs. Research into areas of supervisory control has rapidly increased. Past research has investigated various approaches of autonomous control and operator limitation to improve mission commanders' Situation Awareness (SA) and cognitive workload. The aim of this paper is to address this challenge through a visualisation framework of UAV information constructed from Information Abstraction (IA). This paper presents the concept and process of IA, and the visualisation framework (constructed using IA), the concept associated with the Level Of Detail (LOD) indexing method, the visualisation of an example of the framework. Experiments will test the hypothesis that, the operator will be able to achieve increased SA and reduced cognitive load with the proposed framework.

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Peeling is an essential phase of post harvesting and processing industry; however undesirable processing losses are unavoidable and always have been the main concern of food processing sector. There are three methods of peeling fruits and vegetables including mechanical, chemical and thermal, depending on the class and type of fruit. By comparison, the mechanical methods are the most preferred; mechanical peeling methods do not create any harmful effects on the tissue and they keep edible portions of produce fresh. The main disadvantage of mechanical peeling is the rate of material loss and deformations. Obviously reducing material losses and increasing the quality of the process has a direct effect on the whole efficiency of food processing industry, this needs more study on technological aspects of these operations. In order to enhance the effectiveness of food industrial practices it is essential to have a clear understanding of material properties and behaviour of tissues under industrial processes. This paper presents the scheme of research that seeks to examine tissue damage of tough skinned vegetables under mechanical peeling process by developing a novel FE model of the process using explicit dynamic finite element analysis approach. A computer model of mechanical peeling process will be developed in this study to stimulate the energy consumption and stress strain interactions of cutter and tissue. The available Finite Element softwares and methods will be applied to establish the model. Improving the knowledge of interactions and involves variables in food operation particularly in peeling process is the main objectives of the proposed study. Understanding of these interrelationships will help researchers and designer of food processing equipments to develop new and more efficient technologies. Presented work intends to review available literature and previous works has been done in this area of research and identify current gap in modelling and simulation of food processes.

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In managing their operations, organizations have traditionally focused on economic imperatives in terms of time, cost, efficiency, and quality. In doing so, they have been a major contributor to environmental degradation caused by re-source consumption, greenhouse emissions, and wastage. As a consequence, or-ganizations are increasingly encouraged to improve their operations also from an ecological perspective, and thus to consider environmental sustainability as an additional management imperative. In order to lessen their impact on the natural environment, organizations must design and implement environmentally sustainable processes, which we call the challenge of Green Business Process Management (Green BPM). This chapter elaborates on the challenge and perspec-tive of Green BPM, and explores the contributions that business process management can provide to creating environmentally sustainable organizations. Our key premise is that business as well as information technology managers need to engage in a process-focused discussion to enable a common, comprehensive understanding of organizational processes, and the process-centered opportunities for making these processes, and ultimately the organization as a process-centric entity, “green.” Through our review of the key BPM capability areas and how they can be framed in terms of environmental sustainability considerations, we provide an overview and introduction to the subsequent chapters in this book.

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Non-profit organisations by their very nature are staffed by a variety of different people with a range of backgrounds, experiences and reasons for participation. These differences can lead to “distancing” of certain groups and with little time or money for boundary spanning the organisation can find itself in a fractured state that hampers not just its goal realisation, but its goal determination. Strategic planning is often seen as an expensive, time consuming process that many smaller non-profit organisations can little afford to indulge in. In addition, the ruling elite, whether historical or professional may view the process as unnecessary or threatening. However, strategic planning can offer processes and potential outcomes that non profit organisations can not afford to ignore. This paper provides an analysis through one case study involving a non-profit, health related organisation that moved through a process of strategic planning that ultimately encouraged development and group cohesion through goal identification and determination as well as strategy formulation. The results indicate the importance of valuing the strategic planning process itself rather than the form it takes. Challenging the rulership of the historical or professional elite can be difficult in a non-profit organisation, but diversity of involvement rather than uniformity proved to be a successful strategy. Organisational cohesion through consensus building was the ultimate outcome.