853 resultados para Business Process Management, BPM life cycle, quality, root cause analysis


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Despite of significant contributions of urban road transport to global economy and society, it is one of the largest sources of local and global emission impact. In order to address the environmental concerns of urban road transport it is imperative to achieve a holistic understanding of contributory factors causing emissions which requires a complete look onto its whole life cycle. Previous studies were mainly based on segmental views which mostly studied environmental impacts of individual transport modes and very few considered impacts other than operational phase. This study develops an integrated life cycle inventory model for urban road transport emissions from a holistic modal perspective. Singapore case was used to demonstrate the model. Results show that total life cycle greenhouse gas emission from Singapore’s road transport sector is 7.8 million tons per year. The total amount of criteria air pollutants are also estimated in this study.

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This thesis addresses the process simulation and validation in Business Process Management. It proposes that the hybrid Multi Agent System (MAS) / 3D Virtual World approach is a valid method for better simulating the behaviour of human resources in business processes, supporting a wide range of rich visualization applications that can facilitate communication between business analysts and stakeholders. It is expected that the findings of this thesis may be fruitfully extended from BPM to other application domains, such as social simulation in video games and computer-based training animations.

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Purpose – The purpose of this paper is to develop an effective methodology for implementing lean manufacturing strategies and a leanness evaluation metric using continuous performance measurement (CPM). Design/methodology/approach – Based on five lean principles, a systematic lean implementation methodology for manufacturing organizations has been proposed. A simplified leanness evaluation metric consisting of both efficiency and effectiveness attributes of manufacturing performance has been developed for continuous evaluation of lean implementation. A case study to validate the proposed methodology has been conducted and proposed CPM metric has been used to assess the manufacturing leanness. Findings – Proposed methodology is able to systematically identify manufacturing wastes, select appropriate lean tools, identify relevant performance indicators, achieve significant performance improvement and establish lean culture in the organization. Continuous performance measurement matrices in terms of efficiency and effectiveness are proved to be appropriate methods for continuous evaluation of lean performance. Research limitations/implications – Effectiveness of the method developed has been demonstrated by applying it in a real life assembly process. However, more tests/applications will be necessary to generalize the findings. Practical implications – Results show that applying the methods developed, managers can successfully identify and remove manufacturing wastes from their production processes. By improving process efficiency, they can optimize their resource allocations. Manufacturers now have a validated step by step methodology for successfully implementing lean strategies. Originality/value – According to the authors’ best knowledge, this is the first known study that proposed a systematic lean implementation methodology based on lean principles and continuous improvement techniques. Evaluation of performance improvement by lean strategies is a critical issue. This study develops a simplified leanness evaluation metric considering both efficiency and effectiveness attributes and integrates it with the lean implementation methodology.

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Process improvement has become a number one business priority, and more and more project requests are raised in organizations, seeking approval and resources for process-related projects. Realistically, the total of the requested funds exceeds the allocated budget, the number of projects is higher than the available bandwidth, and only some of these (very often only few) can be supported and most never see any light. Relevant resources are scarce, and correct decisions must be made to make sure that those projects that are of best value are implemented. How can decision makers make the right decision on the following: Which project(s) are to be approved and when to commence work on them? Which projects are most aligned with corporate strategy? How can the project’s value to the business be calculated and explained? How can these decisions be made in a fair, justifiable manner that brings the best results to the company and its stakeholders? This chapter describes a business value scoring (BVS) model that was built, tested, and implemented by a leading financial institution in Australia to address these very questions. The chapter discusses the background and motivations for such an initiative and describes the tool in detail. All components and underlying concepts are explained, together with details on its application. This tool has been successfully implemented in the case organization. The chapter provides practical guidelines for organizations that wish to adopt this approach.

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Process mining has developed into a popular research discipline and nowadays its associated techniques are widely applied in practice. What is currently ill-understood is how the success of a process mining project can be measured and what the antecedent factors of process mining success are. We consider an improved, grounded understanding of these aspects of value to better manage the effectiveness and efficiency of process mining projects in practice. As such, we advance a model, tailored to the characteristics of process mining projects, which identifies and relates success factors and measures. We draw inspiration from the literature from related fields for the construction of a theoretical, a priori model. That model has been validated and re-specified on the basis of a multiple case study, which involved four industrial process mining projects. The unique contribution of this paper is that it presents the first set of success factors and measures on the basis of an analysis of real process mining projects. The presented model can also serve as a basis for further extension and refinement using insights from additional analyses.

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The advances made within the aviation industry over the past several decades have significantly improved the availability, affordability and convenience of air travel and have been greatly beneficial in both social and economic terms. Air transport has developed into an irreplaceable service being relied on by millions of people each day and as such airports have become critical elements of national infrastructure to facilitate the movement of people and goods. As components of critical infrastructure (CI), airports are integral parts of a national economy supporting regional as well as national trade, commercial activity and employment. Therefore, any disruption or crisis which impacts the continuity of operations at airports can have significant negative consequences for the airport as a business, for the local economy and other nodes of transport infrastructure as well as for society. Due to the highly dynamic and volatile environment in which airports operate in, the aviation industry has faced many different challenges over the years ranging from terrorist attacks such as September 11, to health crises such as the SARS epidemic to system breakdowns such as the recent computer system outage at Virgin Blue Airlines in Australia. All these events have highlighted the vulnerability of airport systems to a range of disturbances as well as the gravity and widespread impact of any kind of discontinuity in airport functions. Such incidents thus emphasise the need for increasing resilience and reliability of airports and ensuring business continuity in the event of a crisis...

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This thesis presents novel techniques for addressing the problems of continuous change and inconsistencies in large process model collections. The developed techniques treat process models as a collection of fragments and facilitate version control, standardization and automated process model discovery using fragment-based concepts. Experimental results show that the presented techniques are beneficial in consolidating large process model collections, specifically when there is a high degree of redundancy.

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In the last years, the trade-o between exibility and sup- port has become a leading issue in work ow technology. In this paper we show how an imperative modeling approach used to de ne stable and well-understood processes can be complemented by a modeling ap- proach that enables automatic process adaptation and exploits planning techniques to deal with environmental changes and exceptions that may occur during process execution. To this end, we designed and imple- mented a Custom Service that allows the Yawl execution environment to delegate the execution of subprocesses and activities to the SmartPM execution environment, which is able to automatically adapt a process to deal with emerging changes and exceptions. We demonstrate the fea- sibility and validity of the approach by showing the design and execution of an emergency management process de ned for train derailments.

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Process Modeling is a widely used concept for understanding, documenting and also redesigning the operations of organizations. The validation and usage of process models is however affected by the fact that only business analysts fully understand them in detail. This is in particular a problem because they are typically not domain experts. In this paper, we investigate in how far the concept of verbalization can be adapted from object-role modeling to process models. To this end, we define an approach which automatically transforms BPMN process models into natural language texts and combines different techniques from linguistics and graph decomposition in a flexible and accurate manner. The evaluation of the technique is based on a prototypical implementation and involves a test set of 53 BPMN process models showing that natural language texts can be generated in a reliable fashion.

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This paper addresses the problem of transforming a process model with an arbitrary topology into an equivalent well-structured process model. While this problem has received significant attention, there is still no full characterization of the class of unstructured process models that can be transformed into well-structured ones, nor an automated method to structure any process model that belongs to this class. This paper fills this gap in the context of acyclic process models. The paper defines a necessary and sufficient condition for an unstructured process model to have an equivalent structured model under fully concurrent bisimulation, as well as a complete structuring method.

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Companies use business process models to represent their working procedures in order to deploy services to markets, to analyze them, and to improve upon them. Competitive markets necessitate complex procedures, which lead to large process specifications with sophisticated structures. Real world process models can often incorporate hundreds of modeling constructs. While a large degree of detail complicates the comprehension of the processes, it is essential to many analysis tasks. This paper presents a technique to abstract, i.e., to simplify process models. Given a detailed model, we introduce abstraction rules which generalize process fragments in order to bring the model to a higher abstraction level. The approach is suited for the abstraction of large process specifications in order to aid model comprehension as well as decomposing problems of process model analysis. The work is based on process structure trees that have recently been introduced to the field of business process management.

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Process models are usually depicted as directed graphs, with nodes representing activities and directed edges control flow. While structured processes with pre-defined control flow have been studied in detail, flexible processes including ad-hoc activities need further investigation. This paper presents flexible process graph, a novel approach to model processes in the context of dynamic environment and adaptive process participants’ behavior. The approach allows defining execution constraints, which are more restrictive than traditional ad-hoc processes and less restrictive than traditional control flow, thereby balancing structured control flow with unstructured ad-hoc activities. Flexible process graph focuses on what can be done to perform a process. Process participants’ routing decisions are based on the current process state. As a formal grounding, the approach uses hypergraphs, where each edge can associate any number of nodes. Hypergraphs are used to define execution semantics of processes formally. We provide a process scenario to motivate and illustrate the approach.

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Road infrastructure has been considered as one of the most expensive and extensive infrastructure assets of the built environment globally. This asset also impacts the natural environment significantly during different phases of life e.g. construction, use, maintenance and end-of-life. The growing emphasis for sustainable development to meet the needs of future generations requires mitigation of the environmental impacts of road infrastructure during all phases of life e.g. construction, operation and end-of-life disposal (as required). Life-cycle analysis (LCA), a method of quantification of all stages of life, has recently been studied to explore all the environmental components of road projects due to limitations of generic environmental assessments. The LCA ensures collection and assessment of the inputs and outputs relating to any potential environmental factor of any system throughout its life. However, absence of a defined system boundary covering all potential environmental components restricts the findings of the current LCA studies. A review of the relevant published LCA studies has identified that environmental components such as rolling resistance of pavement, effect of solar radiation on pavement(albedo), traffic congestion during construction, and roadway lighting & signals are not considered by most of the studies. These components have potentially higher weightings for environment damage than several commonly considered components such as materials, transportation and equipment. This paper presents the findings of literature review, and suggests a system boundary model for LCA study of road infrastructure projects covering potential environmental components.

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This thesis investigated both the potential for Business Continuity Management to enhance organisational reliability, and appropriate levels of Business Continuity Management capability resident in a number of Australian international and regional airports. Findings indicated that a host of regulatory and business processes including Business Continuity Management can assist in creating reliability in aviation infrastructure systems in Australia. Further, the thesis developed a multi-level maturity assessment framework for defining the depth of implementation of Business Continuity Management capabilities in airports, along with other recommendations to improve functional reliability of airport operations.

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This paper evaluates the suitability of sequence classification techniques for analyzing deviant business process executions based on event logs. Deviant process executions are those that deviate in a negative or positive way with respect to normative or desirable outcomes, such as non-compliant executions or executions that undershoot or exceed performance targets. We evaluate a range of feature types and classification methods in terms of their ability to accurately discriminate between normal and deviant executions both when deviances are infrequent (unbalanced) and when deviances are as frequent as normal executions (balanced). We also analyze the ability of the discovered rules to explain potential causes and contributing factors of observed deviances. The evaluation results show that feature types extracted using pattern mining techniques only slightly outperform those based on individual activity frequency. The results also suggest that more complex feature types ought to be explored to achieve higher levels of accuracy.