O gerenciamento de processos de negócio (BPM – Business Process Management) é uma abordagem estruturada que apoia as empresas a melhorar os seus processos fundamentais, dentre os quais se destaca o processo de desenvolvimento de produtos (PDP). Entretanto, a literatura é escassa de uma orientação sistêmica para guiar a seleção de ações de melhoria para o PDP de modo que se considere os objetivos estratégicos do processo. O foco das ações, geralmente, é somente em superar as deficiências relativas à situação atual. O objetivo da presente pesquisa é desenvolver um método de seleção de ações de melhoria para o PDP que contemple tanto o diagnóstico da situação atual quanto a situação futura desejada para o processo. A abordagem metodológica denominada Design Research Methodology (DRM) é utilizada para conduzir o desenvolvimento da pesquisa, e dois estudos de caso foram aplicados para avaliar a aplicação do método. Ele é constituído por quatro etapas correspondendo à definição dos objetivos estratégicos, a análise dos problemas que ocorrem no PDP, a avaliação das ações de melhoria, e a priorização delas de acordo com os prazos no horizonte de tempo, a complexidade e os recursos envolvidos para implementá-las. A proposta ainda utiliza as boas práticas do PDP para proposição das ações de melhoria, e aplica o processo de roadmapping para o mapeamento, seleção e priorização das ações. A novidade é a integração dos objetivos estratégicos do PDP em programas de melhoria, estendendo o modelo de melhoria tradicional associado à abordagem BPM. Os resultados da aplicação do método indicam que ele apresenta-se como estímulo para as empresas alcançarem o alinhamento estratégico no PDP e buscarem por novas práticas gerenciais e técnicas em prol da melhoria do desempenho desse processo. / The Business Process Management (BPM) is a structured approach that supports companies to improve their core processes, among which stands out the new product development (NPD). However, the literature is scarce of a systemic orientation to guide the selection of improvement actions for NPD in order to consider the strategic objectives of the process. Usually the focus of actions is only on overcoming shortcomings relative to the current situation. The aim of this research is to develop a method of selecting improvement actions for NPD that considers both the diagnosis of the current situation and the future situation desired for the process. The methodological approach called Design Research Methodology (DRM) is used to drive the development of the research, and two case studies were applied to evaluate the application of the method. It consists of four stages, which are the definition of the strategic objectives, the analysis of the problems that occur in NPD, the evaluation of improvement actions, and the prioritization of them in accordance with the time, the complexity of the actions and the resources involved to implement them. This proposal also uses the NPD good practices to define the improvement actions, and applies the roadmapping for mapping, selecting and prioritizing the actions. The novelty of the method is the integration of the NPD\'s strategic objectives into improvement programs, extending the traditional improvement model associated with the BPM approach. The results of the application of the method indicate that it is a stimulus for the companies to reach the strategic alignment in the PDP and to apply new managerial and technical practices in order to improve the performance of the process.

Mineração de processos é um novo campo de pesquisa que liga mineração de dados e gestão de processos de negócio. A mineração de processos segue a premissa de que existe um processo desconhecido em um determinado contexto, e que ao analisar os traços do seu comportamento, com o auxílio da mineração de dados, é possível descobrir o modelo do processo. No entanto, processos de negócio realistas são difíceis de minerar por causa do excesso de comportamento registrado nos logs. Esses processos não estruturados, apesar de complexos, possuem um potencial grande para melhoria, sendo que as abordagens atuais de mineração de processos para esse contexto ainda provém pouco suporte à gestão. Este trabalho de pesquisa de mestrado visou aplicar técnicas computacionais evolutivas na mineração de modelos de processo, usando algoritmos genéticos para descobrir automaticamente modelos de processos não estruturados visando dar suporte à gestão organizacional de processos. Uma revisão da literatura foi realizada para auxiliar a proposição de uma nova abordagem focada na descoberta de modelos de processos não estruturados. A abordagem proposta introduz novas fórmulas de cálculo das métricas de completude e precisão baseadas nas informações de transições entre atividades, reorganizadas por meio de uma estrutura de matriz criada neste trabalho. A abordagem introduz também o uso de operadores genéticos e estratégias de fluxo evolutivo ainda não implementados na literatura relativa a algoritmos genéticos na descoberta de processos. Análises da parametrização da abordagem proposta, bem como os modelos de processos resultantes, indicam que a abordagem é eficaz na mineração de modelos de processos melhores a partir de amostras de um log não estruturado / Process mining is a new field of research that links data mining and business process management. Process mining follows the premise that there is an unknown process in a given context, and by analyzing the traces of its behavior, with the help of data mining, the process model can be discovered. However, realistic business processes are difficult to mine because of excessive behavior recorded in the logs. These unstructured processes, despite being complex, hold great potential for improvement, and the current process mining approaches for that context yet provide little support for management. This masters research project aims to apply evolutionary computational techniques in process mining, using genetic algorithms to automatically discover unstructured process models in order to support process management in organizations. A literature review was carried out to support the proposition of a new approach focused on the discovery of unstructured process models. The proposed approach introduces new formulas for calculating completeness and precision metrics, based on the information of transitions between activities that are reorganized through a matrix structure created in this work. The approach also introduces the use of genetic operators and evolutionary flow strategies not yet implemented in the literature regarding genetic algorithms in process discovery. Analyzes of the parameterization of the proposed approach, as well as the resulting process models, indicate that the approach is effective in mining better process models from samples of a unstructured log

Linha de Produto de Software (LP) é uma forma sistemática de promover a geração de produtos de software específicos baseados no reúso de uma infraestrutura bem definida. Conceitos de LP aplicados ao domínio de Gestão de Processos de Negócio (BPM - Business Process Management) já apresentaram resultados significativos, entretanto, o escopo de aplicação e os benefícios ainda são limitados. Essas limitações ocorrem, pois as abordagens de LP já existentes para BPM normalmente não cobrem todo o ciclo de vida de processos de negócio e não oferecem o devido tratamento aos aspectos dinâmicos que as organizações demandam para esse domínio. Linha de Produto de Software Dinâmica (LPD) é uma evolução das LPs tradicionais que tem proporcionado uma forma eficiente para lidar com adaptações de produtos em tempo de execução. LPDs podem ser aplicadas, por exemplo, no contexto de arquiteturas SOA (Service-oriented Architecture), que por sua vez podem ser usadas como base tecnológica para viabilizar BPM nas organizações. Dentro desse contexto, este trabalho propõe uma abordagem de LPD para atender as necessidades de organizações interessadas em realizar processos de negócio, por meio de um alinhamento entre conceitos de BPM e SOA. A abordagem proposta aqui, denominada Dynamic Product Line for Business Process Management (DynPL4BPM), visa ser abrangente o suficiente para cobrir todo o ciclo de vida de BPM, sendo previsto o tratamento de aspectos dinâmicos que o domínio de BPM requer. Uma avaliação sistemática e comparativa demonstrou que a abordagem proposta é bem sucedida em apresentar processos bem mais abrangentes que outras soluções similares já propostas na literatura para o mesmo fim. / Software Product Line (PL) is a systematic way to promote the generation of specific software products based on the reuse of a well-defined infrastructure. Concepts of PL applied to Business Process Management (BPM) have already presented significant results; however, the application scope and benefits are still limited. These limitations occur because the existing approaches of LP for BPM usually do not cover the entire lifecycle of business processes and do not provide proper treatment to the dynamic aspects that organizations demand for this domain. Dynamic Software Product Line (DPL) is an evolution of traditional PLs that has provided an efficient way to deal with adaptations of products at runtime. DPLs can be applied, for example, in the SOA (Service-oriented Architecture) context, which in turn can be used as technological basis to enable BPM within organizations. Within this context, this dissertation proposes a DPL approach to meet the needs of organizations interested in carrying out business processes by means of an alignment between BPM and SOA concepts. The approach proposed here, called Dynamic Product Line for Business Process Management (DynPL4BPM), aims to be comprehensive enough to cover the entire BPM lifecycle, including the treatment of dynamic aspects that the BPM domain requires. A systematic and comparative assessment showed that the proposed approach is successful in presenting processes much more comprehensive than other similar solutions already proposed in the literature for the same purpose.

Mineração de processos é uma área de pesquisa relativamente recente que se situa entre mineração de dados e aprendizado de máquina, de um lado, e modelagem e análise de processos de negócio, de outro lado. Mineração de processos visa descobrir, monitorar e aprimorar processos de negócio reais por meio da extração de conhecimento a partir de logs de eventos disponíveis em sistemas de informação orientados a processos. O principal objetivo deste trabalho foi avaliar o contexto de aplicação de técnicas provenientes das áreas de inteligência computacional e de aprendizado de máquina, incluindo redes neurais artificiais. Para fins de simplificação, denominadas no restante deste texto apenas como ``redes neurais\'\'. e máquinas de vetores de suporte, no contexto de mineração de processos. Considerando que essas técnicas são, atualmente, as mais aplicadas em tarefas de mineração de dados, seria esperado que elas também estivessem sendo majoritariamente aplicadas em mineração de processos, o que não tinha sido demonstrado na literatura recente e foi confirmado por este trabalho. Buscou-se compreender o amplo cenário envolvido na área de mineração de processos, incluindo as principais caraterísticas que têm sido encontradas ao longo dos últimos dez anos em termos de: tipos de mineração de processos, tarefas de mineração de dados usadas, e técnicas usadas para resolver tais tarefas. O principal enfoque do trabalho foi identificar se as técnicas de inteligência computacional e de aprendizado de máquina realmente não estavam sendo amplamente usadas em mineração de processos, ao mesmo tempo que se buscou identificar os principais motivos para esse fenômeno. Isso foi realizado por meio de um estudo geral da área, que seguiu rigor científico e sistemático, seguido pela validação das lições aprendidas por meio de um exemplo de aplicação. Este estudo considera vários enfoques para delimitar a área: por um lado, as abordagens, técnicas, tarefas de mineração e ferramentas comumente mais usadas; e, por outro lado, veículos de publicação, universidades e pesquisadores interessados no desenvolvimento da área. Os resultados apresentam que 81% das publicações atuais seguem as abordagens tradicionais em mineração de dados. O tipo de mineração de processos com mais estudo é Descoberta 71% dos estudos primários. Os resultados deste trabalho são valiosos para profissionais e pesquisadores envolvidos no tema, e representam um grande aporte para a área / Mining process is a relatively new research area that lies between data mining and machine learning, on one hand, and business process modeling and analysis, on the other hand. Mining process aims at discovering, monitoring and improving business processes by extracting real knowledge from event logs available in process-oriented information systems. The main objective of this master\'s project was to assess the application of computational intelligence and machine learning techniques, including, for example, neural networks and support vector machines, in process mining. Since these techniques are currently widely applied in data mining tasks, it would be expected that they were also widely applied to the process mining context, which has been not evidenced in recent literature and confirmed by this work. We sought to understand the broad scenario involved in the process mining area, including the main features that have been found over the last ten years in terms of: types of process mining, data mining tasks used, and techniques applied to solving such tasks. The main focus of the study was to identify whether the computational intelligence and machine learning techniques were indeed not being widely used in process mining whereas we sought to identify the main reasons for this phenomenon. This was accomplished through a general study area, which followed scientific and systematic rigor, followed by validation of the lessons learned through an application example. This study considers various approaches to delimit the area: on the one hand, approaches, techniques, mining tasks and more commonly used tools; and, on the other hand, the publication vehicles, universities and researchers interested in the development area. The results show that 81% of current publications follow traditional approaches to data mining. The type of mining processes more study is Discovery 71% of the primary studies. These results are valuable for practitioners and researchers involved in the issue, and represent a major contribution to the area

Les services Web proposent un paradigme intéressant pour la publication, la découverte et la consommation de services. Ce sont des applications faiblement couplées qui peuvent être exécutées seules ou être composées pour créer de nouveaux services à valeur ajoutée. Ils peuvent être consommés comme des services individuels qui fournissent une interface unique qui reçoit des inputs et retourne des outputs (cas 1), ou bien ils peuvent être consommés en tant que composants à intégrer dans des procédés métier (cas 2). Nous appelons le premier cas de consommation « utilisation individuelle » et le second cas de consommation « utilisation en procédé métier ». La nécessité d'avoir des outils dédiés pour aider les consommateurs dans les deux cas de consommation a impliqué de nombreux travaux de recherche dans les milieux académiques ou industriels. D'une part, beaucoup de portails et de moteurs de recherche de services ont été développés pour aider les utilisateurs à rechercher et invoquer les services Web pour une utilisation individuelle. Cependant, les approches actuelles prennent principalement en compte les connaissances explicites présentées par les descriptions de service. Ils font des recommandations sans tenir compte des données qui reflètent l'intérêt des utilisateurs et peuvent demander des informations supplémentaires aux utilisateurs. D'autre part, plusieurs techniques et mécanismes associées aux procédés métier ont été élaborés pour rechercher des modèles de procédé métiers similaires, ou utiliser des modèles de référence. Ces mécanismes sont utilisés pour assister les analystes métiers à la conception de procédés métiers. Cependant, ils sont lents, source d'erreurs, grands consommateurs de ressources humaines, et peuvent induire à l’erreur les analystes métier. Dans notre travail, nous cherchons à faciliter la consommation de services Web pour une utilisation individuelle ou en procédé métier en proposant des techniques de recommandation. Notre objectif est de recommander aux utilisateurs des services qui sont proches de leur intérêt et de recommander aux analystes métier des services qui sont pertinents pour un procédé métier en cours de conception. Pour recommander des services pour une utilisation individuelle, nous prenons en compte l’historique des données d'utilisation de l'utilisateur qui reflètent ses intérêts. Nous appliquons des techniques de filtrage collaboratif bien connues pour faire des recommandations. Nous avons proposé cinq algorithmes et développé une application Web qui permet aux utilisateurs d'utiliser des services recommandés. Pour recommander des services pour une utilisation en procédé métier, nous prenons en compte les relations entre les services du procédé métier. Nous proposons de recommander les services en fonction de leurs localisations dans le procédé métier. Nous avons définit le contexte de voisinage d'un service. Nous avons présenté des recommandations basées sur l'appariement de contexte de voisinage. Par ailleurs, nous avons développé un langage de requête pour permettre aux analystes métier d'exprimer formellement des contraintes de filtrage. Nous avons proposé également une approche pour extraire le contexte de voisinage à partir de traces d’exécution de procédés métier. Enfin, nous avons développé trois applications afin de valider notre approche. Nous avons effectué des expérimentations sur des données recueillies par nos applications et sur deux grands ensembles de données publiques. Les résultats expérimentaux montrent que notre approche est faisable, précise et performante dans des cas d'utilisation réels / Web services have been developed as an attractive paradigm for publishing, discovering and consuming services. They are loosely-coupled applications that can be run alone or be composed to create new value-added services. They can be consumed as individual services which provide a unique interface to receive inputs and return outputs; or they can be consumed as components to be integrated into business processes. We call the first consumption case individual use and the second case business process use. The requirement of specific tools to assist consumers in the two service consumption cases involves many researches in both academics and industry. On the one hand, many service portals and service crawlers have been developed as specific tools to assist users to search and invoke Web services for individual use. However, current approaches take mainly into account explicit knowledge presented by service descriptions. They make recommendations without considering data that reflect user interest and may require additional information from users. On the other hand, some business process mechanisms to search for similar business process models or to use reference models have been developed. These mechanisms are used to assist process analysts to facilitate business process design. However, they are labor-intense, error-prone, time-consuming, and may make business analyst confused. In our work, we aim at facilitating the service consumption for individual use and business process use using recommendation techniques. We target to recommend users services that are close to their interest and to recommend business analysts services that are relevant to an ongoing designed business process. To recommend services for individual use, we take into account the user's usage data which reflect the user's interest. We apply well-known collaborative filtering techniques which are developed for making recommendations. We propose five algorithms and develop a web-based application that allows users to use services. To recommend services for business process use, we take into account the relations between services in business processes. We target to recommend relevant services to selected positions in a business process. We define the neighborhood context of a service. We make recommendations based on the neighborhood context matching. Besides, we develop a query language to allow business analysts to formally express constraints to filter services. We also propose an approach to extract the service's neighborhood context from business process logs. Finally, we develop three applications to validate our approach. We perform experiments on the data collected by our applications and on two large public datasets. Experimental results show that our approach is feasible, accurate and has good performance in real use-cases

ERP system has shaped the way modern organisations design, control, and execute business processes. It has not only paved the way for efficient use of organisational resources but also offered the opportunity to utilise data logged in the system for ensuring internal control. The key contribution of this research is that it has resulted in a method which can practically be employed by internal auditors for measuring internal fraud risk of business organisations with ERP systems, by utilising process mining technique and evidential reasoning in the form of Bayesian theorem, in a much more effective way compared to conventional frequentist method. The other significant contribution is that it has paved the way for combining process mining technique and evidential reasoning in addressing problems prevalent within organisational contexts. This research has contributed in developing IS theories for design and action especially in the area of soft systems methodology as it has relied on business process modelling in addressing the issue of internal fraud risk. The chosen method has contributed in facilitating incorporation of design science method in problem solving. Researchers have focused on applying data mining techniques within organisational contexts for extracting valuable information. Process mining is a comparatively new technique which allows business processes to be analysed based on event logs. Analysis of business processes can be useful for organisations not only for attaining greater efficiency but also for ensuring internal control inside the organisation. Large organisations have various measures in place for ensuring internal control. Measuring the risk of fraud within a business process is an important practice for preventing fraud as accurate measurement of fraud risk provides business experts with the opportunity to comprehend the extent of the problem. Business experts, such as internal auditors, still heavily rely upon conventional methods for measuring internal fraud risk way by of random check of process compliance. Organisations with ERP systems in place can avail themselves of the opportunity to use event logs for extending the scope of assessing process conformance. This has not been put into practice as there is a lack of well researched methods which can allow event logs to be utilised for enhancing internal control. This research can be proved to be useful for practitioners as it has developed a method for measuring internal fraud risk within organisations. This research aimed to utilise process mining technique that allows business experts to exert greater control over business process execution by allowing the internal fraud risk to be measured effectively. A method has been developed for measuring internal fraud risk of business originations with ERP systems by using process mining and Bayesian theorem. In this method, rate of process deviation is calculated by conducting process mining on relevant logs of events and then that process deviation rate is applied in Bayesian theorem along with historic internal fraud risk rate and process deviation rate calculated manually for arriving at a revised internal fraud risk rate. Bayesian theorem has been relied upon for the purpose of developing this new method as it allows evidential reasoning to be incorporated. The method has been developed as a Design Science Research Method (DSRM) artefact by conducting three case-studies. Data has been collected from three case companies, operating in readymade garments manufacturing industry, pharmaceuticals industry, and aviation industry, regarding their procurement process for conducting process mining. The revised internal fraud risk rates were then evaluated by considering the feedback received from respective business experts of each of the case company. The proposed method is beneficial as it has paved the way for practitioners to utilise process mining using a soft system methodology. The developed method is of immense significance as it has contributed in the field of business intelligence and analytics (BI&A) and the big data analytics which have become significantly important to both academics and practitioners over the past couple of decades.

Nous proposons une approche de gestion des processus métier configurables (cBP) offrant une vue consolidée des variantes de ces processus. Une variante est le résultat de l'ajustement d'un cBP en réponse à des besoins fonctionnels et / ou structurels. Cette approche utilise une base de connaissances pour suivre les spécificités de chaque variante représentée sous la forme d'arborescence de structure de processus configurable (cPST). Une implémentation de l'approche consistant à générer un cPST à partir d'un cBP est proposée. Nous appliquons cette approche pour calculer la complexité des processus métier configurables et prouver son avantage pour améliorer la qualité du cBP / We propose an approach for managing configurable Business Processes (cBP) that offer a consolidated view over these processes’ variants. A variant is the result of adjusting a BP in response to functional and/or structural needs. The approach uses a knowledge base to track the specificities of each variant that is represented as configurable Process Structure Tree (cPST). An implementation of the approach that consists of generating a cPST from a cBP is proposed. We apply this approach to compute configurable business process complexity and to prove its advantage for improving cBP quality

Business process analysis and integration are key endeavours for today's enterprises. Recently, Web services have been widely adopted for the implementation and integration of business processes within and across enterprises. In this dissertation, we investigate the problem of enabling the analysis of service interactions, in today's enterprises, in the context of business process executions, and that of service integration. Our study shows that only fraction of interactions in the enterprise are supported by process-aware systems. However, enabling above-mentioned analyses requires: (i) a model of the underlying business process to be used as a reference for the analysis, and (ii) the ability to correlate events generated during service interactions into process instances. We refer to a process model and the corresponding process instances as a "process view". We propose the concept of process space to refer to all process related information sources in the enterprise, over which various process views are defined. We propose the design and development of a system called "process space discovery system" (PSDS) for discovering process views in a process space. We introduce novel approaches for the correlation of events into process instances, focusing on the public processes of Web services (business protocols), and also for the discovery of the business protocol models from the process instances of a process view. Analysis of service integration approaches shows that while standardisation in Web services simplifies the integration in the communication level, at the higher levels of abstractions (e.g., services interfaces and protocol models) services are still open to heterogeneities. We characterise the mismatches between service interfaces and protocol specifications and introduce "mismatch patterns" to represent them. A mismatch pattern also includes an adapter template that aims at the resolution of the captured mismatch. We also propose semi-automated approaches for identifying the mismatches between interface and protocol specifications of two services. The proposed approaches have been implemented in prototype tools, and experimentally validated on synthetic and real-world datasets. The discovered process views, using PSDS, can be used to perform various analyses in an enterprise, and the proposed adaptation approach facilitates the adoption of Web services in business process integration.

資訊科技的進步，使得企業競爭的方式產生了根本性的改變，由過去單一企業的競爭，朝向跨組織整合的方向發展。企業間無論透過併購或策略聯盟的手段，皆希望整合上下游、提昇效率，以提高整體競爭力。而整體服務水準的提升，有賴於跨組織流程與資訊上的整合，使客戶的需求可以快速被滿足。工作流在跨組織流程中扮演極為關鍵性的角色，它結合企業邏輯、人員作業、組織資訊科技，主導企業流程，並直接影響到作業的品質與效率。 　　本研究採個案研究方式，選擇一國際海運物流集團，實地訪談各子公司，分析海運物流業者跨組織的整合運作。從企業流程與工作流的配合中，架構出資訊在跨組織企業中的傳遞，並描繪出資訊科技在工作流中所扮演的角色。結合企業流程、工作流、資訊架構此三個面向的觀點，探討企業工作流中的問題、資訊不連續的中斷點、跨組織工作流管理的困難點、以及資訊系統整合的問題。 　　經問題探討與流程分析，站在資訊整合、工作流資訊化、自動化的觀點，本研究針對個案集團提出新的工作流模式，為其規劃出與工作流整合之資訊系統，同時定義及強化資訊系統在可見性與自動追蹤、稽催上的角色。

因應資訊化作業，大型企業組織透過企業資源規劃系統來整合組織內部與外部的資訊，以促進各種不同的商業功能間資訊的流動與交換。企業資源規劃系統中的主要模組包括商業流程管理。傳統商業流程管理著重在商業處理的自動化。先進的商業流程管理整合了流程邏輯與商業邏輯的功能，以有助於商業策略的規劃。商業流程管理的生命週期包括流程設計、系統配置、流程啟動、診斷四個階段。現有的研究多集中在前三個階段，較少與診斷有關的研究。本篇論文針對商業流程管理系統，研發系統發生錯誤時的診斷工具。本論文提出了診斷模型。此模型由使用者反應的問題中，定義錯誤類別、歸納使用者外部資訊，由商業規則和資料庫綱要中參考整合限制，並對應到系統的內部資訊。我們也開發了追蹤工具，追蹤錯誤可能的發生點，並依不同類別進行問題偵錯。除了針對本身的工作流程中的活動，也對前後的活動進行搜尋，以縮小錯誤偵測的範圍，協助資訊人員有效率排除錯誤。本論文根據一家電子公司的商業流程管理系統的個案研究，顯示我們所提出的診斷模型與追蹤工具有助於問題的偵錯。 關鍵字: 商業流程管理、診斷工具、商業邏輯 / An Enterprise Resource Panning (ERP) system integrates internal and external information andfacilitates the flow of information between all business functions inside and outside an organization. One of the main components of an ERP is the Business Process Management (BPM). Traditional BPM focues on the automation of business processes while advanced BPM has been extended to integrate with process logics and business logics for business strategy. The life cycle of a BPM system consists of process design, system configuration process enactment and diagnosis phases.Much research has been done on the first three phases. Little attension has been paid to the diagnosis phase. This thesis focuses on the design and implementation of a diagnosis tool for BPM systems. We propose a diagnosis model to represent the external and internal view of an error event. This diagnosis model is helpful for the troibleshouting to capture the status of an error event. Moreover, a bug tracer system is devlopement based on the proposed diagnosis model to diagnose the problem of workflow activities, and also trace before and after activities in the workflow, narrow the scope of error detection. Case studies from an electronic company demonstrate that the proposed diagnosis model and the tracer tool are helpful for troubleshooting. Keywords: Business Process Management, Diagnosis Tool, Business Logic