The Experts below are selected from a list of 138 Experts worldwide ranked by ideXlab platform
X Y Zhang - One of the best experts on this subject based on the ideXlab platform.
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plasma arc welding Process sensing control and modeling
Journal of Manufacturing Processes, 2014Co-Authors: C S Wu, W J Ren, Liyuan Wang, X Y ZhangAbstract:Abstract This article introduces the basic principles of plasma arc welding (PAW) and provides a survey of the latest research and applications in the field. The PAW Process is compared to gas tungsten arc welding, its Process characteristics are listed, the classification is made, and two modes of operation in PAW, i.e., melt-in and keyhole, are explained. The keyhole mechanism and its influencing factors are introduced. The sensing and control methodologies of the PAW Process are reviewed. The coupled behaviors of weld pool and keyhole, the heat transfer and fluid flow as well as three-dimensional modeling and simulation in PAW are discussed. Finally, a novel PAW Process Variant, the controlled pulse keyholing Process and the corresponding experimental system are introduced.
Farbod Taymouri - One of the best experts on this subject based on the ideXlab platform.
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business Process Variant analysis survey and classification
Knowledge Based Systems, 2021Co-Authors: Farbod Taymouri, Marcello La Rosa, Marlon Dumas, Fabrizio Maria MaggiAbstract:Abstract It is common for business Processes to exhibit a high degree of internal heterogeneity, in the sense that the executions of the Process differ widely from each other due to contextual factors, human factors, or deliberate business decisions. For example, a quote-to-cash Process in a multinational company is typically executed differently across different countries or even across different regions in the same country. Similarly, an insurance claims handling Process might be executed differently across different claims handling centers or across multiple teams within the same claims handling center. A subset of executions of a business Process that can be distinguished from others based on a given predicate (e.g. the executions of a Process in a given country) is called a Process Variant. Understanding differences between Process Variants helps analysts and managers to make informed decisions as to how to standardize or otherwise improve a business Process, for example by helping them find out what makes it that a given Variant exhibits a higher performance than another one. Process Variant analysis is a family of techniques to analyze event logs produced during the execution of a Process, in order to identify and explain the differences between two or more Process Variants. A wide range of methods for Process Variant analysis have been proposed in the past decade. However, due to the interdisciplinary nature of this field, the proposed methods and the types of differences they can identify vary widely, and there is a lack of a unifying view of the field. To close this gap, this article presents a systematic literature review of methods for Process Variant analysis. The identified studies are classified according to their inputs, outputs, analysis purpose, underpinning algorithms, and extra-functional characteristics. The paper closes with a broad classification of approaches into three categories based on the paradigm they employ to compare multiple Process Variants.
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business Process Variant analysis based on mutual fingerprints of event logs
Conference on Advanced Information Systems Engineering, 2020Co-Authors: Farbod Taymouri, Marcello La Rosa, Josep CarmonaAbstract:Comparing business Process Variants using event logs is a common use case in Process mining. Existing techniques for Process Variant analysis detect statistically-significant differences between Variants at the level of individual entities (such as Process activities) and their relationships (e.g. directly-follows relations between activities). This may lead to a proliferation of differences due to the low level of granularity in which such differences are captured. This paper presents a novel approach to detect statistically-significant differences between Variants at the level of entire Process traces (i.e. sequences of directly-follows relations). The cornerstone of this approach is a technique to learn a directly-follows graph called mutual fingerprint from the event logs of the two Variants. A mutual fingerprint is a lossless encoding of a set of traces and their duration using discrete wavelet transformation. This structure facilitates the understanding of statistical differences along the control-flow and performance dimensions. The approach has been evaluated using real-life event logs against two baselines. The results show that at a trace level, the baselines cannot always reveal the differences discovered by our approach, or can detect spurious differences.
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business Process Variant analysis survey and classification
arXiv: Other Computer Science, 2019Co-Authors: Farbod Taymouri, Marcello La Rosa, Marlon Dumas, Fabrizio Maria MaggiAbstract:Process Variant analysis aims at identifying and addressing the differences existing in a set of Process executions enacted by the same Process model. A Process model can be executed differently in different situations for various reasons, e.g., the Process could run in different locations or seasons, which gives rise to different behaviors. Having intuitions about the discrepancies in Process behaviors, though challenging, is beneficial for managers and Process analysts since they can improve their Process models efficiently, e.g., via interactive learning or adapting mechanisms. Several methods have been proposed to tackle the problem of uncovering discrepancies in Process executions. However, because of the interdisciplinary nature of the challenge, the methods and sorts of analysis in the literature are very heterogeneous. This article not only presents a systematic literature review and taxonomy of methods for Variant analysis of business Processes but also provides a methodology including the required steps to apply this type of analysis for the identification of Variants in business Process executions.
Fabrizio Maria Maggi - One of the best experts on this subject based on the ideXlab platform.
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business Process Variant analysis survey and classification
Knowledge Based Systems, 2021Co-Authors: Farbod Taymouri, Marcello La Rosa, Marlon Dumas, Fabrizio Maria MaggiAbstract:Abstract It is common for business Processes to exhibit a high degree of internal heterogeneity, in the sense that the executions of the Process differ widely from each other due to contextual factors, human factors, or deliberate business decisions. For example, a quote-to-cash Process in a multinational company is typically executed differently across different countries or even across different regions in the same country. Similarly, an insurance claims handling Process might be executed differently across different claims handling centers or across multiple teams within the same claims handling center. A subset of executions of a business Process that can be distinguished from others based on a given predicate (e.g. the executions of a Process in a given country) is called a Process Variant. Understanding differences between Process Variants helps analysts and managers to make informed decisions as to how to standardize or otherwise improve a business Process, for example by helping them find out what makes it that a given Variant exhibits a higher performance than another one. Process Variant analysis is a family of techniques to analyze event logs produced during the execution of a Process, in order to identify and explain the differences between two or more Process Variants. A wide range of methods for Process Variant analysis have been proposed in the past decade. However, due to the interdisciplinary nature of this field, the proposed methods and the types of differences they can identify vary widely, and there is a lack of a unifying view of the field. To close this gap, this article presents a systematic literature review of methods for Process Variant analysis. The identified studies are classified according to their inputs, outputs, analysis purpose, underpinning algorithms, and extra-functional characteristics. The paper closes with a broad classification of approaches into three categories based on the paradigm they employ to compare multiple Process Variants.
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business Process Variant analysis survey and classification
arXiv: Other Computer Science, 2019Co-Authors: Farbod Taymouri, Marcello La Rosa, Marlon Dumas, Fabrizio Maria MaggiAbstract:Process Variant analysis aims at identifying and addressing the differences existing in a set of Process executions enacted by the same Process model. A Process model can be executed differently in different situations for various reasons, e.g., the Process could run in different locations or seasons, which gives rise to different behaviors. Having intuitions about the discrepancies in Process behaviors, though challenging, is beneficial for managers and Process analysts since they can improve their Process models efficiently, e.g., via interactive learning or adapting mechanisms. Several methods have been proposed to tackle the problem of uncovering discrepancies in Process executions. However, because of the interdisciplinary nature of the challenge, the methods and sorts of analysis in the literature are very heterogeneous. This article not only presents a systematic literature review and taxonomy of methods for Variant analysis of business Processes but also provides a methodology including the required steps to apply this type of analysis for the identification of Variants in business Process executions.
C S Wu - One of the best experts on this subject based on the ideXlab platform.
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plasma arc welding Process sensing control and modeling
Journal of Manufacturing Processes, 2014Co-Authors: C S Wu, W J Ren, Liyuan Wang, X Y ZhangAbstract:Abstract This article introduces the basic principles of plasma arc welding (PAW) and provides a survey of the latest research and applications in the field. The PAW Process is compared to gas tungsten arc welding, its Process characteristics are listed, the classification is made, and two modes of operation in PAW, i.e., melt-in and keyhole, are explained. The keyhole mechanism and its influencing factors are introduced. The sensing and control methodologies of the PAW Process are reviewed. The coupled behaviors of weld pool and keyhole, the heat transfer and fluid flow as well as three-dimensional modeling and simulation in PAW are discussed. Finally, a novel PAW Process Variant, the controlled pulse keyholing Process and the corresponding experimental system are introduced.
Walid Gaaloul - One of the best experts on this subject based on the ideXlab platform.
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service querying to support Process Variant development
Journal of Systems and Software, 2016Co-Authors: Nguyen Ngoc Chan, Nattawat Nonsung, Walid GaaloulAbstract:Service querying helps to facilitate the development of Process Variants.We provide a query language based on the similarity between services.We compute the service similarity based on a concept of neighborhood context.We specify the similarity between service connectors (AND, OR, XOR).We developed a GUI application and performed several experiments on a real dataset. Developing Process Variants enables enterprises to effectively adapt their business models to different markets. Existing approaches focus on business Process models to support the Variant development. The assignment of services in a business Process, which ensures the Process variability, has not been widely examined. In this paper, we present an innovative approach that focuses on component services instead of Process models. We target to recommend services to a selected position in a business Process. We define the service composition context as the relationships between a service and its neighbors. We compute the similarity between services based on the matching of their composition contexts. Then, we propose a query language that considers the composition context matching for service querying. We developed an application to demonstrate our approach and performed different experiments on a public dataset of real Process models. Experimental results show that our approach is feasible and efficient.
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A linear program for optimal configurable business Processes deployment into cloud federation
Proceedings - 2016 IEEE International Conference on Services Computing SCC 2016, 2016Co-Authors: Molka Rekik, Nour Assy, Walid Gaaloul, Khouloud Boukadi, Hanene Ben-abdallahAbstract:A configurable Process model is a generic model from which an enterprise\ncan derive and execute Process Variants that meet its specific needs and\ncontexts. With the advent of cloud computing and its economic\npay-per-use model, enterprises are increasingly outsourcing partially or\ntotally their Process Variants to cloud providers, and recently to cloud\nfederations. A main challenge in this regard is to allocate optimally\ncloud resources to the Process Variants' activities. More specifically,\nan enterprise may be interested in outsourcing only those that result in\nan optimal deployment. Due to the diversity of the enterprise QoS\nrequirements, the heterogeneity of resources offered by the cloud\nfederation and the large number of possible configurations in a\nconfigurable Process model, finding the optimal Process Variant\ndeployment becomes a highly challenging problem. In this paper, we\npropose a novel approach to solve this problem through a binary/(0-1)\nlinear program with a quadratic objective function under a set of\nconstraints pertinent to both the enterprise and cloud federation\nrequirements. Our prototypical implementation demonstrates the\nfeasibility and the results of our experiments highlight the\neffectiveness of our proposed solution.
