Topic
Process modeling
About: Process modeling is a research topic. Over the lifetime, 11639 publications have been published within this topic receiving 223996 citations. The topic is also known as: process simulation.
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TL;DR: This paper presents Event Stream Processing Units (SPUs) as an abstraction mechanism to encapsulate application logic for event stream processing and enable a seamless transition between process models, executable process representations, and components at the IT layer, and presents a runtime infrastructure that executes SPUs and supports implicit invocation and completion semantics.
58 citations
TL;DR: This article presents a process modeling language and a support tool which are conceived especially for process model elicitation and provides a view mechanism that enables inspection of models according to different perspectives.
Abstract: Software processes are complex entities that demand careful understand ing and improvement as they determine the quality of the resulting product. A necessary step toward the improvement of an organization's process is a clear description of the entities involved and of their mutual relationships. Process model elicitation aims at constructing this description under the shape of a software process model. The model is constructed by gathering, from several sources, process information which is often incomplete, inconsistent, and ambiguous. A process modeling language can be used to represent the model being elicited. However, elicitation requires process models to be understandable and well structured. These requirements are often not satisfied by available process modeling languages becuase of their bias toward process enaction rather than process description. This article presents a process modeling language and a support tool which are conceived especially for process model elicitation. The E3 language is an object-oriented modeling language with a graphical notation. In E3, associations are a means to express constraints and facilitate reuse. The E3p-draw tool supports the creation and management of E3 models and provides a view mechanism that enables inspection of models according to different perspectives.
58 citations
TL;DR: In this paper, the preference for different process representation forms depending on the task setting and cognitive style of the user was examined empirically, and it was found that users consistently prefer diagrams over other representation formats.
Abstract: Process models describe someone's understanding of processes. Processes can be described using unstructured, semi-formal or diagrammatic representation forms. These representations are used in a variety of task settings, ranging from understanding processes to executing or improving processes, with the implicit assumption that the chosen representation form will be appropriate for all task settings. We explore the validity of this assumption by examining empirically the preference for different process representation forms depending on the task setting and cognitive style of the user. Based on data collected from 120 business school students, we show that preferences for process representation formats vary dependent on application purpose and cognitive styles of the participants. However, users consistently prefer diagrams over other representation formats. Our research informs a broader research agenda on task-specific applications of process modeling. We offer several recommendations for further research in this area.
58 citations
TL;DR: A high-efficiency mechanistic model, self-consistent clustering analyses, is developed, which incorporates factors such as voids, phase composition, inclusions, and grain structures, which are the differentiating features of AM metals.
Abstract: This paper presents our latest work on comprehensive modeling of process-structure-property relationships for additive manufacturing (AM) materials, including using data-mining techniques to close the cycle of design-predict-optimize. To illustrate the process-structure relationship, the multi-scale multi-physics process modeling starts from the micro-scale to establish a mechanistic heat source model, to the meso-scale models of individual powder particle evolution, and finally to the macro-scale model to simulate the fabrication process of a complex product. To link structure and properties, a high-efficiency mechanistic model, self-consistent clustering analyses, is developed to capture a variety of material response. The model incorporates factors such as voids, phase composition, inclusions, and grain structures, which are the differentiating features of AM metals. Furthermore, we propose data-mining as an effective solution for novel rapid design and optimization, which is motivated by the numerous influencing factors in the AM process. We believe this paper will provide a roadmap to advance AM fundamental understanding and guide the monitoring and advanced diagnostics of AM processing.
58 citations
07 Sep 2014
TL;DR: A framework for controlling the safe execution of tasks and signalling possible misbehaviours at runtime is described and a real use case on smart logistics and the preliminary results of its application are outlined.
Abstract: Information sources providing real-time status of physical objects have drastically increased in recent times. So far, research in business process monitoring has mainly focused on checking the completion of tasks. However, the availability of real-time information allows for a more detailed tracking of individual business tasks. This paper describes a framework for controlling the safe execution of tasks and signalling possible misbehaviours at runtime. It outlines a real use case on smart logistics and the preliminary results of its application.
58 citations