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.

Determining Process Model Precision and Generalization with Weighted Artificial Negative Events

Abstract: Process mining encompasses the research area which is concerned with knowledge discovery from event logs. One common process mining task focuses on conformance checking, comparing discovered or designed process models with actual real-life behavior as captured in event logs in order to assess the “goodness” of the process model. This paper introduces a novel conformance checking method to measure how well a process model performs in terms of precision and generalization with respect to the actual executions of a process as recorded in an event log. Our approach differs from related work in the sense that we apply the concept of so-called weighted artificial negative events toward conformance checking, leading to more robust results, especially when dealing with less complete event logs that only contain a subset of all possible process execution behavior. In addition, our technique offers a novel way to estimate a process model’s ability to generalize. Existing literature has focused mainly on the fitness (recall) and precision (appropriateness) of process models, whereas generalization has been much more difficult to estimate. The described algorithms are implemented in a number of ProM plugins, and a Petri net conformance checking tool was developed to inspect process model conformance in a visual manner.

Modeling of CO2 capture via chemical absorption processes − An extensive literature review

Abstract: Climate change mainly due to the release of greenhouse gases into the atmosphere is getting alarming dimensions. CO2 capture from point source emissions is a promising solution, lately receiving significant attention. In particular, chemical absorption of CO2 from flue gases using aqueous solvents (mainly alkanolamines) is a well-known process, studied in detail. Modern research aims to optimize this process, maximizing the absorption rates and minimizing the parasitic but not negligible energy requirements for solvent regeneration. This type of analysis requires considering the coupling of the absorption with the power plant operation or other source of CO2. The operation fluctuations and disturbances, such as load variations or start-up mode have to be reflected in the process modeling, justifying the emerging need for dynamic modeling. However, dynamic analysis is not always realizable as dynamic experimental data are scarce in order to enable accurate model validation. Thus, steady state models are still convenient for certain cases. The current work provides a short description of the main modeling approaches followed and enlists representative steady state and dynamic models found in literature. Finally, a primary comparison is performed for some comparable models that used the same set of experimental data for model validation.

Process and deviation exploration with Inductive visual Miner

Abstract: Process mining aims to extract information from recorded process data, which can be used to gain insights into the process. This requires applying a discovery algorithm and settings its parameters, after which the discovered process model should be evaluated. Both steps may need to be repeated several times until a satisfying model is found; we refer to this as process exploration. Existing commercial tools usually do not provide models having executable semantics, thereby disallowing for accurate map evaluation, while most academic tools lack features and by the repetitive nature of process exploration, their use is tedious. In this paper, we describe a novel process exploration tool: the Inductive visual Miner. It aims to bridge this gap between commercial and academic tools, by combining the executable semantics of academic tools with the exploration support of commercial tools. It also adds animation and deviation visualisation capabilities. Copyright © 2014 for this paper by its authors. Copying permitted for private and academic purposes.

Process Management in Design and Construction

Abstract: Process Management in Design and Construction will provide students on construction and project management related courses with a description of the state of process management in design and construction - including current process models - as well as future vision based on up-to-date research findings and good practice in the construction industry. The book also offers practical guidance to industrial and consultancy organisations on undertaking and implementing process management projects…