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.

Creative computing with Landlab: an open-source toolkit for building, coupling, and exploring two-dimensional numerical models of Earth-surface dynamics

Abstract: . The ability to model surface processes and to couple them to both subsurface and atmospheric regimes has proven invaluable to research in the Earth and planetary sciences. However, creating a new model typically demands a very large investment of time, and modifying an existing model to address a new problem typically means the new work is constrained to its detriment by model adaptations for a different problem. Landlab is an open-source software framework explicitly designed to accelerate the development of new process models by providing (1) a set of tools and existing grid structures – including both regular and irregular grids – to make it faster and easier to develop new process components, or numerical implementations of physical processes; (2) a suite of stable, modular, and interoperable process components that can be combined to create an integrated model; and (3) a set of tools for data input, output, manipulation, and visualization. A set of example models built with these components is also provided. Landlab's structure makes it ideal not only for fully developed modelling applications but also for model prototyping and classroom use. Because of its modular nature, it can also act as a platform for model intercomparison and epistemic uncertainty and sensitivity analyses. Landlab exposes a standardized model interoperability interface, and is able to couple to third-party models and software. Landlab also offers tools to allow the creation of cellular automata, and allows native coupling of such models to more traditional continuous differential equation-based modules. We illustrate the principles of component coupling in Landlab using a model of landform evolution, a cellular ecohydrologic model, and a flood-wave routing model.

A programming process architecture

Abstract: The Programming Process Architecture is a framework describing required activities for an operational process that can be used to develop system or application software. The architecture includes process management tasks, mechanisms for analysis and development of the process, and product quality reviews duringt he various stages of the development cycle. It requires explicit entry criteria, validation, and exit criteria for each task in the process, which combined form the "essence" of the architecture. The architecture describes requirements for a process needing no new invention, but rather using the best proven methodologies, techniques, and tools available today. This paper describes the Programming Process Architecture and its use, emphasizing the reasons for its development.

Active Trace Clustering for Improved Process Discovery

Abstract: Process discovery is the learning task that entails the construction of process models from event logs of information systems. Typically, these event logs are large data sets that contain the process executions by registering what activity has taken place at a certain moment in time. By far the most arduous challenge for process discovery algorithms consists of tackling the problem of accurate and comprehensible knowledge discovery from highly flexible environments. Event logs from such flexible systems often contain a large variety of process executions which makes the application of process mining most interesting. However, simply applying existing process discovery techniques will often yield highly incomprehensible process models because of their inaccuracy and complexity. With respect to resolving this problem, trace clustering is one very interesting approach since it allows to split up an existing event log so as to facilitate the knowledge discovery process. In this paper, we propose a novel trace clustering technique that significantly differs from previous approaches. Above all, it starts from the observation that currently available techniques suffer from a large divergence between the clustering bias and the evaluation bias. By employing an active learning inspired approach, this bias divergence is solved. In an assessment using four complex, real-life event logs, it is shown that our technique significantly outperforms currently available trace clustering techniques.

Deriving process models for workflow management systems from audit trails

Abstract: The present invention relates to the area of workflow management systems (WFMS). More particularly the invention is related to a methodology of automatically deriving and steadily improving a process model executed by the WFMS. The current invention dramatically simplifies and automates the process of model a business model of a business process. The invention allows to start just with set of unrelated activities and discover the real world relations between them at a later point in time; data mining and OLAP technologies are exploited for this discovery. The current invention thus proposes a posteriori methodology. For that purpose the precise underlying process model is derived at a later point in time based on audit data collected by the WFMS during the early deployment of a process model.

Decision framework for chemical process design including different stages of environmental, health, and safety assessment

Abstract: In recent years, many chemical companies have adopted the concept of sustainable development as a core business value. In this context and with focus on early phases, we present a novel design framework that comprises four stages of process modeling and multiobjective evaluation considering monetary and nonmonetary aspects. Each stage is characterized by the available information as a basis for process modeling and assessment. Appropriate modeling approaches, and evaluation indicators for economy, life-cycle environmental impacts, environment, health, and safety (EHS) hazard, and technical aspects are selected for each defined stage. The proposed framework is demonstrated on the design of a methyl methacrylate (MMA) process: considering 17 synthesis routes, the framework is mimicked step-by-step, to select the route with the best multiobjective performances, and to produce an optimized process flowsheet. As a validation of the framework, evaluation profile of six routes over all stages are compared, and crucial points are identified that should be estimated considerably well in early stages of the framework. © 2008 American Institute of Chemical Engineers AIChE J, 2008