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.

GreenPro: a new methodology for cleaner and greener process design

Abstract: Chemical and allied industries have shown interest in reducing pollution by implementing cleaner technologies or processes that use, or generate, lower amounts of or less harmful pollutants. However, abatement processes are still required at many plants to reduce the discharge of pollutants at the end-of-the-pipe. It has been observed many times that efforts made to optimise the abatement process reduce the quality and/or quantity of waste discharge at the end-of-the-pipe, but increase the total environmental burden and impact. Therefore, it is very important to consider the environmental burden and adverse impacts caused due to any change or modification in the process and allied facilities for the complete system (up- and downstream of the process). Moreover, these measures have generally been taken only after fully fledged design of the process or at the operating stage, thus making the preventive/abatement measure a costly affair. Therefore, there is great need for a design process (applicable to the early design and decision-making stages) that not only considers economy and technology as the basic input for the design, but also considers environmental soundness as one of the important parameters. This paper proposes a systematic methodology for process design that considers the assessment and minimisation of the environmental impacts of the complete process system (including upstream processes). It incorporates life cycle analysis (LCA) principles within a formal design process and optimisation framework. This proposed process design methodology with minimum environmental impact extends to a complete description of the environmental impact of the process and its associated activities. It has good real-life application potential, as it includes environmental objectives together with technology and economics at the design stage so as to determine a cost-efficient solution. Further, by employing process modelling and optimisation techniques, it yields optimal design/operating conditions with minimum environmental impact. The applicability of the proposed methodology has been demonstrated through a real case study. The most interesting observation made in the case study is that the total cost of the optimised operation is minimum when the process is designed and optimised considering the global boundary (the “cradle to the grave” approach) in contrast to the conventional boundary (process boundary).

Meronymy-based aggregation of activities in business process models

Abstract: As business process management is increasingly applied in practice, more companies document their operations in the form of process models. Since users require descriptions of one process on various levels of detail, there are often multiple models created for the same process. Business process model abstraction emerged as a technique reducing the number of models to be stored: given a detailed process model, business process model abstraction delivers abstract representations for the same process. A key problem in many abstraction scenarios is the transition from detailed activities in the initial model to coarse-grained activities in the abstract model. This transition is realized by an aggregation operation clustering multiple activities to a single one. So far, humans decide on how to aggregate, which is expensive. This paper presents a semi-automated approach to activity aggregation that reduces the human effort significantly. The approach takes advantage of an activity meronymy relation, i.e., part-of relation defined between activities. The approach is semi-automated, as it proposes sets of meaningful aggregations, while the user still decides. The approach is evaluated by a real-world use case.

Learning from Context to Improve Business Processes

Abstract: K. Ploesser, M. Peleg, P.Soffer, M. Rosemann, and J. Recker, are members of a team of researchers from Queensland University, Australia, Stanford University, USA and Haifa University, Israel, who are currently investigating how context-awareness can become an integral part of business process modeling. They argue that to get to the next level of process management we must broaden our analysis beyond internal processes to the contextual environment in which the processes are embedded. Read this compelling Article for their take on how this will impact business process management in the future.

System and method of predictive modeling for managing decisions for business enterprises

Abstract: A system and method is provided for predictive modeling of technical and non-technical components in a business infrastructure that implementing one or more business solutions According to a first aspect of the invention, performance metrics generated from a predictive model of a business infrastructure are translated into enterprise decision or indicators that correspond to the service, performance and financial states of a business enterprise As a result, non-technical executives can utilize the enterprise decision metrics or indicators to evaluate, support, and monitor the effect of business decisions, for example, with respect to profitability, productivity, growth, and risk of the business According to a second aspect of the invention, the accuracy of the predictive modeling is improved by mathematically expressing the dynamic characteristics and behavior of each infrastructure component as a result of direct and indirect effects of the infrastructure components impacting one another Perturbation theory can be used to express direct and indirect effects