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.

A simulation-based process model for managing complex design projects

Abstract: This paper presents a process modeling and analysis technique for managing complex design projects using advanced simulation. The model computes the probability distribution of lead time in a stochastic, resource-constrained project network where iterations take place among sequential, parallel, and overlapped tasks. The model uses the design structure matrix representation to capture the information flows between tasks. We use a simulation-based analysis to account for many realistic aspects of design process behavior which were not possible in previous analytical models. We propose a heuristic for the stochastic, resource-constrained project scheduling problem in an iterative project network. The model can be used for better project planning and control by identifying leverage points for process improvements, and for evaluating alternative planning and execution strategies. An industrial example is provided to illustrate the utility of the model.

The computer as a tool for learning through reflection

Abstract: A unique aspect of computers is that they not only represent process but also naturally keep track of the actions used to carry out a given task, so that the process with its trace can become an object of study in its own right. One effect of this can be seen vividly in the sciences, where computers and computational languages have improved our ability to develop and test process theories of complex natural phenomena. Before powerful computers became readily available as scientific tools, process models were expressed in mathematical languages, such as differential equations— languages primarily effective in capturing a static “snapshot” of a process. Computation provided formal languages that are more flexible than mathematics but just as precise. In part because computation is itself dynamic, it provides an ideal medium for representing and testing richer, more varied, and more detailed theories of process. The use of this medium for process modeling has radically changed the nature of many current theories in both the physical and social sciences. Particularly in the arena of the cognitive sciences, computational techniques have proved to be powerful tools for both experimental and theoretical investigations of the mind.

Opportunities and constraints: the current struggle with BPMN

Abstract: Purpose – The business process modeling notation (BPMN) is an increasingly important standard for process modeling and has enjoyed high levels of attention in business practice. In this paper, experiences are shared from several research projects investigating the uptake and user acceptance of BPMN by analysts world‐wide. This personal viewpoint aims to offer a number of implications for business process management (BPM) practice and seeks to stimulate and guide further research and other developments in this area.Design/methodology/approach – This paper offers a personal viewpoint based on the experiences and findings gathered from survey research and interviews on the use of BPMN. While details on research execution are mostly omitted, references are provided to guide the interested reader to the methodology used in the original studies.Findings – First, statistics are provided on the usage of BPMN by process modelers world‐wide. Amongst others, it is shown that the high interest in BPMN has created a m...

Measuring similarity between semantic business process models

Abstract: A business process may be modeled in different ways by different modelers even when utilizing the same modeling language. An appropriate method for solving ambiguity issues in process models caused by the use of synonyms, homonyms or different abstraction levels for process element names is the use of ontology-based descriptions of process models. So-called semantic business process models promise to support business process interoperability and interconnectivity. But, for (semi-) automatic process interoperability and interconnectivity two problems need to be solved. How can similar terms for process element names be automatically discovered and how can semantic business process composition be facilitated. In this paper we will present solutions for these problems based upon an OWL DL-based description of Petri nets.