Combination of a Discrete Event Simulation and an Analytical Performance Analysis through Model-Transformations

Porzucek, Tomasz; Kluth, Stephan; Fritzsche, Mathias; Redlich, David

doi:10.1109/ecbs.2010.26

Cited by 5 publications

(5 citation statements)

References 14 publications

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“…FMC-QE [37]. Generally speaking, the biggest advantage is that instant results can be computed, which is why analytical techniques are preferably used in high-level analyses like optimisation were thousands of different cases have to be analysed as fast as possible.…”

Section: Analysis Types For Reasoning On Bpm@rtmentioning

confidence: 99%

“…Generally speaking, the biggest advantage is that instant results can be computed, which is why analytical techniques are preferably used in high-level analyses like optimisation were thousands of different cases have to be analysed as fast as possible. Disadvantages are that they typically are only simplified approximations (e.g., conditional loop behaviour hard to be represented by a formula [37]), impose additional constraints and are difficult to use [5]. -Simulation "... attempts to mimic real-life or hypothetical behaviour" [61].…”

Section: Analysis Types For Reasoning On Bpm@rtmentioning

confidence: 99%

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Research Challenges for Business Process Models at Run-Time

et al. 2014

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Abstract. Today's fast and competitive markets require businesses to react faster to changes in its environment, and sometimes even before the changes actually happen. Changes can occur on almost every level, e.g. change in demand of customers, change of law, or change of the corporate strategy. Not adapting to these changes can result in financial and legal consequences for any business organisation. IT-controlled business processes are essential parts of modern organisations which motivates why business processes are required to efficiently adapt to these changes in a quick and flexible way. This requirement suggests a more dynamic handling of business processes and their models, moving from design-time business process models to run-time business process models. One general approach to address this problem is provided by the community of models@run.time, in which models reflect the system's current state at any point in time and allow immediate reasoning and adaptation mechanisms. This paper examines the potential role of business process models at run-time by: (1) discussing the state-of the art of both, business process modelling and models@run.time, (2) reflecting on the nature of business processes at run-time, and (3) most importantly, highlighting key research challenges that need addressing to make this step.

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Section: Analysis Types For Reasoning On Bpm@rtmentioning

confidence: 99%

Section: Analysis Types For Reasoning On Bpm@rtmentioning

confidence: 99%

Research Challenges for Business Process Models at Run-Time

et al. 2014

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“…In this second approach, in addition to the extracted historical performance data, BP Scenario information about control workflow, involved roles and resources are utilised in a discrete event simulation (Robinson, 1964). The beneficial effect of using simulation over analytical methods for predicting PPIs is discussed in (Redlich and Gilani, 2011) and (Porzucek et al, 2010). Figure 1 shows the general concept for extracting Historical (and current) PPI data plus the two approaches of how to compute the Predicted PPI data via Analytical Prediction (horizontally striped) and Prediction via Simulation (vertically striped).…”

Section: Analytical Prediction Eventsmentioning

confidence: 99%

“…The two main approaches to compute PPI predictions are described in Section 2. Our framework employs the second approach, Prediction via Simulation, because it preserves the control flow information of the targeted BPs and thereby helps to exploit the benefits of behavioural simulations (Porzucek et al, 2010). Additionally, the KPI prediction process via BD simulation is orchestrated following the BD life cycle provided in Section 3 (shown in figure 2).…”

Section: An Advanced Business Simulation Frameworkmentioning

confidence: 99%

Business Model Design An Evaluation of Paper-based and Computer-Aided Canvases

Fritscher

Pigneur

2014

Proceedings of the Fourth International Symposium on Business Modeling and Software Design

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“…Angelidis et al [33] introduce a generic simulator incorporating realistic schedules, priority rules, and resource restrictions designed specifically for the simulation of complex assembly lines. Porzucek et al [34] use an analytical performance prediction approach to improve the performance of discrete event simulation. They evaluated their method based on an industrial case study.…”

Section: Background Of the Researchmentioning

confidence: 99%

Performance and Improvement of Production Line Function Using Computer Simulation (Case Study: An Iron Foundry)

Saidabad¹,

Taghizadeh²

2015

AJCM

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Using the accurate methods and tools for evaluation of function in different areas is of great importance. In recent years, much more studies have been done on the nature and methodology of function evaluation in organizations and its improvement. This study aimed to evaluate and improve the function of production line through computer simulation in one of the iron foundries in Iran. For this purpose, at first data has been gathered on the basis of timing with chronometer for each one of the production line machineries and using this data, distribution functions governing the activity cycle of each one of these machineries have been determined; and then, using the required gathered data for computer simulation (taking the advantage of "ED" simulation software), a model was simulated to introduce the current situation of production line and the validity of simulated model was measured on the basis of production rate. And then, considering the criteria such as the production rate, average waiting time, machine utilization coefficient, production yield, production cost, production income and the production time production line function was evaluated. Finally, applying amendment changes on the simulated model improved model was offered.

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Combination of a Discrete Event Simulation and an Analytical Performance Analysis through Model-Transformations

Cited by 5 publications

References 14 publications

Research Challenges for Business Process Models at Run-Time

Research Challenges for Business Process Models at Run-Time

Business Model Design An Evaluation of Paper-based and Computer-Aided Canvases

Performance and Improvement of Production Line Function Using Computer Simulation (Case Study: An Iron Foundry)

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