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Simulation Based Evaluation of Service Science Productivity for Solution Providers

Simulation Based Evaluation of Service Science Productivity for Solution Providers
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Author(s): Sven M. Tackenberg (Institute of Industrial Engineering and Ergonomics, RWTH Aachen, Germany), Thomas Gärtner (Institute of Industrial Engineering and Ergonomics, RWTH Aachen, Germany), Sönke Duckwitz (Institute of Industrial Engineering and Ergonomics, RWTH Aachen, Germany)and Christopher Schlick (Institute of Industrial Engineering and Ergonomics, RWTH Aachen, Germany)
Copyright: 2012
Pages: 19
Source title: Technological Applications and Advancements in Service Science, Management, and Engineering
Source Author(s)/Editor(s): Stuart D. Galup (Florida Atlantic University, USA)
DOI: 10.4018/978-1-4666-1583-0.ch019

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Abstract

Many companies offer customized solutions by integrating services into their product portfolio. In this regard, a systematic planning for solution providers is crucial, otherwise, task sequences or the assignment of resources to achieve the business objectives can be incorrect. In order to evaluate and to raise the service productivity, service models and simulation techniques have been used to determine the sequence of activities and to assign actors and resources to tasks. In this paper, the authors demonstrate that service solutions can be prospectively modeled, simulated, and optimized. To achieve improved service productivity, the concepts for service productivity are reviewed and a Petri net based simulation approach is introduced. Tests confirm that the simulation approach is capable of calculating a number of service performance metrics that focus on the effect of a stochastic makespan for tasks and the variable assignment of actors and iterations to activities. In the validation study, a service solution process for a power plant construction is considered to analyze the external validity of the simulation model, as well as the structural validity of the corresponding computational models. Simulation results demonstrate the approach providing a convergence to a global optimal service solution.

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