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Simulation des Personaleinsatzes zur optimierten Flexibilitätsnutzung in der Produktion

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Simulation des Personaleinsatzes zur optimierten Flexibilitätsnutzung in der Produktion

Betreuer: Dr.-Ing. W. Roßdeutscher

Bearbeiter:
Christoph Jahn

Companies are always subject to fluctuations in their markets. This can be caused by economic crisis or through industry-specific market changes. To ensure in the long term the company's success and competitiveness it is essential to respond with adequate instruments and mechanisms to given market conditions. Flexibility provides one way for organizations to respond to fluctuating markets. By different instruments of flexibility a company can coordinate declines in sales and emerge stronger from crisis.
The present document is concerned with the use of personnel flexibility in the production environment. In the human resource management flexibility is used as a reactive instrument by most companies. A proactive use of flexibility instruments "before the times of crisis" is a new challenge in a modern production environment. Flexibility in the human resource management allows companies in addition to flexible manufacturing processes to adapt to fluctuating demands. A simulation model is developed in which the workforce is simulated for an optimized use of flexibility.
The main interest refers to the consideration of the functionality and the impact of flexibility. Can a company's success be positively influenced by personnel flexibility and what are the consequences arising in a social perspective for the workforce of a company? The comprehension of the functionality of different mechanisms within a flexible production environment is essential for a correct implementation and an optimized use of flexibility.
After consideration of the concept of flexibility, different instruments are described that provide a flexible adjustment of production processes on technical, organizational and personnel level. It is developed a simulation model which integrates the mechanisms of flexibility in a manufacturing company. The interactions of the various model parameters are summarized in a mathematical model. As calculating methodology the linear optimization method is used, which determines the optimum of the formulated mathematical problem. Finally models of different observation periods are evaluated in scenarios of different market demands. The functionality of the simulation model is also verified in comparison with a reference model.

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