Autor: Patricia Stock

Many companies are challenged to consider in the planning process for working times not only current laws, labour contracts and their operative goals but also the time-related wishes of their employees. One can identify different types of employees which differ in their working time preferences as well as in the work load they have to deal with in their private lifes. Therefore, the working time configuration has to take the specific situation of the employees into account. Consequently, the process of the working time configuration becomes highly complex. But there are currently no tools available that allow decision-makers of a company to evaluate an intended working time model prospectively (i.e. before its realization) while taking dynamic aspects of their operations as well as the work-life balance of the employees into account. At best, the work-life balance of the employees is a key figure for the evaluation of a working time model but not a parameter during the planning ...

As a reaction to the growing demands of the market on enterprises, ever more complex procedures for production control are being developed. Most recently, self-organising procedures, which often mimic the behaviour of natu­ral systems (e.g. evolutionary or genetic algorithms), have come to the fore. The methods of Swarm Intelligence and, in particular, the Ant Colony Optimi­zation (ACO), which are characterised by their flexibility and adaptability, could serve as a basis for this. The ifab-Institute has developed a pro­cedure for the short-term, operative manufacturing control based on this approach, which will be presented in this article.

In order to achieve a flexible reaction to fluctuations in demand the operative working times have to be rearranged. Often flexible working time models are implemented, whose configurations are problematic from personnel and operative points of view. In addition, the currently available evaluation methods turn out to be highly subjective. This article will present a simulation-based working time configuration which allows for a prospective evaluation of working time models.