Criteria and Application of Autonomous Cooperating Logistic Processes

Competitive enterprises have to react fast and flexible to an increasing dynamic environment. To achieve the ability to adapt on these new requirements autonomous cooperating logistic processes seems to be an appropriate method. This paper introduces a general definition of autonomous control and its meaning in a logistics context. Based on this, a catalogue of criteria is developed to ensure the identification of autonomous cooperating processes in logistic systems and its distinction to conventionally controlled processes. To demonstrate this catalogue, its criteria and the concerning properties are explained by means of an exemplary shop-floor scenario. 1 INITIAL SITUATION AND CALL FOR ACTION Over the past years an increase in structural and dynamic complexity of production and logistics systems could be observed. This development is caused by diverse changes, for example, short product life cycles as well as a decreasing number of lots with a simultaneously rising number of product variants and higher product complexity. As a result, new demands were placed on competitive companies, which cannot be fulfilled with conventional controlling methods. Conventional production systems are characterized by central planning and controlling processes, which do not allow fast and flexible adaptation to changing environmental influences. Establishing autonomous cooperating logistics processes seems to be an appropriate method to meet these demands. The idea of autonomous cooperating logistic processes is to develop decentralised and heterarchical planning and controlling methods in contrast to existing central and hierarchical aligned planning and controlling approaches [1]. Autonomous decision functions are shifted to logistic objects. In the context of autonomous control logistic objects are defined as material items (e.g. part, Published in: Gao, J.X., Baxter, D.I., Sackett, P.J. (Ed.): Proceedings of the 3rd International Conference on Manufacturing Research Advances in Manufacturing Technology and Management, Cranfield, 2005.