Simon Brezovnik

Intelligent design of an unconstrained layout for a flexible manufacturing system

The presented research removes common constraints regarding the design of layout of flexible manufacturing system, and the subsequent search for a good solution is left solely to artificial intelligence. The proposed system is composed of a creative subsystem which can use different evolutionary optimization methods, and a subsystem for evaluating layouts. In the presented work the subsystem for creation uses a particle swarm optimization method for the creation/modification of solution sets. Evaluation of solution quality is made using intelligent search of the shortest travel paths within the layout. This system has proved to be innovative since it proposes very good solutions which are oriented to the main task of the system and are not simplified because of human limitations.

Modelling of intelligent robot system by reverse engineering and swarm intelligence

The paper proposes the design of the intelligent robot system by reverse engineering and optimisation of the resistance welding application. Building of the system starts with the design of the virtual robot model by reverse engineering method. By that method, the user programme interface of the older robot ACMA XR701 is modernised. Building of the system continues with the incorporation of the TCP/IP-RS232 communication interface ensuring the control of the robot through internet. In the end, superstructuring of the robot system with the optimisation module, based on the swarm intelligence, is proposed.

Intelligent Optimization Methods for Industrial Storage Systems

The presented chapter introduces intelligent methods, which can be used for designing and managing of modern warehouses. Because of the ever-increasing complexity of such systems, the traditional methods cannot assure optimal or near-optimal solutions in design and operation. Demands for high utilization, flexibility, and the capacity to work reliably, even in changeable environments, can be met by adding intelligence to artificial system. The most promising intelligent methods are evolutionary computation and swarm intelligence which are unique methods of non-deterministic solving and optimizing. They proved to be effective and robust for planning and management of real systems. Evolutionary computation and swarm intelligence are methods, which were obtained from the observation of nature. Nature has some of the best answers to the problem of design and management. Therefore, this chapter tries to present intelligent methods to wider audience, and especially to experts and students of warehousing design and management.