Integrated Computer-Aided Engineering

In this paper, we develop an intelligent system to approach dynamical optimisation problems emerging in control of complex systems. In particular our proposal is to exploit the adaptivity of an artificial life (alife) environment in order to achieve “not control rules but autonomous structures able to dynamically adapt and to generate optimised-control rules”. The basic features of the proposed approach are: no intensive modelling (continuous learning directly from measurements) and capability to follow the system evolution (adaptation to environmental changes). The suggested methodology has been tested on an energy regulation problem deriving from a classical testbed in dynamical systems experimentations: the Chua's circuit. We supposed not to know the system dynamics and to be able to act only on a subset of control parameters, letting the others vary in time in a random discrete way. We let the optimisation process searching for the new best value of performance, whenever a drop due to changes in fitness landscape occurred. We present the most important results showing the effectiveness of the proposed approach in adapting to environmental non-stationary changes by recovering the optimal value of process performance.

This paper proposes a new method to split colour images into regions. The only input information is the image to be segmented. Hence, this is a blind colour image segmentation method. It consists of four subsystems: preprocessing, cluster detection, cluster fusion and postprocessing.

Proofs are given for the significant properties that we have found. It is not necessary to specify the number of regions in advance, which is a significant improvement over the standard competitive-style strategies. Finally, simulation results are given to demonstrate the performance of this method for some images.

Mass-customized production systems are challenging in that they intend to provide custom-specific products at the price of conventional mass production. Since this also includes small production volumes, the manufacturing systems must achieve flexibility, easy reconfigurability, and a totally product-oriented approach. In this paper, we introduce a flexible-automation model developed within the scope of the European Union-funded PABADIS project (Plant Automation Based on Distributed Systems) that meets these requirements by combining Plug-and-Participate technology with software agents.

Contemporary workflow management systems are driven by explicit process models, i.e., a completely specified workflow design is required in order to enact a given workflow process. Creating a workflow design is a complicated time-consuming process and typically, there are discrepancies between the actual workflow processes and the processes as perceived by the management. Therefore, we propose a technique for rediscovering workflow models. This technique uses workflow logs to discover the workflow process as it is actually being executed. The workflow log contains information about events taking place. We assume that these events are totally ordered and each event refers to one task being executed for a single case. This information can easily be extracted from transactional information systems (e.g., Enterprise Resource Planning systems such as SAP and Baan). The rediscovering technique proposed in this paper can deal with noise and can also be used to validate workflow processes by uncovering and measuring the discrepancies between prescriptive models and actual process executions.

Seller-driven business models (e.g. online bookstores) have been successfully implemented and concretized in Electronic Commerce both in practice and science in the last years. In contrast to this we can depict that more customer-driven business models are implemented in the beginning. One major problem of customizable products and services in Electronic Commerce can be found in the adaptation of the human advisory activity which is inevitable in the traditional sale. For this reason we depict the customization in the customer's view and the corresponding business models in electronic markets. Main focus will be on the improvement of the communication interface between customer and seller in order to better specify the output, especially for customer-driven output. At this point we suggest an IT-enabled consulting component which creates predictions for the customer's specification by using association rules.

The purpose of this paper is, on the one hand, to identify to define and classify customization requirements and, on the other hand, to evaluate how generic modeling and configuration assistance within the Constraint Satisfaction Problem (CSP) framework can fulfil the requirements. The aim is to provide commercial configurator knowledge base designers with constraint based generic modeling elements for customizable industrial product. A first part recalls the main trends of the configuration problem. In a second part divided in four sections corresponding with different requirement set; each section proposes a definition of the requirement set, some CSP based modeling elements and a discussion about adequacy of relevant configuration assistance techniques.

Two interconnected sub-problems, i.e. scheduling of independent, non-preemptive tasks on unrelated executors as well as motion control of a group of moving executors performing the tasks, which form a two-level manufacturing operation system are investigated. As the performance index of the two-level system the makespan is assumed. For the motion control sub-problem a knowledge based pattern recognition procedure is used. The procedure is treated as a co-ordinator of movements of separate executors and allows avoiding their possible collisions. The knowledge-based pattern recognition problem is solved using the logic-algebraic method. An expert is assumed to be the source of knowledge about collisions, which is given in the form of logic expressions. Two heuristic solution algorithms for the two-level system are presented. The first algorithm ensures the current modification of solutions for the scheduling sub-problem during the control procedure of the two-level system. In the second one the on-line procedure is used, which enables determination of the best solution in the current decision step of the control procedure. Both algorithms are compared via computer simulation and examples of results are presented. A numerical example for both solution algorithms is also given. It concerns the selected process in a discrete manufacturing system.

Most commercially-operated traffic and transport systems are incumbent upon a central control, which offers only little scope for non-standard customer's requests. In most cases the customer has to orientate himself at fixed timetables as well as at given transport lots of the transport means. This paper therefore pursues the approach to make transport systems much more flexible by using decentralized transport control. In order to achieve this objective, the transport system concerned is to be divided into independent decentralized units that interact with each other in form of an agent system. First a description language based on Petri nets (PrT-nets) will be introduced which describes all relevant components of a transport system, particularly in order to carry through the transport disposition. The represented agent system furthermore offers the simple possibility of integrating components of the market economy, such as vehicle suppliers, conducting companies, big customers or service industries.