Effective engineering-change management (ECM) is a real challenge in mechanical engineering industry and manufacturing companies. Computer-aided design systems are usually connected to other systems such as ERP or product data management, but currently this integration does not provide effective means to manage engineering change (EC). While communication between multidisciplinary teams working on a project is known to have a significantly positive impact on the ECM, the communication between disciplines is generally performed solely through message exchange. Experts could feel the need to meet to agree on the requested changes, which in turn translates into longer design and manufacturing processes. There is a need for a system that assists human experts in making decisions about ECs. Such a system will considerably reduce the processing time following a change-request procedure. This paper proposes a collaborative tool named EchoMag, which assists designers and experts during the change-management process. The proposed system ensures the coherence of data between the various disciplines involved in the change process. EchoMag also assists experts in making decisions by proposing alternative solutions when change requests are not agreed upon. Software agents were used to implement EchoMag for which a prototype was developed. Results of the implementation are discussed.

Computer-aided design organizations worry much about the management of the communication between the various multidisciplinary teams working on the same project. The good management of this communication is very important for the success of the engineering change management process. Each discipline must approve or reject a change request according to its constraints and inform the other disciplines involved. Currently, the communication between the various disciplines is performed using messages. The approval or the rejection of a change request can be made only if human experts representing these disciplines meet and negotiate, which in turn can be very time consuming. Organizations thus, have a great need for a system which could automate the communication between experts and assist them in making sound engineering change decisions. Such a system could also help by reducing the time needed to verify an engineering change request therefore accelerating the production start-up and the time to market. This paper proposes an agent-based system that can manage the engineering change requests efficiently. Actually, the proposed system checks if the engineering change request does not create any inconsistency with the constraints stemming from the various disciplines. It also assists experts in making decisions by proposing alternative solutions. Each discipline is represented by an expert agent. When an inconsistency is discovered, a negotiation process among expert agents is launched. The system proposed could be easily connected to various CAD tools.

This paper presents a multi-agent architecture and a supporting data structure suited for the verification of constraints in a mechanical engineering design context. The data structure is composed of three levels, namely an environment level, providing a link to existing mechanical engineering software, an expert level, capturing product requirements and trade knowledge through constraints formulation and finally a product level, dealing with specific products under development. Constraints and models are assigned distinctive attributes which are then exploited by the agents in their verification strategies which are rightly termed as constraints or model driven. Multi-agent task planning provides an additional level of optimization for the operation of agents in their mission to check the product against the various constraints throughout the design process.

This paper presents an efficient, noncontact measurement technique for the automatic identification of the real kinematic parameters of an industrial robot. The technique is based on least-squares analysis and on the Hayati and Mirmirani kinematic modeling convention for closed kinematic chains. The measurement system consists of a single camera mounted on the robot's wrist. The camera measures position and orientation of a passive target in six degrees of freedom. Target position is evaluated by applying least-squares analysis on an overdetermined system of equations based on the quaternion representation of the finite rotation formula. To enhance the accuracy of the measurement, a variety of image processing functions including subpixel interpolation are applied.