Development of a knowledge-based and collaborative engineering design agent

In order to avoid errors in engineering design that affect the later product life cycle, especially the manufacturing process, an analysis or evaluation has to be performed at the earliest possible stage. As this evaluation is very knowledge-intensive and often this knowledge is not directly available to the engineer, this paper presents an approach for a knowledge-based and collaborative engineering design agent. The technology based on multi-agent systems enables problem-solving support by an autonomous knowledge-based system which has its own beliefs, goals, and intentions. The presented approach is embedded in a CAD development environment and validated on an application example from engineering design

MAP-NBV: Multi-agent Prediction-guided Next-Best-View Planning for Active 3D Object Reconstruction

We propose MAP-NBV, a prediction-guided active algorithm for 3D reconstruction with multi-agent systems. Prediction-based approaches have shown great improvement in active perception tasks by learning the cues about structures in the environment from data. But these methods primarily focus on single-agent systems. We design a next-best-view approach that utilizes geometric measures over the predictions and jointly optimizes the information gain and control effort for efficient collaborative 3D reconstruction of the object. Our method achieves 22.75% improvement over the prediction-based single-agent approach and 15.63% improvement over the non-predictive multi-agent approach. We make our code publicly available through our project website: http://raaslab.org/projects/MAPNBV/Comment: 7 pages, 7 figures, 2 tables. Submitted to MRS 202

A multi-agent approach for design consistency checking

The last decade has seen an explosion of interest to advanced product development methods, such as Computer Integrated Manufacture, Extended Enterprise and Concurrent Engineering. As a result of the globalization and future distribution of design and manufacturing facilities, the cooperation amongst partners is becoming more challenging due to the fact that the design process tends to be sequential and requires communication networks for planning design activities and/or a great deal of travel to/from designers' workplaces. In a virtual environment, teams of designers work together and use the Internet/Intranet for communication. The design is a multi-disciplinary task that involves several stages. These stages include input data analysis, conceptual design, basic structural design, detail design, production design, manufacturing processes analysis, and documentation. As a result, the virtual team, normally, is very changeable in term of designers' participation. Moreover, the environment itself changes over time. This leads to a potential increase in the number of design. A methodology of Intelligent Distributed Mismatch Control (IDMC) is proposed to alleviate some of the related difficulties. This thesis looks at the Intelligent Distributed Mismatch Control, in the context of the European Aerospace Industry, and suggests a methodology for a conceptual framework based on a multi-agent architecture. This multi-agent architecture is a kernel of an Intelligent Distributed Mismatch Control System (IDMCS) that aims at ensuring that the overall design is consistent and acceptable to all participating partners. A Methodology of Intelligent Distributed Mismatch Control is introduced and successfully implemented to detect design mismatches in complex design environments. A description of the research models and methods for intelligent mismatch control, a taxonomy of design mismatches, and an investigation into potential applications, such as aerospace design, are presented. The Multi-agent framework for mismatch control is developed and described. Based on the methodology used for the IDMC application, a formal framework for a multi-agent system is developed. The Methods and Principles are trialed out using an Aerospace Distributed Design application, namely the design of an A340 wing box. The ontology of knowledge for agent-based Intelligent Distributed Mismatch Control System is introduced, as well as the distributed collaborative environment for consortium based projects

DETC2006-99149 AN AGENT-BASED APPROACH TO COLLABORATIVE PRODUCT DESIGN

ABSTRACT The growth of computer science and technology has brought new opportunities for multidisciplinary designers and engineers to collaborate with each other in a concurrent and coordinated manner. The development of computational agents with unified data structures and software protocols can contribute to the establishment of a new way of working in collaborative design, which is increasingly becoming an international practice. In this paper, we first propose a computational model of collaborative product design management aiming to improve the efficiency and effectiveness of the cooperation and coordination among participating disciplines. Then, we present a new framework of collaborative design which adopts an agent-based approach and relocates designers, managers, systems, and supporting agents in a unified knowledge representation scheme for product design. An agent-based system is now being implemented and the design of a set of dinning table and chairs is chosen to demonstrate how the system can help designers in the management and coordination of the collaborative product design process. INTORDUCTION Increasing product complexity, explosive global competition, and rapidly changing customer's demands are forcing product manufacturers to improve the efficiency of design decision-making and shrink design cycle times. Advances in the computer science and technology have opened new opportunities for multidisciplinary designers and engineers to collaborative with each other more efficiently and effectively. Collaborative design can create added value in the design and production process by bringing the benefit of team work and cooperation in a concurrent and coordinated manner. Also, it help reduce the loss of efficiency resulted from potential conflicts and misunderstandings among team members. However, the difficulties arising from the requirements for design coordination mixed with differences among heterogeneous system architectures and information structures tend to undermine the effectiveness and the success of collaborative design among multidisciplinary designers. Recently, agent technology has been recognized by more and more researchers as a promising approach to analyzing, designing, and implementing industrial distributed systems. An intelligent agent consists of self-contained knowledge-based systems capable of perceiving, reasoning, adapting, learning, cooperating, and delegating in a dynamic environment to tackle specialist problems. The way in which intelligent software agents residing in a multi-agent system interact and cooperate with one another to achieve a common goal is similar to the way that human designers collaborate with each other to carry out a product design project. Thus, we believe that a collaborative product design environment implemented by taking an agentbased approach will be capable of assisting human designers or design teams effectively and efficiently in collaborative product design. In this paper, based on the analysis of the characteristics of a collaborative design process, we first propose a computational model of collaborative product design management to improve

A Generic Conceptual Model for Risk Analysis in a Multi-agent Based Collaborative Design Environment

Organised by: Cranfield UniversityThis paper presents a generic conceptual model of risk evaluation in order to manage the risk through related constraints and variables under a multi-agent collaborative design environment. Initially, a hierarchy constraint network is developed to mapping constraints and variables. Then, an effective approximation technique named Risk Assessment Matrix is adopted to evaluate risk level and rank priority after probability quantification and consequence validation. Additionally, an Intelligent Data based Reasoning Methodology is expanded to deal with risk mitigation by combining inductive learning methods and reasoning consistency algorithms with feasible solution strategies. Finally, two empirical studies were conducted to validate the effectiveness and feasibility of the conceptual model.Mori Seiki – The Machine Tool Compan