scholarly journals Visualization in Collaborative Engineering Design

2000 ◽  
Author(s):  
Patricia M. Jones ◽  
Beth A. Brucker ◽  
Van J. Woods ◽  
Blessing F. Adeoye
2018 ◽  
Author(s):  
Tehya Stockman ◽  
Claire Kincaid ◽  
Thomas Heale ◽  
Steven Meyer ◽  
Alexandra Strong

Author(s):  
Li Zhao ◽  
Yan Jin

Collaborative engineering design requires multiple people working together to achieve a common goal. Data sharing approach and workflow management approach have been developed to support collaborative design, but the disconnection of these two approaches has led to problems of efficiency and adaptability. In this paper, we propose a work structure based approach for collaborative design. Our goal is to improve process efficiency and adaptability by integrating management processes with engineering details and allowing designers to make certain managerial decisions through peer coordination. For a specific task, a work structure is a network of engineering work items connected by dynamically acquired engineering dependencies. It is used to generate multiple processes from which the one that best fits the current situation is dynamically determined through coordination among team participants. In order to capture engineering dependencies and associate engineering details, an adaptive work process model is developed that explicitly represents engineering work, work structure, and processes. Based on this model, a set of operations and algorithms are developed for intelligent agents to provide coordination support. Experiments have shown that by following this approach, engineering design processes can dynamically adapt to both requirement and resource changes, and the process efficiency can be significantly improved.


Author(s):  
Qi Hao ◽  
Weiming Shen ◽  
Zhan Zhang ◽  
Seong-Whan Park ◽  
Jai-Kyung Lee

Agent technology is playing an increasingly important role in developing intelligent, distributed and collaborative applications. The innate difficulties of interoperation between heterogeneous agent communities and rapid construction of multi-agent systems have motivated the emergence of FIPA specifications and the proliferation of multi-agent system platforms or toolkits that implement FIPA specifications. In this paper, a FIPA compliant multi-agent framework called AADE (Autonomous Agent Development Environment) is presented. This framework, originating from the engineering fields, can facilitate the rapid development of collaborative engineering applications (especially in engineering design and manufacturing fields) through the provision of reusable packages of agent-level components and programming tools. An agent oriented engineering project on the development of an e-engineering design and optimization environment is designed and developed based on the facilities provided by the AADE framework.


Author(s):  
Alkım Z. Avşar ◽  
Ambrosio Valencia-Romero ◽  
Paul T. Grogan

Abstract Collaborative systems design is a human-centered activity dependent on individual decision-making processes. Personality traits have been found to influence individual behaviors and tendencies to compete or cooperate. This paper investigates the effects of Big Five and Locus of Control personality traits on negotiated outcomes of a simplified collaborative engineering design task. Secondary data includes results from short-form personality inventories and outcomes of pair design tasks. The data includes ten sessions of four participants each, where each participant completes a sequence of 12 pair tasks involving design space exploration and negotiation. Regression analysis shows a statistically-significant relationship between Big Five and Locus of Control and total individual value accumulated across the 12 design tasks. Results show the Big Five, aggregating extraversion, agreeableness, conscientiousness, neuroticism, and intellect/imagination to a single factor, negatively affects individual value and internal Locus of Control positively affects individual value. Future work should consider a dedicated experiment to refine understanding of how personality traits influence collaborative systems design and propose interventions to improve collaborative design processes.


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