Intelligent Weld Manufacturing: Role of Integrated Computational Welding Engineering

David, Stan A.; Chen, Jian; Feng, Zhili; Gibson, Brian T.

doi:10.1007/978-981-10-7043-3_1

Title: Intelligent Weld Manufacturing: Role of Integrated Computational Welding Engineering

Journal Article · Sat Dec 02 00:00:00 EST 2017 · Transactions on Intelligent Welding Manufacturing

DOI:https://doi.org/10.1007/978-981-10-7043-3_1· OSTI ID:1429199

David, Stan A. ^[1];

^[1];

^[1]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

A master welder uses his sensory perceptions to evaluate the process and connect them with his/her knowledge base to take the necessary corrective measures with his/her acquired skills to make a good weld. All these actions must take place in real time. Success depends on intuition and skills, and the procedure is labor-intensive and frequently unreliable. The solution is intelligent weld manufacturing. The ultimate goal of intelligent weld manufacturing would involve sensing and control of heat source position, weld temperature, weld penetration, defect formation and ultimately control of microstructure and properties. This involves a solution to a problem (welding) with many highly coupled and nonlinear variables. The trend is to use an emerging tool known as intelligent control. This approach enables the user to choose a desirable end factor such as properties, defect control, or productivity to derive the selection of process parameters such as current, voltage, or speed to provide for appropriate control of the process. Important elements of intelligent manufacturing are sensing and control theory and design, process modeling, and artificial intelligence. Significant progress has been made in all these areas. Integrated computational welding engineering (ICWE) is an emerging field that will aid in the realization of intelligent weld manufacturing. The paper will discuss the progress in process modeling, microstructure, properties, and process control and automation and the importance of ICWE. Also, control and automation strategies for friction stir welding will be discussed.

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Research Organization:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1429199

Journal Information:: Transactions on Intelligent Welding Manufacturing, Vol. 1, Issue 2; ISSN 2520-8519

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 16 works

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