Fuzzy regression method for prediction and control the bead width in the robotic arc-welding process

Journal of Materials Processing Technology

Volumn 164-165, Issue , 2005, Pages 1134-1139

  Xue, Yu ^a   Kim, I S ^a   Son, J S ^a   Park, C E ^a   Kim, H H ^a   Sung, B S ^a   Kim, I J ^a   Kim, H J ^b   Kang, B Y ^b  

^a Mokpo National University   (South Korea)

^b Korea Institute of Industrial Technology   (South Korea)

Author keywords

Artificial intelligence (AI) technology; Bead width; Fuzzy linear regression method; Robotic GMA welding; Taguchi method

Indexed keywords

ARTIFICIAL INTELLIGENCE; CONTROL SYSTEM ANALYSIS; FUZZY SETS; LINEAR EQUATIONS; REGRESSION ANALYSIS; ROBOTICS; CUSTOMER SATISFACTION; ELECTRIC ARC WELDING; MATHEMATICAL MODELS; TAGUCHI METHODS; WELDING;

ARTIFICIAL INTELLIGENCE (AI) TECHNOLOGY; BEAD WIDTH; FUZZY LINEAR REGRESSION METHOD; ROBOTIC GMA WELDING; TAGUCHI METHOD;

ELECTRIC ARC WELDING; ROBOTICS;

ARTIFICIAL INTELLIGENCE TECHNOLOGIES; AUTOMATED WELDING SYSTEMS; BEAD WIDTH; FUZZY LINEAR REGRESSION METHOD; MANUFACTURING INDUSTRIES; PREDICTION AND CONTROL; QUALITY CHARACTERISTIC; ROBOTIC GMA WELDING;

EID: 17844367854     PISSN: 09240136     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jmatprotec.2005.02.174     Document Type: Article

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