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<p>The rapid progression of Industry 4.0 has underscored the demand for intelligent welding systems capable of real-time adaptation to process fluctuations, ensuring defect-free and high-quality welds. Conventional robotic welding systems, constrained by pre-programmed parameters and lacking a closed-loop feedback system, often fail to respond effectively to variations during operation. Therefore, the aim of the current research is to develop a real-time closed-loop control system (SmartWeldX) for adaptive robotic Tungsten Inert Gas (TIG) welding to monitor and control the weld defects. This system is further divided into three modules: a robotic module, an artificial intelligence (AI) module, and a closed-loop control module. The developed system has been validated through scenario-based weld trials by adjusting the real-time welding parameters, including weld speed and current, for normal and defected weld joints. The optimum weld parameters of current and speed were 80 A and 230&#xa0;mm/min for normal weld joints. The system has dynamically adjusted the welding current to 100–120 A and reduced the weld speed to 200–210&#xa0;mm/min upon detection of lack of fusion. The system also successfully identified burnthrough, for which the current was reduced to 80–100 A and the speed to 180–200&#xa0;mm/min, and contamination prompted an increase in current to 100–120 A and a decrease in speed to 170–200&#xa0;mm/min. This system demonstrates potential for integration into intelligent manufacturing environments where adaptive control is essential to maintain weld quality under variable conditions. Its implementation can enhance automation in various sectors such as aerospace, automotive, and pipeline industries by enabling robust, defect-aware welding operations.</p>

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A real-time closed-loop control system for adaptive robotic welding: a step toward intelligent welding

  • 期刊论文

  • 发表日期：

    2025年11月19日

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  • Afrasyab Khan,
  • Salman Hussain,
  • Muhammad Jawad,
  • Wasim Ahmad,
  • Mirza Jahanzaib

摘要

The rapid progression of Industry 4.0 has underscored the demand for intelligent welding systems capable of real-time adaptation to process fluctuations, ensuring defect-free and high-quality welds. Conventional robotic welding systems, constrained by pre-programmed parameters and lacking a closed-loop feedback system, often fail to respond effectively to variations during operation. Therefore, the aim of the current research is to develop a real-time closed-loop control system (SmartWeldX) for adaptive robotic Tungsten Inert Gas (TIG) welding to monitor and control the weld defects. This system is further divided into three modules: a robotic module, an artificial intelligence (AI) module, and a closed-loop control module. The developed system has been validated through scenario-based weld trials by adjusting the real-time welding parameters, including weld speed and current, for normal and defected weld joints. The optimum weld parameters of current and speed were 80 A and 230 mm/min for normal weld joints. The system has dynamically adjusted the welding current to 100–120 A and reduced the weld speed to 200–210 mm/min upon detection of lack of fusion. The system also successfully identified burnthrough, for which the current was reduced to 80–100 A and the speed to 180–200 mm/min, and contamination prompted an increase in current to 100–120 A and a decrease in speed to 170–200 mm/min. This system demonstrates potential for integration into intelligent manufacturing environments where adaptive control is essential to maintain weld quality under variable conditions. Its implementation can enhance automation in various sectors such as aerospace, automotive, and pipeline industries by enabling robust, defect-aware welding operations.