Welding
Assembly Line
IBM and AWS partnering to transform industrial welding with AI and machine learning
IBM Smart Edge for Welding on AWS utilizes audio and visual capturing technology developed in collaboration with IBM Research. Using visual and audio recordings taken at the time of the weld, state-of-the-art artificial intelligence and machine learning models analyze the quality of the weld. If the quality does not meet standards, alerts are sent, and remediation action can take place without delay.
The solution substantially reduces the time between detection and remediation of defects, as well as the number of defects on the manufacturing line. By leveraging a combination of optical, thermal, and acoustic insights during the weld inspection process, two key manufacturing personas can better determine whether a welding discontinuity may result in a defect that will cost time and money: weld technician and process engineer.
Material Manufacturing: New Weld Wire Reduces Failures from Hydrogen Damage
Oak Ridge National Laboratories, along with several other federal agencies, has developed a new alloy for welding applications in hopes of improving weld strength. While there are few details on the specifics of the new alloy, the welding wires created aim to reduce the effectiveness of hydrogen attack along welds.
The mechanisms of hydrogen damage are not well understood, but there are two common pathways in which hydrogen can lead to or further cracking in alloys. The localized cracking leads to a weak spot in the component, which will eventually lead to failure of the component, often below expected stress values.
Welding Defects – Types, Causes, Prevention
Modern technology allows us to perform welding techniques more efficiently. Along with numerous testing methods facilitating the discovery of different types of welding defects, the execution and correction of these imperfections is constantly getting better. Focusing on improving both the machinery and technical skill make up a difference when it comes to limiting weld defects. This leads many industries to manufacture products of higher quality than ever before.
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NovEye™ - AI In Arc Welding
Spin Welding for Plastics Assembly
At the industrial level, spin welding technology for plastics assembly has made great strides in recent years. Long gone is the need to use a drill press to rotate one part against another. Manufacturers now use state-of-the-art machines with servomotors and sensors that provide full control over speed, acceleration and deceleration, and weld and hold time to consistently produce high-quality parts with super-strong welds.
Like any welding technology, spin welding has its market niche. Tier 1 automotive suppliers and manufacturers of filters and filter housings remain the biggest users of the process. Spin-welded automotive parts include durable under-hood parts like small elbows on manifolds, valves, tanks and bottles. Another application is welding extruded tubing to molded attachments for fuel filter lines.
New Ultrasonic Welder Mode Uses Real-time Adjustments to Improve Welds
Ultrasonic welding, including the single-parameter weld modes, let electronics manufacturers meet high levels of assembly quality, especially for products built from rigid, molded plastic components. But companies that assemble products from components with more dimensional, flexural, or material-related variability have faced a tougher challenge, one typically met by in-house modifications to ultrasonic welding equipment.
To use a welder equipped with dynamic mode, operators select the single-parameter weld mode that provides the best application results to date. Then, they enter two application-specific “scores,” which act as limits for dynamic mode activity. The first is a material “density” score that characterizes the hardness or resistance of the material that is to receive the welded, staked, or inserted part. Low density scores equate to harder, more resistant materials. The second, the “reactivity” score, affects the reaction time needed to get the desired density setting. In operation, dynamic mode monitors each weld cycle, using the density and reactivity limits to adjust and improve the cycle in response to specific part-to-part variabilities throughout the production run.
Quality prediction of ultrasonically welded joints using a hybrid machine learning model
Ultrasonic metal welding has advantages over other joining technologies due to its low energy consumption, rapid cycle time and the ease of process automation. The ultrasonic welding (USW) process is very sensitive to process parameters, and thus can be difficult to consistently produce strong joints. There is significant interest from the manufacturing community to understand these variable interactions. Machine learning is one such method which can be exploited to better understand the complex interactions of USW input parameters. In this paper, the lap shear strength (LSS) of USW Al 5754 joints is investigated using an off-the-shelf Branson Ultraweld L20. Firstly, a 33 full factorial parametric study using ANOVA is carried out to examine the effects of three USW input parameters (weld energy, vibration amplitude & clamping pressure) on LSS. Following this, a high-fidelity predictive hybrid GA-ANN model is then trained using the input parameters and the addition of process data recorded during welding (peak power).
This Robotic Avatar Welds, Cuts, Lifts While Controlled By A VR Operator Over 5G
Guardian XT is the latest “highly dextrous mobile industrial robot” from Sarcos. Think of it as the top half of your body with super-strong arms, configurable attachments for different tasks, a built-in battery pack, cameras and sensors for eyes, and a 5G connection for taking orders from a remote operator who sees what the robot sees via a VR headset and wears a motion capture suit so the robot does what he or she does.
With different attachments on its arms, Guardian XT can weld, sand, grind, cut, inspect, and more. Over time the company will be developing more quick-swap attachments for more capabilities, just like an excavating company might purchase different buckets or attachments for its machinery as different jobs have varying requirements. Plus, there’s a three-fingered robotic hand coming that can hold and use many of the tools a human uses today.