Canvas Category: Software : Operational Technology : Industrial Robot
Automate welding of high-mix products. With ABAGY software, you can use welding robots even for custom projects and one-of-a-kind parts. No need to program robots. Just click and weld.
Welding and the Automation Frontier
There are two main types of welding to consider when talking about welding automation. The first is resistance welding. With resistance welding, the parts to be welded are pressed between two electrodes. Current then runs across the electrodes, and the electrical resistance of the metal between them causes the parts to heat up, melt, and weld together. Resistance welding can be done as “spot welding” (where just a single point is welded), or as “seam welding” (where a continuous seam is welded). Resistance welding is generally used to join thin materials, such as sheet steel. The second type of welding is arc welding. With arc welding, an electric arc is created between a metal electrode and the metal to be welded, and the heat of the arc melts the metal. The arc is then moved along the joint to be welded. There are several different types of arc welding, such as MIG, TIG, and SMAW, which differ in things like the material of the electrode, whether the electrode is consumed in the process, and how the weld is shielded from the air. In addition to these, there are other types of welding such as forge welding, laser welding, friction welding, and oxyacetylene welding. But for the last 100 years most welding, and most welding automation, has been done with either resistance or arc welding.
Advancing welding automation technology, then, seems to have mostly taken tasks that were already automated to some degree, and made them more efficient. Better welding robots and weld sensors reduced the need for expensive machine retooling, and reduced the number of machine operators. It’s had comparatively less effect on skilled welder employment - better sensors, cobots, and portable welding rigs have changed the calculus somewhat, but a robotic welding system is still far less capable than a manual welder in terms of the sort of variation that it can cope with and the sorts of problems it can solve.
🦾🧑🏭 The Robotization of High-mix, Low-volume Production Gains Momentum
One company, ABAGY, overcomes the limitations of traditional robotics. With this software, manufacturers can use robots for custom projects or even one-of-a-kind parts. No robot programming is required. The software automatically generates a robot program to produce a specific product, which only takes minutes. Using machine vision, the system scans the parts and adjusts the robot’s path depending on the actual position and deviations of the product.
A manufacturer in Sabetha, Kan., already had a robotic cell, but wanted to increase its utilization. The robotic cell was used for a limited number of parts because the programming was tedious. After implementing a new system with AI and machine vision, the setup time reduced dramatically — only 10-to-15 minutes for a new product — and the robot can now be used for many more products. It used to take 90-to-120 minutes to program a robot to produce one rotor. That’s a big win for a manufacturer with high-mix production. In the first month of the robotic cell’s operation, the company created 50 different technical charts. The company plans further robotization of production.
Cycle Time with Robots. Faster or Slower?
Can Large Language Models Enhance Efficiency In Industrial Robotics?
One of the factors that slow down the penetration of industrial robots into manufacturing is the complexity of human-to-machine interfaces. This is where large language models, such as ChatGPT developed by OpenAI, come in. Large language models are a cutting-edge artificial intelligence technology that can understand and respond to human language at times almost indistinguishable from human conversation. Its versatility has been proven in applications ranging from chatbots to language translation and even creative writing.
It turns out that large language models are quite effective at generating teach pendant programs for a variety of industrial robots, such as KUKA, FANUC, Yaskawa, ABB and others.