Can ChatGPT Create Usable G-Code Programs?
Mike Wearne is an educational content creator at CAMInstructor, has a take on the GPT-3 G-code. “If we use a basic program that’s a drill four holes sort of thing, and compare this to someone who’s just learning G code, I would say it’s not bad,” he says. “I would give it a low B or a high C.” The overall structure was there — it put the right codes in the right places, such as G20 and G21 to switch between metric and imperial units, and G90 for absolute positioning at the top of the program. “If you’re new to G-code programming, those are usually the tough things to remember and to get in the right spot,” he notes. However, it was missing some elements, such as tool changes and spindle speeds.
Wearne also noticed a marked improvement in the G code GPT-4 produces. “It’s like GPT-4 can think more about its answers and GPT-3.5 just spits out whatever it comes up with as quick as it can,” he explains. With its most recent update, Wearne says it can program simple parts almost perfectly. Whereas GPT-3 was getting a high C or low B as a grade for its code, “For the simple parts, if we’re in G-code 101, GPT-4 is getting an A,” he says.
The Race to Automate Aerospace: A Talk with JPB Système CEO Damien Marc
“I took the decision to incorporate manufacturing into our core business. And that was a tough decision — our business is global, our competition is global, so we need to produce at the best quality and the best price,” explained Marc. “France was not necessarily the best choice in that sense, so I was going to look around and maybe buy a company. I didn’t find what I was looking for, but then I realized there was one other way I might be able to do it.”
Marc’s plan was to use CNC machines, with the business logic behind the idea that the equipment cost more or less the same no matter the country, but hiring the higher-salary workers in the French market could allow JPB to get the most value out of each machine. Marc quickly ran into trouble with this idea, as well. Much like in many of the other most heavily industrialized nations, good CNC operators that don’t already have jobs are just hard to come by. He finally settled on using CNC robots for the low-value tasks, so he could “center the operators in high-value operations.” This was a promising turning point, although it came with its own set of challenges.
“When I put two different machines in the workshop, they weren’t able to communicate with each other,” Marc said, referring attempts to connect his first CNC robot to an inspection machine. “There is no protocol. I was really surprised because my background is computer skills and electronics.” JPB ended up having to make its own programmable logic control (PLC) language in order to get the machines synced: “So, we created the communication between those two machines, and at the end, the machine for production was producing, the machine for inspection was inspecting, and the inspection machine was sending the offsets corrections to the production machine. We successfully created our first closed-loop.”
Xaba and Lockheed Martin Collaborate to Test Cognitive Autonomous Robots in Airframe Manufacturing
Xaba, developers of the first AI-driven robotics and CNC machine controller, and Lockheed Martin recently completed a collaboration to evaluate the automation of crucial manufacturing operations using the global aerospace company’s industrial robots integrated with Xaba’s proprietary physics-informed deep artificial neural network model, xCognition.
Xaba and Lockheed Martin identified a use case focused on a typical robotics work cell used in any aerospace factory to test how Xaba’s xCognition “synthetic brain” could empower a commercial robot with greater intelligence and understanding of its body and the task it is about to execute while ensuring required quality and tolerances are achieved.
Precision Manufacturing of Large and Complex Parts
Using the Toolchanger to Automate Production
The benefits of automation are potentially huge, but the investment required for a robot arm or pallet changer can be intimidating or even prohibitive. “Our customers wanted to get more usage out of their precision vises and felt they wanted to get into automation, but every time you start talking with those ballpark numbers jumping into $250,000 or $300,000 to do setups and vises, it scares so many off,” says Jon Dobosenski, general manager of Lang Technovation. This inspired Lang’s Haubex system, which it designed to be a low-cost, simple way for shops to take a first step in automation by using a feature that’s already included on many milling machines — the toolchanger.
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Predictive-Maintenance Tech Is Taking Off as Manufacturers Seek More Efficiency
Anna Farberov, general manager of PepsiCo Labs, the technology venture arm of PepsiCo Inc., said that over the past year so-called predictive-maintenance systems at four Frito-Lay plants reduced unexpected breakdowns, interruptions and incremental costs for replacement parts, among other benefits.
Developed by New York-based startup Augury Inc., the technology has helped Frito-Lay add some 4,000 hours a year of manufacturing capacity—the equivalent of several million pounds of snacks coming off the production line and shipped to store shelves, Ms. Farberov said.
Cycle Time Reduction Secrets part 1
Robots and CNC Machines - An Assembly Configuration Made in Heaven
The real challenge with manufacturing comes from making all of your equipment work together. Electrical and automation controls have been around for decades, and the technology has advanced at nearly overwhelming rates. It’s almost a guarantee that any new machine will need some sort of custom interface board or network protocol to communicate and work in harmony with the rest of the process or overall system.
Two types of machines have a tendency to be a bit more difficult for novice users to integrate into a larger system scope - robots and CNC machines.
CNC builders look to software, machine-health data, customization and modular design
The adoption of on-machine components follows the development of more and more sophisticated hardware and software for better machine-to-machine communication. Increasingly, components are using multiple protocols, facilitating deeper communication for easier access to more in-depth data. Customers of systems integrators like Methods Machine Tools want solutions for faster and more specific data collection from any protocol, in order to boost production with predictive maintenance insight.
“The emergence of data as a tool to enable real-time decision making on the shop floor is evolving how companies run and maintain their machines,” Parenteau says. Whereas old alarms signaled the presence of an issue, detailed diagnostics can instead tell operators precisely what the issue is. For example, rather than just letting an operator know how much cutting fluid is in the tank of a CNC machine, more advanced on-machine components could tell someone the viscosity and temperature of the fluid. That information can be used to improve machining processes and resolve minor issues before they become costly problems. Coolant flow is another variable that is closely monitored in CNC machine tools, as it can have a direct impact on shop productivity or part quality, he says.
How to Reduce Tool Failure with CNC Tool Breakage Detection
There are several active technologies used in CNC machining that enable manufacturers to realize these benefits. The type of system used for tooling breakage detection may consist of one or more of the following technologies.
They’re often tied to production monitoring systems and ideally IIoT platforms that can analyze tooling data in the cloud to better predict breakages in the future. One innovation in the area of non-contact technologies is the use of high-frequency data that helps diagnose, predict and avoid failures. This technology is sensorless and uses instantaneous real-time data pulled at an extremely high rate to build accurate tool failure detection models.
How to Reduce Cycle Times by 70% and more on Your Existing CNCs and Dramatically Improve Tool Life Too
Much has been made of high efficiency milling in recent years, and for good reason. Roughing cycle times can often be reduced by as much as 80% by using solid end mills, small stepovers, faster feed rates and deeper axial depths of cut. The shortcoming has been that, due to part feature obstructions or CAM system limitations, the cutting technique can often only be used in certain areas of a part so that total part cycle time reduction ends up being much more modest.
Dr. Somekh says iMachining applies a much more flexible approach with the patented ability to dynamically vary the tool cutting angle (which refers to the degree of radial engagement of the tool with the material) and the feed rate in order to maintain a constant chip thickness and load on the cutting tool. The dynamic feed rate adjustment algorithm supports material cutting angles from 10 to 80 degrees of tool engagement. Constant load and chip thickness is key to the success of iMachining, also with very small cutters and machining in hard or highly abrasive materials.
CNC Machining vs. Manual Machining
CNC machines are faster and produce less waste than their manual counterparts. Manual machines which have undergone a CNC retrofit have been shown to produce parts 75-300% faster. Increasing throughput reduces part costs by decreasing the number of man-hours required to produce each part. Also, switching tools on a CNC machine can be over four times faster than on a similar manual machine. This results in faster turnaround times to get finished parts to customers.
The higher accuracy and precision of CNC machines also produce a lower scrap rate and therefore a lower part cost.Lower scrap rates not only mean more money in your pocket upfront, but higher precision machining tends to decrease customer rejection rate as well. When you have a more precise, repeatable process, the risk for missing defects during inspection is low. This prevents the customer from receiving faulty parts which, in turn, increases customer satisfaction.