In a typical CNC machining operation, a human measures the workpiece at regular intervals and then enters tool-offset values as needed into the machine control. The problem here is that people occasionally make mistakes, which can lead to scrapped parts and production delays. It can also damage an expensive machine tool.
Booster Precision Components is a multinational manufacturing company specializing in compressor wheels and other machined parts for the turbocharger industry. Management there wanted to eliminate these risks at its plant in Schwanewede, Germany, by implementing an automated machine control solution. They turned to Hexagon Manufacturing Intelligence for help.
“Their aim was to free the operator from the burden of deciding how and when to make tool offsets, a goal that’s increasingly important given the shortage of skilled labor,” recalled Stephen Graham, executive VP of metrology and production software at Hexagon. “Using our Q-DAS IMC | Intelligent Machine Control software, they’re now able to manufacture smarter, not harder.”
The term “smart manufacturing” comes up frequently at Hexagon. Graham sits at the head of a business unit that encompasses all of the company’s metrology and production software. This includes CAD/CAM and CNC toolpath simulation, reverse engineering, mold and die design, production planning, machine analytics, remote monitoring solutions and various other production and engineering-related software systems, many of which offer opportunities for integration with CNC equipment.
And yet, Graham and the Hexagon team are interested in far more than the data-sharing, islands-of-information path taken by far too many integration projects. “Our smart manufacturing vision is very much about trying to drive toward autonomy in manufacturing,” he said. “That means going way beyond conventional automation to develop systems capable of independent operation and control of industrial machinery, providing a comprehensive, end-to-end workflow.”
In Booster’s case, this involved gathering in-process measurement data from a CNC lathe and sending it to a statistical process control system—Q-DAS IMC—that analyzed the results and compared them to a preconfigured tolerance band. When adjustments were needed, the software sent the required correction to the machine tool. The system would also determine whether an actual tool change was required and alert a human accordingly—and retain all correction values for documentation.
In all, Booster has connected 34 machine tools to the Q-DAS IMC software. The continuous feedback loop provides much tighter process control than was being achieved previously, using manual corrections,” Graham said. “It also reduces the amount of time the operator was spending at the machine, as well as the risk associated with human involvement. The result was higher part quality, less scrap and significantly greater throughput. From my side, this is not only a great example of the types of solutions that are now available but also an analogy for the kind of bigger picture we’re trying to achieve in terms of driving autonomy throughout manufacturing. It was a great start.”
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