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Considering the potential of data-driven manufacturing, organizations need to rethink the role of quality control, in the realm of individual operations and throughout the supply chain of the entire organization. Today's manufacturers are armed with the latest software and sensors and have the ability to use data gathered from measuring equipment to improve processes at every phase of a product’s development. However, making this work requires all involved, from design engineers to CAM programmers to shop floor personnel, to participate in quality control.
As the data flows and feedback loops blur the lines between traditionally distinct roles like engineering, production, and quality control, following are the few examples of the wider implications of threading quality data throughout all the stages of a product’s development:
Machinists Become Inspectors
For a machine shop, an example of choice for leveraging the digital thread is using data collected by an on-machine probe to update tool or work offsets. Several organizations are installing this added functionality on their computer-aided manufacturing (CAM) software. The feature allows users to generate probe paths swiftly and directly integrate them into the machining cycles. It can be swapped between the two as needed so as to validate the machining process during the process. Metrology is thus integrated with production.
Inspection Bottlenecks Break
In the digital thread, data flows in the forward as well as the backward direction. The implication is that quality control (which should be thought of as a means of improving upstream processes) becomes faster and easier. For example, the truly interconnected production operation can leverage information from the CAM operation—machining speeds, feeds and other parameters—to ensure the best measurement strategy for the job.
Data Tell a Story
In an effort to work with existing shop-management software rather than replacing it, several solution providers are designing solutions for more than just painting a holistic picture of quality control within an operation. It also aims to tell a story—to illuminate why data appear as they do and to expose the trends within, thereby making that data actionable. Widely used in automotive circles, the software provides not only analysis but also analysis in the proper context.
Automation Becomes Invisible
One of the most critical functions in manufacturing is workflow management, which includes the storage and organization of all measurement documents and tasks associated with metrology. However, even an overarching resource-management product like Smart Quality can do only so much to address one key challenge of connecting and leveraging the digital thread. As often experienced by many C-suite executives, the challenge associated with using data to build intelligence into manufacturing is making sense of the sheer volume of data available. Relevant information must be extracted out even before products like those are ever leveraged.
See Also: The Manufacturing Outlook