Industrial internet of things (IIoT) is going to initiate a paradigm shift in product quality management. From the quality control of incoming parts, all the way to installation, it is possible to have a data driven quality approach to isolate and eliminate the source of bad quality parts and poorly operating processes.

Tracking quality of various factors within a production system should be centralized with the ability to view and monitor them easily in order to detect problem areas of the process. Factors can include quality of compressed air/ air quality, quality of the fitting of two parts by automation, belt tightening and loosening in large belt drives, tracking vacuum/pressure in pneumatic systems, vibration signatures of final product (motors, pumps, blowers, etc.).

Commercial buildings

Production Quality Control (In-Process)

Quality control during production is an important aspect of reducing cost caused by misaligned equipment or faulty equipment. When a machine is misaligned, operating incorrectly, or faulty, then parts or products produced by that piece of equipment may have poor fitting, tolerances that do not meet specifications, or incorrect yields for a desired product.

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Commercial buildings

Post Production Quality Control (Post-Process)

Although the Quality Management Software (QMS) module of a Manufacturing Enterprise System (MES) is nothing new, quality data from finished products are still rudimentary for most industries other than the heavily regulated pharmaceutical/biotech industry. Quality control of the data that assess damage from transportation, or incorrect or out of spec installation is almost non-existent.

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