Quality Control
[wtm_use_case_cats]
Data analytics can also be used to ensure your products meet certain quality control standards. If you’re manufacturing food products, the packaging and ingredients directly affect product quality. By analyzing and monitoring all the components along your supply chain, scanning the quality of incoming materials, you can use this data to identify different ways to improve quality control.
Temperature-sensitive products like vegetables, fruits, milk, ice-cream demand accurate environmental conditions and can get damaged in case of temperature fluctuations.
Specific IoT-driven sensors, which process, analyze, and transfer the data to all parties in real-time, providing the ability to monitor the full supply chain cycle is the perfect solution here. While using Big Data, it is possible to timely replace the damaged products with new ones or perform preventive measures. Big Data-powered software and hardware can also be adopted and used along with production processes, scanning the quality of incoming materials and final products.
Benefits for the company
Catching these issues before they reach consumers preserves the brand’s integrity, protects from negative feedback, and sets company on track toward sales growth.
Feasability
High
Type of expertise/ AI domain
Orthogonal Partial Least Squares , IoT, Big Datav
Internal data required
the quality of incoming materials
The food processor enters start and stop times for various stages of the process. Sorting, washing, packaging, and placing in cold storage can all be tracked with automated sensors.
Again, the product is monitored on its way from the processor to the grocer or restaurant. Any delays that could cause the food to spoil prematurely can be easily identified.