Data Use Cases in Manufacturing
Improved Quality Assurance
Product quality maintenance is a top priority for manufacturers. Most manufacturers already have the data needed to significantly improve their quality levels and reduce quality-related costs. The number of quality tests needed for a product can be largely reduced using pattern recognition and predictive analytics to determine the number and type of tests truly needed, instead of performing all tests on all items.
Build to Order
The build to order production approach is extremely efficient and has been adopted widely by many businesses in varied industries. A well-defined data platform needs to be in place to analyse customer behaviour and sales data in order to benefit the most from this business model. This gives decision makers the ability to use predictive analytics to foresee order volumes on each possible configuration and adjust their supply chain accordingly.
Predictive & Preventive Maintenance
Operational data can be analysed with pattern recognition methods, meaning upcoming failures and maintenance needs can be predicted well in advance. This leads to less downtimes and lower costs related to maintenance. The lifespan of machines will also be increased as irreversible failures can be prevented.
Managing Supply Chain Risk
Big data can be used to reduce risk in the delivery of raw materials. This allows decision makers to track in advance, potential delays on a map, the ability to analyse weather statistics for tornadoes, earthquakes, hurricanes, etc. and calculate the probabilities of delays. This allows them to identify backup suppliers and develop contingency plans
Here the Adatis team share their latest perspectives on all things advanced data analytics