Quality has always been an area in which analytics has played a major role in manufacturing, with companies trying to minimize faults and tune product lifetime in relation to warranty coverage, saving millions in costs as a result.
Now, products are pushed into shorter lifecycles and higher degrees of configurability and customization and this pressure is shedding light on the limits of managing product quality the “old way”.
Embedded Quality Analytics is designed to allow manufacturing companies to change the status quo and perform a more effective and cheaper root-cause analysis while, at the same time, reducing warranty claims.
In the Embedded Quality Analytics environment, data is streamed from the product to the quality team with feedback on faults, actual product usage by the client and environment conditions: this new information set crunched with machine learning algorithms will allow to check what is really going on – and wrong – in the everyday life of the product.
Using Embedded Quality Analytics you will be able to immediately track a faulty supplier or detect types of usages that are creating higher faults than planned, without having to wait for products to come back to support. Less support means minor costs but will be even more beneficial in terms of customer experience and satisfaction.
Finally, Embedded Quality Analytics will also turn the table on warranty: machine learning will detect optimal use regimens to be included as limits in warranty and being proactive in alerting clients of out of warranty usage, thus allowing for an even lower fault rate.