The widespread use of social media across the world can create a PR crisis for any company dealing with a #productquality issue. But not only is the brand image implicated, product quality issues can result in detrimental financial costs from product recalls.
The chase for process optimization has largely driven the adoption of #IoT solutions today. #Optimizing the plant’s performance can both directly and indirectly boost product quality, but it only paints a broad picture of each individual product’s status. In order to fully capitalise on the capabilities of #IoTapplications, companies should implement complementary product analytics tracking tools to ensure that their products are up to standard before reaching customers.
Having the right product-centric analytics are essential in the #semiconductor and #electronicsmanufacturing industries. But what are product analytics, and how can IoT tools help you measure that? Let’s find out.
What is product analytics?
On the topic of IoT, process data and analytics is more commonly known throughout the industry. Optimizing machines or specific systems in a plant through IoT applications helps to increase overall plant performance and lower maintenance and operational cost. However, process data and analytics only provides a broad overview on the quality of the final product, and misses out on the specific details needed for a comprehensive product quality report.
On the other hand, product analytics is able to capture minute details accurately that can help you improve your products significantly.
Here are some use cases of product analytics:
Tester ‘freeze’ causing a gap in data reporting Tester ‘freeze’ is the situation when consecutive products are not actually properly tested, but have their test results copied over. This tester ‘freeze’ problem often happens along the supply chain, and can result in serious lapses in product quality management.
Using statistical variations to give real-time product data and analytics Machines that have not been equipped with product analytics tools will record the test results of a product without considering the time of testing. These machines provide an average quality percentage, such as 90% or 80%, but fail to give specific details on which products along the line were affected. Product analytics can identify statistical variations and gradual degradations in test results to help us pinpoint exactly which products had defects.
Ensuring full visibility on all factory processes and outputs
Plant or supply chain operations are extremely complex. Implementing product analytics tools will ensure you get full visibility across all your inputs, processes and outputs so you can make better business decisions at the end of the day.
It’s important to track data from front to end. Product analytics data are not used in isolation. They can be applied to inform the current processes by giving insights on the areas that are lacking or problematic. In return, process analytics can also provide valuable insights to the areas where a product can be modified to better fit plant operations.
That said, product analytics can be difficult to implement! While process analytics is focused on a particular environment, such as the factory floor, product analytics requires all dimensions across the product lifecycle to be covered. Being able to track, analyse, harmonise and report all the data is no simple feat.
If product analytics is something that you’re interested to look in, consider speaking to one of our experienced consultants to help you get started on understanding what you need to implement the right tools for your company!
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