The data-driven quality control offers many advantages. First of all, there is the time savings, since samples are automatically compared with a model, which reduces the usual delays. Another important advantage is that the entire product life cycle can be continuously monitored and analyzed. In this way, possible errors can be identified before they occur and / or they can be rectified at an early stage and not just at the end of the life cycle.
The third important benefit is that the quality control processes are not isolated. Instead, they are integrated into the main operation of the plant. For example, if the performance of a particular machine causes deviations in the products, machine learning models of the predictive maintenance programs in the factory can be integrated into the quality models. This means that the factory staff can make really well-founded decisions and receive several insights from the data-driven quality control processes.
Integration of multiple data sources
With data-driven quality control and initial production check service, multiple sources of external quality-related data can be integrated in real time. A factory owner could incorporate real-time customer social media reactions to a particular product or reports of customer failures into the quality models. This allows customers to become part of the factory quality processes and the factory owners can quickly address post-production issues. Customers will get the feeling that their input and feedback are being taken into account, which in the end will have a positive effect on the overall customer experience.
Conclusion
A "smart factory" or manufacturing environment refers to one of the following situations:
All factory processes, supply chains and systems have been digitized and automated as much as possible and are fully integrated
The factory processes and systems are continuously improved by analyzing the big data that the factory generates
Factory processes and systems benefit from IoT platforms and Industry 4.0 concepts
Many factory owners try to turn their factories into “smart” factories, as this means greater efficiency, productivity, a reduction in waste or scrap in their factories and the creation of new sources of income.
It can be tempting for a factory owner to focus solely on increasing production when introducing big data solutions while neglecting or ignoring other areas that can also be improved with the data. In the past, quality control has been isolated and has not benefited as much from data solutions. However, to increase revenue, production, customer satisfaction, and sales should all increase. Effective data-driven quality control can make a significant contribution to increasing customer satisfaction and sales. For this reason, it is worthwhile not to neglect integration into the factory platforms.
