It isn’t always easy for manufacturers to determine what data is important for smart manufacturing data analytics, and to ensure that the right data is being collected. In many cases, the interfaces to data collection sources are complex and data isn’t standardized. Manufacturers often require vendor assistance to retrieve data from a machine and then need to invest significant time and resources in normalizing the data so it can be utilized effectively in their manufacturing analytics. Indeed, an MIT study estimates that 70% of data generated in high-tech manufacturing processes is not used! Either the data was not collected properly or there is no platform that can use the data in an intelligent manner to drive informed business decisions.
Putting manufacturing data to work in the PCB assembly factory
Download this ebook to learn about:
Common challenges to collecting good data and where collecting data makes sense for the factory business forecasting and reporting.
What makes data smart and the difference between standalone data and analytics.
How data can be distributed from underlying infrastructure for external use.
What tools are available today to help you put data-driven manufacturing principles into practice.
How data can be used to trace the sources of problems and defective or counterfeit parts.
Real-world example of how companies are hitting actionable KPIs by putting their data to good use with analytics.
Opcenter Execution Electronics IoT - MSS (Valor IoT manufacturing - Shopfloor)
Electronics & Semiconductor