There has been a sharp rise of data collection systems on the shop floor such as Data Historians, I-IoT, OEE Systems and MES. Companies have more data about their manufacturing processes than ever before. What is often lacking is the ability to find the most critical pieces of data in all the noise.
This problem can be solved through people or through software. However, most manufacturing organizations do not have data science experts, nor do most data science people in companies have enough operations knowledge to be effective.
The other approach involves implementing systems that employ advanced techniques to mine the data automatically. These systems can the provide the users with a list of prioritized problems to be addressed.
In this webinar, we will cover how this can be implemented across a range of manufacturing and system environments.