The Evolution and Required Transformation of Statistical Process Monitoring
In Industry 4.0, there is a need for automated diagnosis of process monitoring alarms along with root cause determination and process adjustment. Computationally intensive and adaptable approaches such as those incorporated into ProcessMiner software are required for...Three Common Misconceptions About AI in Manufacturing
Artificial intelligence (AI) and machine learning (ML) are creating quite a name for themselves in the manufacturing industry and for good reason. Both AI and ML are helping manufacturers use factory data to streamline operations, improve processes and make better...Manufacturing’s Perfect Storm
US Manufacturing Supply Chain Unprepared for Record Surge in Demand By: Tom Tulloch, Chief Commercial Officer, ProcessMiner™ Manufacturing is forecast to come roaring back in the second half of 2021, according to many leading indices. This is fantastic news for...Bringing Industry 4.0 to You
The Industrial Revolution paved the way for the life we know today and far surpassed the era of simplistic conveyor belts and heavy manual surveillance. Production lines employ machinery and humans alike. Industries have always stepped up with technological advancement and thereby use a plethora of devices designed and produced to meet specific tasks on factory grounds.
Variability Reduction: Why Important To Manufacturers?
A real-world dataset is provided from the pulp-and-paper manufacturing industry. The dataset comes from a multivariate time series process. The data contains a rare event of paper break that commonly occurs in the industry. The data contains sensor readings at regular time-intervals (x’s) and the event label (y).