ML21.Industry
A plant with more than 100 different machines and more than 150 operators, producing more than 1,200 different products experienced that a large number of orders were not being fulfilled on time, for no apparent reason. CodeNext21 used several techniques to identify and eliminate the root cause of this delay. Second, the CodeNext21 monitoring dashboard continues to be used to gain real-time insight into production efficiency.
Process mining
As the first stage in this business case, process mining was used to reconstruct the manufacturing process and gain insight into the operation of the plant. Already at this stage, several anomalies in plant operations were discovered (e.g. deviations from recommended machine types)
Use case:
Increase the capacity of a complex production system with more than 100 machines.
Results:
Increased capacity by an additional 20% and saved costs on machinery.
Detecting abnormalities
Our state-of-the-art anomaly detection software made short work of detecting the anomalous factors in the production process. Some of our key findings include:
Results
Using our data analytics platform, the client identified the root cause of their delays and improved their system throughput by over 20%.
Continuous monitoring
Our real-time detection platform has built-in monitoring dashboards. The customer continues to use these dashboards to track their process in real time. This allows feedback early in the production process, eliminating delays as early as possible and not affecting delivery schedules.
