The Year of
AI & Machine Learning for Tooling
AI & Machine Learning
Train and deploy your AI & Machine Learning to eMoldino experienced platform.
AI & MACHINE LEARNING
The Impact on Tooling
Leading businesses rely on the power of Artificial Intelligence and Machine Learning to make the best use of their voluminous and unstructured data and identify hidden patterns and relationships within the datapoints.
eMoldino’s AI and Machine Learning powered platform utilizes dynamic tooling data to build classification, predictive, and diagnostic solutions that provide insights into the tool’s production efficiency, remaining useful life, and its health status. Leveraging the power of AI and ML algorithms on the data we collect through our sensors, we provide solutions such as predictive maintenance of tools, delivery risk forecast, and part quality prediction.
AI & MACHINE LEARNING
Traditional algorithms severely fail in finding patterns and non-linear relationships within big data. On the other hand, ML algorithms find rules to classify data or make predictions based on learned patterns without being explicitly programed to do so.
Another significant difference is the amount of data that can be processed. For the sake of accuracy, the larger the data volume, the higher the accuracy of the machine learning based models since the algorithms train on larger sets of observation and are less prone to overfitting. For traditional algorithms including statistical methods, more data means more difficulty as generalizing a rule becomes more difficult due to the presence of stochastic processes in large sets of observation.
Mitigate risk through predictive models.
Everyone wishes for the business to go as planned. However, accidents always happen and they take tolls on people who aren't prepared. Our predictive models notify you what and when to prepare.
Predictive Part Delivery Risk
Predictive Part Quality Management
By leveraging and enabling AI & ML capabilities in our platform, we can identify anomalous behaviors within a production pattern. This algorithm then converts the data into useful insights that are utilized for predictive maintenance. Commonly-known for preventing downtime and other mishaps by effectively predicting when and where tooling failure might occur, also to predict the occurrence of failure by performing maintenance.
By leveraging predictive algorithms, OEMs can forecast future performances with past performances. This type of predictive analysis assists us in understanding how long it will take manufactures to complete their tasks and complete the delivery, helping us answer questions such as;
how long will it take for task completion.
will we meet the scheduled release date?
do we have the capacity to request more products?
AI & ML can predict the quality of produced parts and notify when ever there is a potential high risk of low-quality parts. The prediction of part quality is crucial because an abnormal production pattern can lead to an occurrence of failure in the manufactured parts after a certain period of time.
MEET OUR EXPERTS
Join the journey of
AI and machine learning advancement with eMoldino
Korea Institute of Industrial Technology (KITECH) focuses on research and development of manufacturing technology using IT and artificial intelligence. eMoldino partnered with KITECH, to utilize big data and cutting-edge AI & Machine Learning technology in the field of smart molds & dies.
With the support of KITECH eMoldino has invested over three years in co-developing the industry leading tooling big data platform powered by AI & machine learning technology.
Our goal is not only to provide a service but also drive the industry forward in technological advancement.