AI & MACHINE LEARNING
THE YEAR OF
AI & ML FOR
TOOLING INDUSTRY
Train and deploy your AI & Machine Learning to eMoldino experienced platform.
AI & MACHINE LEARNING
The Impact on Tooling
Leading businesses embrace the idea of Artificial Intelligence(AI) and Machine Learning because they provide a direct solution to; overwhelming data, endless data-flow, and inability to identify hidden patterns and correlations among large amount of data.
eMoldino's AI and Machine Learning algorithms examine tooling and mold data gathered over a long period of time. This enables the system to learn how to identify and classify patterns in large volumes of data and build a predictive model. Compared to the conventional method, machine learning can automatically refine the current algorithms for higher accuracy and to reach optimal results.
AI & MACHINE LEARNING
Conventional vs.
Machine Learning
Machine Learning is not merely a substitute but a supplement for the conventional approach to analyzing data. That being said, Machine learning is used to build predictive algorithms when the conventional method of analysis is unable to perform a specific task to its full capacity and efficiency.
Another significant difference is the amount of data that can be processed. For the sake of accuracy, the larger the data pool, the higher the accuracy of data as more data patterns can be compared and analyzed. There will always be a limitation to the conventional method as human errors cannot ensure 100% accurate data.
In contrast Machine Learning ultimately gains greater capability overtime by analyzing larger sets of data.
APPLICATIONS
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 Maintenance
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.
Predictive Part Delivery Risk
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;
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how long will it take for task completion.
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will we meet the scheduled release date?
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do we have the capacity to request more products?
Predictive Part Quality Management
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.
AI & MACHINE LEARNING
Tooling Big Data
Leading businesses embrace the idea of Artificial Intelligence(AI) and Machine Learning because they provide a direct solution to; overwhelming data, endless data-flow, and inability to identify hidden patterns and correlations among large amount of data.
eMoldino's AI and Machine Learning algorithms examine tooling data gathered over a long period of time. This enables the system to learn how to identify and classify patterns in large volumes of data and build a predictive model. Compared to the conventional method, machine learning can automatically refine the current algorithms for higher accuracy and to reach optimal results.
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 mold & tooling.
Dr. Jason Kim, Ph.D. of KiTECH is the Chief Technology Advisor of eMoldino who has been responsible for the implementation of AI & Machine Learning into eMoldino platform. With the support and leadership of Dr. Kim and his team, eMoldino has invested over two years in co-developing the industry leading tooling big data platform powered by AI & machine learning technology.
Learn more about Digitalization of Mold & Tooling.
Our goal is not only to provide a service but also drive the industry forward in technological advancement.
