Milacron presents three new additions to the M-Powered suite of application. For the first time plastics processors can use predictive models to ensure optimum operation of Milacron machines under wear and tear – unlocking the full value of Predictive Analytics in manufacturing practices.
Our data science team has crafted algorithms that give operators valuable insights into the inner workings of the Milacron machine; for the first time, it allows us to quantify the impact of wear and tear as it progresses. Operators can then take smart decisions by weighing that cost against the cost of maintenance. This was only possible by close collaboration between our data scientist and the engineering team from Milacron. This is a true milestone for the industry.
Dr. Stefan Hild, Director of Data Science at ei3
One of the most important movements in the last few decades is the evolution toward lean manufacturing. As manufacturers evaluate and reform their operations to reduce waste, efficiency can reach new heights. In real-world applications, true maintenance requirements are based on many variables. Through the adoption of machine learning and advanced analytics and AI, M-Powered can now monitor signals of impending failure. When combined, these are key indicators that allow manufacturers to deploy maintenance resources; improvements accrue to manufacturing in the form of cost savings and added efficiency.
Edward Jump, M-Powered IIoT Digital Analytics Leader at Milacron
Screw Efficiency Analysis
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Fill Case Analysis
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Efficiency Report
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