In-Machining Optimization
Automatically adjusting machining parameters using real-time data feedback loops to enable in-machining process optimization.
Industry Challenges
Over the last few decades we are seeing exciting opportunities for innovation resulting from rapid advancements in IoT, sensor, Big Data, and Industry 4.0 technologies.
Lack of skilled resources in the future.
Shifting skillsets towards digital competencies.
Increasing efficiencies and productivity whilst eliminating waste.
Adopting digitalization and automation.
Reaching sustainability targets set by governments and companies.
In-Machining Optimization: An exciting topic for the future of intelligent machining
Concepts such as In-Machining Optimization bring immense value to our industry by automatically adapting machining parameters such as feed rates and spindle speeds to enable live process optimization.
Value proposition
Improve productivity and reduce set up times.
Increase sustainability by reducing the number of scrap parts and managing tool wear.
Increased machining quality by controlling unexpected anomalies arising due to inhomogeneous workpiece material, machine health and/or tool variations.
Enabling process automation through autonomous adaptive control of cutting parameters.
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