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Due to increasingly customized manufacturing and stricter requirements on sustainability, it is challenging to achieve energy efficient optimization for machining processes. This paper presents a novel Cyber Physical System and Big Data enabled machining optimization system to address the above challenge. An effective evolutional algorithm based on Fruit Fly Optimization is applied to generate an adaptive energy efficient schedule, and improve schedule when there are significantly varying working conditions and adjustments on the schedule are necessary. Practical case studies presented in this paper demonstrate the effectiveness and great potential of applicability of the system into practice.
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