A Quantum-assisted Diagnostics Method for Intelligent Manufacturing

Abstract

Present manufacturing machines have few methods to investigate machine health. To minimize issues and enhance the correctness of machine decisions and automation, machine health conditions require to be investigated. Therefore, the evolution of a fresh investigating and diagnostics approach for additive manufacturing machines is needed for better productivity in Industry 4.0. In the current chapter, an intelligent technique for the condition monitoring of additive manufacturing (AM) is described, where an accelerometer fitted on the extruder assembly is used to receive vibration signals. The process errors with the printer were the worn-out timing belts driving the extruder assembly. Quantum-based Support Vector Machine was simulated to identify the 3D-printer status. The simulation outcomes presented here show that this approach has better correctness as compared to the previous Support Vector Machine techniques.

Keywords: 3D Printer, Additive Manufacturing, Industry 4.0, Support Vector Machine.

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