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.
