Management of 3D Printing Processes: Enhancing Pick-and-Place Machine Quality with Taguchi and Principal Component Analysis

Authors

  • Chien-Yi Huang * Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, Taiwan. https://orcid.org/0000-0001-7811-2510
  • Ya-Wei Chung Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, Taiwan.

https://doi.org/10.22105/w35wyr75

Abstract

3D printing techniques are now thriving and extensively used in producing cultural and creative individualized goods. In the present economic development of Taiwan, the electronics manufacturing industry has the highest output value. This study aimed to introduce 3D printing techniques in the electronics manufacturing sector, taking the printing of automatic insertion parts clip bodies as an example. The assembling will fail if an object's quality characteristics fail to meet the standard. This study established four key quality characteristics: the inside diameter of the left and right holes, the outside diameter of the locating point, the height of the locating point, and the middle recess thickness. The tolerance determination of the Taguchi quality loss method was used to establish the manufacturer tolerance of the print object. A printing parameter optimization experiment was then conducted to upgrade the overall quality. Principal Component Analysis (PCA)  was used to propose the optimum parameter combination: PLA material, a fill thickness of 0.16mm, a wall thickness of 0.8mm, a bottom/top thickness of 1.2mm, an infill density of 50%, a printing speed of 20mm/s, and an extruder head temperature of 220℃. Finally, the benefit was assessed, considering the required cost for production, including the purchase cost, depreciation, amortized cost, creation of the 3D model file, the labour cost of operating the printer object subsequent surface treatment and component assembly, and the material cost for the print object and support structure.

Keywords:

‎3D printing‎, Automatic insertion‎, Manufacturer tolerance‎, Taguchi method‎, Benefit assessment

References

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Published

2024-08-04

Issue

Vol. 1 No. 2 (2024): Management Analytics and Social Insights

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How to Cite

Management of 3D Printing Processes: Enhancing Pick-and-Place Machine Quality with Taguchi and Principal Component Analysis. (2024). Management Analytics and Social Insights, 1(2), 154-170. https://doi.org/10.22105/w35wyr75

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