Multi-Response Optimization of an Automated Grass-Flower Beating Machine Using Taguchi and WASPAS in Broom Production

Authors

  • Wanrop Khanthirat Department of Industrial Engineering, Faculty of Engineering and Industrial Technology, Kalasin University, Thailand
  • Surasit Phokha Department of Mechanical and Mechatronics Engineering, Faculty of Engineering and Industrial Technology, Kalasin University, Thailand
  • Waraporn Warorot Department of Industrial Engineering, Faculty of Engineering and Industrial Technology, Kalasin University, Thailand
  • Narong Wichapa Department of Industrial Engineering, Faculty of Engineering and Industrial Technology, Kalasin University, Thailand
  • Anucha Sriburum Department of Industrial Engineering, Faculty of Engineering and Industrial Technology, Kalasin University, Thailand
Volume: 15 | Issue: 5 | Pages: 27542-27550 | October 2025 | https://doi.org/10.48084/etasr.12774

Received: 16 June 2025 | Revised: 24 July 2025 and 6 August 2025 | Accepted: 11 August 2025 | Online: 6 October 2025


Corresponding author: Anucha Sriburum

Abstract

Manual grass-flower beating in traditional broom production often results in inconsistent efficiency and material damage, limiting the productivity in rural communities. This study proposes a novel hybrid optimization framework combining the Taguchi L9 orthogonal array with the Weighted Aggregated Sum Product Assessment (WASPAS) method to enhance the performance of an automated grass-flower beating machine. Three key parameters: the rotational speed, beating time, and feedstock weight, were optimized to maximize the efficiency and minimize the damage. The experimental results identified optimal settings of 100 rpm, 120 s, 120 g, yielding an average efficiency of 95.50% and a low damage score of 1.23. The novelty of this work lies in the first application of Taguchi–WASPAS to optimize the community-scale broom production equipment. The proposed approach provides a cost-effective, replicable solution for improving the product quality and reducing the labor dependency. Future studies should incorporate additional variables and predictive modeling to support a broader implementation in sustainable manufacturing systems.

Keywords:

broom production, multi-response optimization, weighted aggregated sum product assessment, Taguchi method, grass-flower beating machine

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How to Cite

[1]
W. Khanthirat, S. Phokha, W. Warorot, N. Wichapa, and A. Sriburum, “Multi-Response Optimization of an Automated Grass-Flower Beating Machine Using Taguchi and WASPAS in Broom Production”, Eng. Technol. Appl. Sci. Res., vol. 15, no. 5, pp. 27542–27550, Oct. 2025.

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Copyright (c) 2025 Wanrop Khanthirat, Surasit Phokha, Waraporn Warorot, Narong Wichapa, Anucha Sriburum

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