Methodology to optimize dead yarn and tufting time for a high performance CNC by heuristic and genetic approach

Yuan Lung Lai, Pao Chyi Shen, Chien Chih Liao, Tzuo Liang Luo

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


To achieve a high productive manufacturing ability and reduce dead yarn accumulation, a novel computer numerical control (CNC) machine and an efficient methodology was proposed to generate optimal or near optimal sequences of tool paths for minimizing manufacturing time. Two methods are available to generate complicated and customized photo-based carpets: to fit pre-drawn curves on a fabric backing by using a portable tufting gun and to generate available tool paths from a computer-aided manufacturing (CAM) system for a robotic tufting gun. These two operations are not suitable for high-speed applications. The solution proposed in this study starts from the original needle location paths provided by computer graphic software to solve a traversing tuft problem (TTP). The obstacle of the innovative manufacturing process, in reducing the time of the travel path for the tufting of the CNC machine, was solved. The methodology can be easily implemented using a CAM system. Several industrial experiments were proposed, which demonstrate substantial improvements of the proposed algorithm over solutions provided by application software. Moreover, for optimizing the usage of yarn in a spindle traverse movement, we present a high-performance implementation a heuristic genetic algorithm (GA) that allows achieving the optimization task efficiently. A graphical user interface that integrates the entire process was presented.

Original languageEnglish
Pages (from-to)157-177
Number of pages21
JournalRobotics and Computer-Integrated Manufacturing
Publication statusPublished - 2019 Apr

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Mathematics(all)
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

Fingerprint Dive into the research topics of 'Methodology to optimize dead yarn and tufting time for a high performance CNC by heuristic and genetic approach'. Together they form a unique fingerprint.

Cite this