Minimization of Airtime in Machining Process Using Non-Conventional Method


  • Christina Law Boon Hui Universiti Tun Hussein Onn Malaysia
  • Haslina Abdullah Universiti Tun Hussein Onn Malaysia


Airtime, Artificial Intelligence, Ant Colony Optimization


In machining process, the total machining time consist of the productive time and airtime. Machining airtime is a process that movement of the cutting tool before cutting the workpiece. One way to decrease the total machining time is by reducing the airtime. Therefore, in this study, an Artificial Intelligence (AI) method has been implemented in order to optimize the airtime machining which is Ant Colony Optimization (ACO). ACO has been used to minimize the machining airtime to increase the efficiency of machining process. A three-dimensional model consists of drilling process and pocket milling process has been developed using Solidwork software. MATLAB software has been used to generate the optimized toolpath and the data will be transferred to MasterCAM software in order to run the machining simulation. Then, the results of machining time that use toolpath generated by ACO method is compared with the machining time that use toolpaths generated by conventional methods. It can be concluded that in this study, the ACO method is on average, by 83% better than the conventional methods in reducing the machining time. It can be concluded that ACO is capable to reduce airtime machining and enhance the performance of machining process




How to Cite

Law Boon Hui, C., & Abdullah, H. (2022). Minimization of Airtime in Machining Process Using Non-Conventional Method. Research Progress in Mechanical and Manufacturing Engineering, 2(2), 72–78. Retrieved from