Optimisation of tool replacement time in the machining process based on tool condition monitoring using the stochastic approach

ABSTRACT

The efficient cutting tool replacement policy can decrease the machining costs and increase the productivity. This study focuses on the stochastic approach for tool life modelling in the milling process. In this study by considering the costs of tool condition monitoring methods a hybrid policy was developed based on the reliability function for optimising the tool replacement time. The proposed policy covers seven functional modes assuming discrete and continuous modes. The policy in this paper can provide the better solutions for determining the discrete and continuous time interval of the tool condition monitoring and also tool replacement time in the milling process. The proposed policy is defined in the non-convex space, thus this policy is optimised by a particle swarm optimisation (PSO) algorithm. The mentioned policy was applied in an experimental process using a CNC milling machine to assess its performance. Finally, the effect of different costs is demonstrated using the sensitivity analysis and the outcome of the optimised policies under various conditions are compared together. The results show that the proposed policy can optimise the tool replacement time due to its flexibility in covering the different functional modes efficiently.

KEYWORDS:

• Tool replacement
• machining process
• tool condition monitoring
• stochastic tool life
• evolutionary algorithms

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Amirkabir University of Technology [0]