Optimising machining parameters to minimize occupational noise exposure

Abstract

Need - Metal removal processes are generally optimised to maximise productivity, not minimise noise which is an occupational health risk. There is a need to represent noise in production simulations and minimise it. Approach - This is addressed by developing a systems dynamics model was developed for machining, including a regression equation for noise, which may be optimised. The benefit of using a regression approach is that it allows a quantification of the complex dependency between noise and process parameters. The benefit of constructing a simulation model is that it provides the tools to optimise noise exposure: i.e. change machine process parameters to reduce noise. This is challenging to do because generally cutting slower or making less deep cuts will reduce noise, but at the cost of worsening the productivity metrics. Results - For the optimised process parameters, the predicted daily equivalent noise dose was 0.72 dBA, compared to 5.73 dBA for the unoptimised processes. Results show the feasibility of the method, and the ability to reduce noise exposure while not adversely affecting production time. Contribution – A  joint optimisation process parameters to maximise productivity and minimise noise has otherwise not been shown in the literature. The overall here is piloting a practical methodology for the reduction of noise in a manufacturing environment. This can then be included in a simulation, to calculate occupational noise exposure dose for the multiple machining tasks that make up a realistic production sequence. The model simultaneously optimises both noise and productivity.