Assessment of Noise Levels in Working with Welding and CNC Milling Machines in Mechanical Workshops of an Academic Institute
1Civil Engineering, National Institute of Technology Kurukshetra, India
*Author to whom correspondence should be addressed:
E-mail: surinder.deswal.example@university.edu (SD)
E-mail: surinder.deswal.example@university.edu (SD)
Received: February 08, 2024 | Revised: February 21, 2025 | Accepted: April 01, 2025 | Published: June 2025
Abstract
Occupational noise is one of the most hazardous factors in a working environment, including mechanical workshops equipped with industrial robots, CNC machines, etc. under computer numerical control systems that are now indispensable in a modern technological environment. This necessitates noise assessment of such workshops under-industrial setup in academic institutes as well. In the present study of Robotics Lab and CNC Lab, the equivalent continuous noise level (L_Aeq) exceeded the permissible limit of 75 dB at some locations/areas, including the operator location at Mig Welding (79.62 dB, 6.16 % higher), and in Common area (75.37 dB, 0.49 % higher) during the parallel operations of all the three welding machines; whereas, L_Aeq values were within permissible level in CNC Lab in working areas. However, the maximum (L_Amax) and peak (L_Apeak) noise levels were above 85 dB in the production and non-production sections of both the labs and have the potential to cause hearing loss to the workers. The representative spatial noise maps of both Labs were also created using interpolation tools by using ArcGIS 10.7.1 software by adopting the Inverse Distance Weighting (IDW) technique to draw spatial distribution diagrams of noise levels, so as to reveal the noise hotspots in the Labs. The observed noise levels in the present study are lower than the similar reported studies possibly due to the adoption of less noisy super-automatic machines. However, the noise hotspots necessitate the suggested implications-specific preventive and corrective measures that include incorporating/adopting Kaizen techniques, noise masking, white noise machines, avoiding parallel operation of machines, hearing protectors, and double-glazed windows to reduce noise transmission to adjoining academic area.
Keywords
ArcGIS ; Inverse Distance Weighting ; noise assessment ; robotics lab ; CNC lab ; equivalent continuous noise levels ; noise maps
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