Effective Engineering Noise Control Strategies with the Stochastic Noise Mapping Simulation Method: A Case Study in Palm Oil Mill

Abstract

Excessive sound levels pose a substantial risk to the hearing health of industrial workers. This study introduces a stochastic noise mapping technique to propose effective engineering control methods for noise mitigation in the palm oil industry. A case study conducted in a Malaysian palm oil mill employed data to predict the noise mapping and assess personal noise exposure levels of workers. Results showed that 29.6% of the area fell within the high-risk zone, with 28.1% in the extremely high-risk zone. Personal noise monitoring revealed that many workers were exposed to excessive noise, with a maximum time-weighted average sound level of 99.2 dBA among the worker groups. Despite the provision of protective equipment by management, regular usage of hearing protectors during work shifts was lacking. To reduce noise levels, two engineering control methods were proposed: erecting noise barriers around high noise emission sources and limiting the maximum sound power to 110 dBA for dynamic noise sources. Implementing these controls resulted in a 10.9% decrease in the extremely high-risk zone and a 17.8% decrease in the high-risk zone. These findings hold significance as they can guide the implementation of noise monitoring practices and engineering noise control in the industry.