Abstract: Noise has adverse effect on human health and
comfort. Noise not only cause hearing impairment, but it also acts as
a causal factor for stress and raising systolic pressure. Additionally it
can be a causal factor in work accidents, both by marking hazards
and warning signals and by impeding concentration. Industry
workers also suffer psychological and physical stress as well as
hearing loss due to industrial noise. This paper proposes an approach
to enable engineers to point out quantitatively the noisiest source for
modification, while multiple machines are operating simultaneously.
The model with the point source and spherical radiation in a free field
was adopted to formulate the problem. The procedure works very
well in ideal cases (point source and free field). However, most of the
industrial noise problems are complicated by the fact that the noise is
confined in a room. Reflections from the walls, floor, ceiling, and
equipment in a room create a reverberant sound field that alters the
sound wave characteristics from those for the free field. So the model
was validated for relatively low absorption room at NIT Kurukshetra
Central Workshop. The results of validation pointed out that the
estimated sound power of noise sources under simultaneous
conditions were on lower side, within the error limits 3.56 - 6.35 %.
Thus suggesting the use of this methodology for practical
implementation in industry. To demonstrate the application of the
above analytical procedure for estimating the sound power of noise
sources under simultaneous operating conditions, a manufacturing
facility (Railway Workshop at Yamunanagar, India) having five
sound sources (machines) on its workshop floor is considered in this
study. The findings of the case study had identified the two most
effective candidates (noise sources) for noise control in the Railway
Workshop Yamunanagar, India. The study suggests that the
modification in the design and/or replacement of these two identified
noisiest sources (machine) would be necessary so as to achieve an
effective reduction in noise levels. Further, the estimated data allows
engineers to better understand the noise situations of the workplace
and to revise the map when changes occur in noise level due to a
workplace re-layout.