Abstract: The objective of this study is to determine the thermal comfort among worker at Malaysian automotive industry. One critical manual assembly workstation had been chosen as a subject for the study. The human subjects for the study constitute operators at Body Assembly Station of the factory. The environment examined was the Relative Humidity (%), Airflow (m/s), Air Temperature (°C) and Radiant Temperature (°C) of the surrounding workstation area. The environmental factors were measured using Babuc apparatus, which is capable to measure simultaneously those mentioned environmental factors. The time series data of fluctuating level of factors were plotted to identify the significant changes of factors. Then thermal comfort of the workers were assessed by using ISO Standard 7730 Thermal sensation scale by using Predicted Mean Vote (PMV). Further Predicted percentage dissatisfied (PPD) is used to estimate the thermal comfort satisfaction of the occupant. Finally the PPD versus PMV were plotted to present the thermal comfort scenario of workers involved in related workstation. The result of PMV at the related industry is between 1.8 and 2.3, where PPD at that building is between 60% to 84%. The survey result indicated that the temperature more influenced comfort to the occupants
Abstract: The environmental factors such as temperature and
relative humidity are very contribute to the effect of comfort, health,
performance and worker productivity. To ensure an ergonomics work
environment, it is possible to require a specific attention especially in
industries. The aim of this study is to show the effect of temperature
and relative humidity on worker productivity in automotive industry
by taking a workstation in an automotive plant as the location to
conduct the study. From the analysis of the data, there were
relationship between temperature and relative humidity on worker
productivity. Mathematical equation to represent the relationship
between temperatures and relative humidity on the production rate is
modelled. From the equation model, the production rate for the
workstation can be predicted base on the value of temperature and
relative humidity.