• Journal of the Korean Society of Safety
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• v.31 no.3
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• pp.109-115
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• 2016

This study examined the effects of safety-aisle on the safety climate, safety leadership, safety behavior, work loading and perceived accident risk in the small sawmilling industry. We distributed a questionnaire that measured various demographic variables, safety related variables by mail to 200 sawmilling companies. Finally 59 managers' and 129 workers' questionnaires were used for data analysis. An independent t-test was conducted to identify significant mean differences of safety related variables between safety-aisle installed and non-installed companies. Results indicated that mean differences of safety climate and safety behavior between safety-aisle installed and non-installed companies were significant. However, mean differences of safety leadership, work loading and perceived risk were not significant at the p < .05 level. Based on these results, the implications of this study and suggestions for future research were discussed.

• Journal of the Korea Safety Management & Science
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• v.16 no.3
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• pp.45-54
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• 2014

The average injury rate in sawmilling industry for the last 5 years is 4.99%, which means that more than 200 injuries have occurred in that industry every year. Because the first step in risk assessment is the hazard identification, it is very important to know how to define the hazard and nature of harm. We analyzed 643 accident records of three years(2010-2012) and carried out site survey for the same cases. As a result, the most common types of work at the time of injury in sawmilling industry were removing jammed wood 81(12.8%), wood carrying task 52(8.1%), wood cutting 49(7.6%), travelling table log band saw 41(6.4%), maintenance 37(5.8%) etc. In addition, there were statistically significant differences in some analysis factors such as injured body parts, employment size, and handling material among different working places. Therefore, it is concluded that differentiated prevention efforts are necessary in each workplace.

• Journal of the Korea Safety Management & Science
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• v.17 no.4
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• pp.105-112
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• 2015

Sawmilling industry remained a high risk with the average 4.73% of industrial accidents in 2010-2012 that was eight times that of general manufacturing. Sawmilling industry had 200 industrial accidents victim in average. Manufacturing process in sawmill industry contained dangerous machinery such as conveyors, roller, saw ( band saw, circular saw) etc. It may be effective to figure out the type of industrial accidents occurred in the past and extend risk assessment which can predict hazard such as near miss when implementing exposure or potential dangers in sawmill industry. This study conducted research on the actual condition on the place of industrial accident occurrence, detailed work and contact object when injured, and injured part targeting 643 businesses which had industrial accidents in 2010-2012. As the results, RPN of general sawmill industry was the highest 'ganglip saw' with 36,157. RPN of the following order were 'moving truck' with 25,454, 'special machining operations' with 22,283. Also, probability of general sawmill industry was a lots within 1 year, while risk appeared a lots within 5 years. So, risk assessment shall be needed to emphasis on accident prevention of sawmill industry. And additional work will be needed on the risk assessment in hazard prevention work of supervisors.

• Safety and Health at Work
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• v.15 no.3
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• pp.310-316
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• 2024

Background: The wood-processing industry has historically exhibited high rates of occupational hazards resulting in illness and injury. One of the major causes of high injury rates is small firm size, as resource constraints generally preclude hiring safety officers. This study examined the effect of a safety leadership training program that included coaching for managers on workers' safety behaviors and safety climate in three wood-processing companies. Methods: One or two managers at each site participated in this study. The manager training consisted of safety leadership education, safety observation, positive or corrective feedback on workers' behaviors, goal setting, and low-cost rewards for meeting goals. The dependent variable was the percentage of safe employee behaviors recorded on a critical behavior checklist developed for this study. Safety climate was measured before and after the intervention. An AB multiple baseline design across settings was adopted. After the baseline (A), the training program (B) was introduced to each site at different points in time. Results: After the introduction of safety leadership training, the mean rate of safety compliance increased by 15.3%, from 80.38% to 95.68%, and safety climate scores increased significantly from an average of 3.2 to 3.47. Conclusion: These results suggest that safety leadership coaching can be effective in improving safety management in small sawmilling sites. Implications, limitations, and possible future research directions are discussed.