Register for the webinar here

From EHS Today:

Industrial workplaces remain one of the most high-risk work environments as they routinely require their employees to work with various equipment and dynamic conditions.  The ability to predict serious injury and fatality (SIF) risks before an incident occurs is essential to create a robust safety management system that effectively prevents such incidents.

Motivated by this perspective, contemporary safety research now explores ways to accurately forecast future SIF risks and help professionals intervene in a timely manner. To do so, safety researchers take advantage of the significant developments in computing techniques and processing power using tools like machine learning. In this presentation, Dr. Erkal talks about the art of making predictions in the safety domain, different safety performance metrics, and demonstrates a predictive model that could differentiate SIF exposure from safety success given business, project and team attributes of a workplace setting. Join us for these key takeaways:

• Learn how to forecast future SIF conditions to mitigate risks
• Apply predictive analytics methods in safety
• Use various safety performance metrics to evaluate and optimize your safety programs
• Discover a predictive model that could separate SIF exposure from safety success

Register here.