Site Safety Analytics

Challenge & Selection

One of our manufacturing sites is considered as the most dangerous work place. There are thousands of  risk events every year caused by accidents knowingly or unknowingly. These accidents not only cause  severe health/safety issues but also lead to huge financial loss.

Our team grouped together with the operations team to analyze the problem and realized that quality  data was being captured for the above risk events. We then decided to use the Learning Launch tool to  tackle this problem and prevent the occurrence of similar accidents and promote workplace safety as per  below assessment:

a. Analysis of historical accidents is crucial. Based on the results of root cause analysis, proper

actions can be taken by safety professionals and management to eliminate or lessen the identified  causes.

b. It is also noted that one major factor contributing to the risk of an accident is the presence of

destructive items such as distorted & damaged equipment, sharp articles nearby. Mitigating  strategies can be made accordingly after identification of such matters.

Application

To come up with a prototype application, we started analyzing the problem from two perspectives: one  from management’s policies and other one was technology driven. We have presented our ideas and got  acceptance by Leadership for further action.     Dedicated web portal was designed to enhance the safety management processes such as safety  education and interactive training focusing on individual/organizational characteristics such as workers’  attitudes towards safety to increase their awareness.    This portal was even integrated with visualization based on large number of disaster study reports  generated after a fatal accident providing a complete description of the accident in the form of  unstructured text data that were manually analyzed to classify the causes with an objective to find hidden  patterns and present the trends that emerge from the data.     Insight & Approach

Our application had helped the sites to understand the causal factors of the risk events with intuitive  visualization which clearly illustrated that the accidents are considered an outcome of interaction among  physical conditions of the work site, environmental factors, administrative issues and human error.  Feedback received was that the effect of this strategy for preventing injuries was limited due to their  reactive nature.

We would like to move towards the AI based risk model that emphasizes more on automatic classification  of incidents from a massive number of reports into different cause categories which will help in better  understanding of reports, predict and prevent the occurrence of site accidents.


Site Safety Analytics Challenge & Selection One of our manufacturing sites is considered as the most dangerous work place . There are thousands of risk events every year caused by accidents knowingly or unknowingly . These accidents not only cause severe health / safety issues but also lead to huge financial loss . Our team grouped together with the operations team to analyze the problem and realized that quality data was being captured for the above risk events . We then decided to use the Learning Launch tool to tackle this problem and prevent the occurrence of similar accidents and promote workplace safety as per below assessment : a. Analysis of historical accidents is crucial . Based on the results of root cause analysis , proper actions can be taken by safety professionals and management to eliminate or lessen the identified causes . b. It is also noted that one major factor contributing to the risk of an accident is the presence of destructive items such as distorted & damaged equipment , sharp articles nearby . Mitigating strategies can be made accordingly after identification of such matters . Application To come up with a prototype application , we started analyzing the problem from two perspectives : one from management ’s policies and other one was technology driven . We have presented our ideas and got acceptance by Leadership for further action . Dedicated web portal was designed to enhance the safety management processes such as safety education and interactive training focusing on individual / organizational characteristics such as workers ’ attitudes towards safety to increase their awareness . This portal was even integrated with visualization based on large number of disaster study reports generated after a fatal accident providing a complete description of the accident in the form of unstructured text data that were manually analyzed to classify the causes with an objective to find hidden patterns and present the trends that emerge from the data . Insight & Approach Our application had helped the sites to understand the causal factors of the risk events with intuitive visualization which clearly illustrated that the accidents are considered an outcome of interaction among physical conditions of the work site , environmental factors , administrative issues and human error . Feedback received was that the effect of this strategy for preventing injuries was limited due to their reactive nature . We would like to move towards the AI based risk model that emphasizes more on automatic classification of incidents from a massive number of reports into different cause categories which will help in better understanding of reports , predict and prevent the occurrence of site accidents .