Forklift Telematics Improves Safety – If You Can Get to the Point

Predicting forklift injuries is a goal of every safety professional. The publication DC Velocity recently wrote an article on machine learning and how it predicts truck accidents. The focus of the article was on a truck driver’s probability of getting into an accident due to fatigue. The data is predicting the outcome even before the truck driver gets in the vehicle. Can similar be true with the data captured with a forklift safety system? Let’s take a look.

What is Predicting Forklift Injuries?

Predicting forklift injuries is having an educated guess of when a forklift accident is to occur. We at least have a place to start. According to the NSC, there were 7,290 injuries that occurred in 2020. In addition, their ‘injury demographics show that 12.2% of nonfatal injuries occurred to females in 2020, while 5.7% of fatalities were females in 2021. The number of nonfatal injuries in 2020 peaked among 35- to 44-year-old workers, while in 2021 fatal injuries peaked among 55- to 64-year-old workers.’ This is what safety professionals are trying to combat.

How Can It Be Solved?

Data. Predicting forklift injuries is all about collecting and analyzing the data for it to be interpreted for safety strategies and planning. By having the data automatically collected with technology, you no longer need to rely on people to give you some pertinent information for your material handling vehicles. The data is collected via the forklift safety system, interpreted and placed into the online telemetry Dashboard. Here, the data can be analyzed. What can you find out?

Telemetry Dashboard

The data that is collected on the lift trucks are automatically stored on the telemetry Dashboard in real-time. You can watch the information come in when you sit at your desk. The information is placed in numerous ‘buckets’ such as inspections: pass or fail, low, medium and high impacts, and near misses to name a few critical areas. In the near miss category, you will automatically know how many near misses are for pedestrians and objects. This calculation is critical as you can predict the cost of damages to the facility, product or even an injury.

In addition, use the GPS to know ‘where’ the near misses are occurring. By analyzing this data, you will know the area(s) at high risk. Now that you understand the where, go to that area to identify what needs to be changed and make the necessary adjustments. Now watch what happens in real time. Did you affect the number of near misses? Are the numbers going down? If not, what else can be altered to have a positive affect?

Don’t forget, you can also analyze which assets are involved in the near misses as well as the operator. Does a particular asset need repair or maintenance? Is the same operator on those assets or is it a separate issue? In addition, is there a pattern with the forklift operator(s). Do the operators need additional training or tailored training. These are some examples of collecting the data, analyzing the situation and making adjustments for a different result.  

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