According to OSHA, on-the-job injuries cost U.S. employers an estimated $50 billion per year. In addition, it has been said that for U.S. warfighters, the primary cause of lost days is due to accidents and musculoskeletal injuries involving equipment use.
The tools currently used to assess risk of injury for manual material handling can be off by as much as 16 pounds. When these tools underestimate task risk, workers can be exposed to a significant increase in risk of injury. When task risk is overestimated, tasks are expensively redesigned. Both of these scenarios significantly affect your company’s bottom line.
To truly put safety first, we must design with a variety of users in mind, and we must test products and processes virtually before real injuries occur. SantosHuman provides virtual human modeling software that predicts the physical behavior and performance of women and men performing tasks while considering physical human limitations. Santos technologies were designed specifically to help the military and private industries identify opportunities to minimize exposure to risk of injury at the earliest stages of design. This allows designers to correct before building the first prototype. Plus, it makes products and equipment use safer and more ergonomically correct, which significantly benefits everyone’s bottom line.
Santos technologies now include the Arm Force Field method (AFF). AFF is the most accurate and extensively validated method of predicting exposure to risk of injury available today. Tightly integrated within our predictive model and coupled with a duty cycle calculator for realistic task assessments, the Santos AFF Plug-In provides a degree of autonomy to task assessment that does not exist in any other digital human model. This autonomy not only makes Santos virtual human-in-the-loop solutions easier to use, it makes them easier to use correctly. You can now accurately predict the risk of injury for a variety of users long before users are exposed to task risk.
Safety White Paper: Predicting Exposure to Risk of Injury