https://www.fatiguescience.com/wp-content/uploads/2021/02/PR_Thumbnail_Interventions.png 965 1192 Fatigue Science http://www.fatiguescience.com/wp-content/uploads/2019/11/readi-logo-nav.svg Fatigue Science2021-02-17 14:53:562021-02-22 13:10:22Press Release: Fatigue Science announces Fatigue Intervention Tracking, game-changing workflow advancement for fatigue management
Fatigue Science, the global leader in providing human fatigue and performance predictive analytics and fatigue management information systems to heavy industry, military, and elite sports teams, is pleased to announce the launch of Fatigue Intervention Tracking as part of its Readi fatigue management platform.
https://www.fatiguescience.com/wp-content/uploads/2020/09/New-Blog-Graphic-3.png 497 1312 Fatigue Science http://www.fatiguescience.com/wp-content/uploads/2019/11/readi-logo-nav.svg Fatigue Science2020-09-28 06:00:342021-02-08 16:25:09Fatigue Science announces release of 14-Day Fatigue Forecasting, enabling workforce planning 14 days in advance
Readi Enterprise Suite, the Fatigue Management Information System from Fatigue Science, is widely relied upon for its ability to provide objective historical and real-time visibility into workforce fatigue. Now, the release of 14-Day Fatigue Forecasting expands this visibility into the future, providing the world’s first “360º view of fatigue – past, present, and future.” With this advancement, proactive planning measures and proactive safety-critical actions that were previously impossible are now visible and achievable.
https://www.fatiguescience.com/wp-content/uploads/2020/05/ReadiAnalytics-Heavy-Industry.png 4203 6279 Fatigue Science http://www.fatiguescience.com/wp-content/uploads/2019/11/readi-logo-nav.svg Fatigue Science2020-05-27 12:14:012021-02-08 16:33:27Introducing ReadiAnalytics: real-time objective visibility into workforce fatigue
Unlike subjective methods for estimating crew fatigue, ReadiAnalytics captures anonymous sleep data from a sample of crew workers and then processes it alongside a variety of circadian factors with a scientifically-validated biomathematical model. The model then quantifies which on-duty crews will be the most and least fatigued, and how that fatigue will trend over time as their shift pattern progresses. Crucially, worker privacy is preserved, as insights are anonymized and aggregated for each crew, site, and the company.