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How to Mitigate Fatigue in Heavy Industry - Fatigue Science Webinar | May 2019
- 1. Managing On-Duty Fatigue: A Scientific Approach Using New Technology and Validated Science to Reduce Fatigue Risk in Heavy Industry Robert Higdon Director of Product & Corporate Development Fatigue Science
- 2. Institutional Use & Validation Industrial Workforces Military & Elite Sports Since 2006, we’ve helped leading firms in heavy industry and elite sports measure, manage and reduce the risks of fatigue.
- 3. "Nobody is ever fully awake; I was always in a bit of a daze and that is because the way the shifts work doesn't allow the drivers to get a regular sleep pattern.” - Unnamed Former Tram Driver Croydon Tram Derailment, 9 November 2016
- 4. Awareness of fatigue is finally growing. up to 40% of commercial trucking accidents NTSB Up to 65% of surface mining haul truck accidents Caterpillar Global Mining, 2011 The single greatest cause of accidents across a wide range of high-risk industries: “Fatigue has been identified as the leading accident risk in the construction industry.” School of Civil Engineering, University of Sydney, 2010 Exxon Valdez Oil Tanker March 1989 Chernobyl Nuclear Power Plant April 1986 BP Texas City Refinery March 2005
- 6. Fatigue is a physiological condition that we all face when confronted with a lack of sleep or wakefulness outside of normal daylight hours.
- 7. US Department ofTransportation,Analysis of the Relationship between Operator Effectiveness Measures and Economic Impacts of RailAccidents, May 2011 Fatigue Models for Applied Research inWarfighting, Hursh SR, et al.,Aviat Space Environ Med 2004 Fatigue hinders the brain’s ability to interact with the body. Physiologically, it has similar effects to alcohol impairment.
- 8. EMOTIONAL Increased irritability Mood fluctuations Increased anxiety Depressed mood Increased frustration Bouts of Anger Increased impulsivity Increased stimulant use Alcohol use / misuse COGNITIVE Reduced concentration Reduced communication Reduced attention Reduced multitasking Reduced recall of events Decreased memory Reduced socialization Reduced creativity Reduced decision-making Reduced performance PHYSICAL Loss of reaction time Metabolic abnormalities Bodily sensations of pain or cold Risk of cardiovascular disease Risk of cancer Microsleeps Weight gain Risk of diabetes Reduced immunity Fatigue’s wide range of effects:
- 9. The facts are unequivocally clear. Worker fatigue materially impacts: HEALTH. SAFETY. PRODUCTIVITY.
- 10. SAFTE™ Alertness Model Exclusive to Fatigue Science YEARS OF RESEARCH AND DEVELOPMENT 25 ESTIMATED DEVELOPMENT COST $37M The US Army Research Lab spent over 25 years researching how sleep influences human fatigue.
- 11. The time of day Your sleep quantity Here’s what factors influence your fatigue, according to the US Army’s research: The timing & consistency of your sleep Your sleep quality
- 12. a) Last night b) 1 – 2 nights ago c) Over 1 week ago d) Over 1 month ago From how long ago can poor sleep affect the fatigue levels you experience today?
- 13. The US Army research found that sleep’s effects are cumulative. • It’s not just about last night’s sleep. • Your whole past week of sleep influences your fatigue. • Sleep debt is a real thing, and it can build up over time. SLEEP Tues Mon Sun Sat Fri Thurs Weds
- 14. 11:00 pm 7:00 am QUANTITY QUALITY CONSISTENCY Ideally 7+ hours / night Ideally 95%+ efficiency Ideally < 30 minutes of variance For many, it’s rare to get consistently ideal sleep. SLEEP Tues Mon Sun Sat Fri Thurs Weds
- 15. Here’s a more typical example of what sleep looks like for many industrial workers. x InadequateAmount of Time in Bed x High Variability in Bedtimes & WakeTimes x SignificantTime Lost to Awakenings Tues Mon Sun Sat Fri Thurs Weds
- 16. Using US Army research, it’s possible to analyze one’s past week of sleep data, and predict one’s fatigue levels for the day ahead.
- 17. Fatigue prediction, powered by US Army Research MORE ALERT Quickest Reaction Time Best Mental Performance Less Likely Microsleeps 100 90 80 70 60 Slower Reaction Time Lower Mental Performance More Likely Microsleeps Sleep Data Fatigue Prediction SAFTE™ Alertness Model
- 18. LESS FATIGUE SAFER OPERATION Lapse Index Reaction Time 1.5x+11% 3.7x+30% 5.2x+43% 8.0x+67% 100 90 80 70 60 0.08 BAC Equiv. 1.0x+0% SAFTEAlertnessScale Exclusive to Fatigue Science SAFTE™ Alertness Model: Predicting fatigue in terms of its objective impacts on safety. The SAFTE Model has been validated and relied on in studies by:
- 19. Alertness Score vs. Incident Likelihood (SAFTE Model Study in Railroad Industry, US Dept. of Transportation) SAFTE Alertness Score US Department of Transportation, Validation and Calibration of a Fatigue Assessment Tool, for Railroad Work Schedules, Summary Report, October 2006 Studies confirm a direct relationship between one’s SAFTE Alertness Score and their incident likelihood. SAFTE Alertness Score Alertness Score vs. Avg. Incident Cost (SAFTE Model Study in Railroad Industry, US Dept. of Transportation)
- 20. 0.43 0.24 0.14 0.10 0.04 0.05 y = 0.6196e-0.471x R² = 0.9362 SAFTE Alertness Score vs. Instances of Excessive Speed (average # of instances > 105 km/h per drive-hour in given SAFTE Score range) Similarly, a study showed fatigued drivers to be 9x more likely to excessively speed and 4x more likely to brake harshly. N = 5,462 drive-hours analyzed from 12 drivers; Fall 2016; Conducted by Fatigue Science using client telematics data with permission < 100< 90< 80< 70< 60< 50 SAFTE Alertness Score 0.19 0.11 0.09 0.08 0.05 0.05 y = 0.2142e-0.267x R² = 0.9419 0 - 49 50 - 59 60 - 69 70 - 79 80 - 89 90 - 100 SAFTE Alertness Score vs. Harsh Braking Incidents (average # of harsh braking incidents per drive-hour in given SAFTE Score range) < 100< 90< 80< 70< 60< 50 SAFTE Alertness Score
- 21. Sample Data
- 22. HourlyAlertness 100 90 80 70 60 SHIFT START SHIFT ENDLow fatigue risk during work hours A decent sleeper’s Alertness Scores will generally fluctuate in the 80s or 90s during Day Shift hours, before dipping at night.
- 23. a) Nearly impossible b) Possible but unlikely c) Somewhat likely d) Very likely Assuming you are a consistently good sleeper, how likely are you to dip below 70 when working an overnight shift? 100 90 80 70 60 0.08 BAC Equivalent SAFTEAlertnessScale
- 24. On Night Shifts, it’s normal for anyone–even a good sleeper–to fall below 70 after midnight, due to the body’s circadian rhythm. High fatigue risk around 1:00am HourlyAlertness 100 90 80 70 60 SHIFT START SHIFT END 12am
- 26. SAFTE Alertness Curve Individual Fatigue Risk Profile Worker 005 Percent ofTime On Duty, by Alertness Level By capturing data in a fatigue study, it’s possible to generate an anonymized Fatigue Risk Profile for each individual. Night Shift Worker 005 < 60 < 70 < 80 < 90 < 100 SAFTE Alertness Score
- 27. Organizational Fatigue Risk Profile Site XYZ at Company ABC Percent ofTime On DutyIndividual Fatigue Risk Profiles With a sufficient sample size, individual risk profiles can be combined to form a benchmark for organizational fatigue risk. < 60 < 70 < 80 < 90 < 100 SAFTE Alertness Score 20%
- 28. Organizations will set targets for fatigue risk exposure as a percentage of duty hours spent in each Alertness Score range. Day Shift Night Shift < 60 < 70 < 80 < 90 < 100 SAFTE Alertness Score Example shown. Actual targets vary according to time of day, operational design, and many other factors.
- 30. 1st Wave Science-Based Scheduling Scheduling 2nd Wave Reactive Detection & Data Collection 3rd Wave Predictive Guidance Birth of trucking industry, and first fatigue- related collisions Awareness of fatigue grows with dawn of circadian rhythm-based fatigue research The science of quantifying & predicting fatigue arrives, led by SAFTE™ Alertness Model First mainstream consumer sleep trackers arrive Mobile tech enables personal fatigue predictions Evolution of Fatigue Risk Management Reactive fatigue detection tech arrives, detecting “nodding off” 1930’s ICC implements its first Hours of Service (HOS) Regulation 1938 1970’s 1990’s 2000 2009 2016 First devices to pair sleep data with fatigue modelling, enabling quantification of personal fatigue 2012 Personal fatigue predictions tech becomes smarter, alerting to risks in context of work hours, and guiding risk reduction 2019 Fleets begin using the science of fatigue to optimize schedules
- 31. Readiband is a tool designed to help workers and organizations measure, manage manage and reduce the risks of fatigue. ™
- 32. Built for Heavy Industry Splashproof and durable Validated 92%+ accuracy sleep detection Doesn’t track location Tracks only wrist motion, not heart rate 30+ day battery life
- 34. Fatigue Awareness ReadibandApp 3.0 provides predictive fatigue alerts to workers in the context of their shift hours, enabling advance visibility into personal fatigue levels before beginning their day on duty.
- 35. ReadibandApp 3.0 also empowers users to predict the impact of a personalized sleep plan on their fatigue for the week ahead, enabling them to set targets for personal fatigue risk reduction. Sleep Improvement
- 36. Tools for Management Aggregated fatigue insights that protect worker privacy View workforce fatigue levels, trends,& comparisons across sites and groups Track utilization of investment, while preserving privacy of sleep & fatigue data
Editor's Notes
- This policy of constantly pretending like there is no biology to sleep/wake that matters for waking function is staggeringly disastrous. It is the leading cause of catastrophic outcome.
- http://www.mainlandmachinery.com/fatigue-studied-readiband/
- This week, almost ~XYZ American miners will cause a fatigue-related accident after passing a safety check-in with fatigue undetected. For a mining company of 10,000 workers, solving this problem represents a $XXM opportunity to prevent XX accidents per year.
- This week, almost ~XYZ American miners will cause a fatigue-related accident after passing a safety check-in with fatigue undetected. For a mining company of 10,000 workers, solving this problem represents a $XXM opportunity to prevent XX accidents per year.
- This week, almost ~XYZ American miners will cause a fatigue-related accident after passing a safety check-in with fatigue undetected. For a mining company of 10,000 workers, solving this problem represents a $XXM opportunity to prevent XX accidents per year.
- No aspect of our biology is left unscathed by sleep deprivation. It sinks down into every possible nook and cranny. Russell Foster is Professor of Circadian Neuroscience, Oxford University > Sleep & Circadian Rhythm Disruption in Social Jet Lag and Mental Illness
- There are factors within individuals’ control, that can mitigate sleep loss and circadian disruption - and when feedback is actionable and accessible, we can influence real positive change - and improve safety outcomes.
- Sleep is only half the equation. It’s not enough to know how much, or how well I slept last night. In order to enact real change, I need clear understanding of how my sleep but acutely and chronically affects my fatigue and performance. The SAFTE Alertness Model, is...
- http://www.mainlandmachinery.com/fatigue-studied-readiband/
- This week, almost ~XYZ American miners will cause a fatigue-related accident after passing a safety check-in with fatigue undetected. For a mining company of 10,000 workers, solving this problem represents a $XXM opportunity to prevent XX accidents per year.
- This week, almost ~XYZ American miners will cause a fatigue-related accident after passing a safety check-in with fatigue undetected. For a mining company of 10,000 workers, solving this problem represents a $XXM opportunity to prevent XX accidents per year.
- There are factors within individuals’ control, that can mitigate sleep loss and circadian disruption - and when feedback is actionable and accessible, we can influence real positive change - and improve safety outcomes.
- There are factors within individuals’ control, that can mitigate sleep loss and circadian disruption - and when feedback is actionable and accessible, we can influence real positive change - and improve safety outcomes.
- http://www.mainlandmachinery.com/fatigue-studied-readiband/
- http://www.mainlandmachinery.com/fatigue-studied-readiband/
- http://www.mainlandmachinery.com/fatigue-studied-readiband/