IoT and IIoT are just beginning to reveal demonstrable improvements to workplace safety and quality. Find out how wearables can reduce the risk of slips, trips, and falls.
Quality management systems (QMS) focus on understanding business and production activities used to create value and satisfy customer needs. Sometimes, these activities can be hazardous for the operators who perform them. Keeping workers safe is not only a moral responsibility of the organization, but a way to prevent unexpected downtime, problems that impact product quality, and lost productivity due to days off work.
Three of the most common workplace hazards can pack the most serious impacts. Slips happen when you lose balance and can’t get your footing. Trips happen when you lose your balance while encountering an unexpected object or obstruction. Falls are defined by OSHA as “anything that can cause you to lose your balance or make you unable to properly support your body to remain in a standing position.” Although any of these hazards can lead to injuries, falls are particularly insidious -- and remain the leading cause of death in the construction industry.
Fortunately, Industry 4.0 technologies present new opportunities to mitigate the risks by putting controls in place for prevention. Recently, Costin and partners (2019) developed a prototype to demonstrate how Internet of Things (IoT) sensors can provide early feedback to workers, helping them adjust their behavior in real-time to prevent injuries. Their goal was to identify and demonstrate how active leading indicators could make the workplace more safe, in particular, from equipment strikes, slips, trips, and falls from height, and overexertion.
Here’s what they found:
- By collecting biometric data about workers and their environments, they were able to figure out thresholds at which to alert the safety manager when potentially unsafe conditions emerged. Prior to the study, those thresholds were neither known nor monitored.
- When implementing wearables to reduce risk, organizations should specifically consider the feedback loop between the worker and the system -- although it can be powerful to leverage Big Data and Artificial Intelligence (AI) applications, interpretations of the data by the participants “bring the smartness to the system.”
- Understanding different safety incidents will require different inputs. For slips, trips, and falls, these researchers recommended monitoring the strength of connections and supports, sudden vector changes and shifts in body orientation, and proximity sensing.
Established methods won’t be replaced, however. IoT-based approaches will supplement traditional methods from lean manufacturing like 5S (used to clean and organize a workspace or facility) for hazard prevention. The real innovation is in being able to continuously monitor or sample worker habits, so that those habits can be leveraged as leading indicators to predict or anticipate dangerous situations and events.
Costin, A., Wehle, A., & Adibfar, A. (2019). Leading Indicators—A Conceptual IoT-Based Framework to Produce Active Leading Indicators for Construction Safety. Safety, 5(4), 86.
Danielsen, A., Olofsen, H., & Bremdal, B. A. (2016). Increasing fall risk awareness using wearables: a fall risk awareness protocol. Journal of Biomedical Informatics, 63, 184-194.
Valentic, S. (2018, August 10). 5 Tips to Prevent Slips, Trips and Falls [Infographic]. EHS Today. Available from https://www.ehstoday.com/safety/article/21919742/5-tips-to-prevent-slips-trips-and-falls-infographic
About the Author: Nicole M. Radziwill, PhD, MBA, is SVP, Quality & Strategy, at Ultranauts. She is a Fellow for the American Society for Quality (ASQ) , and editor for Software Quality Professional.