Working in a technology company (and being an engineer) I always enjoy the opportunity to visit a “real” manufacturing plant. I still vividly remember my first visit to an integrated steel mill in the 90s.
The plastic sole of my shoe suddenly went wobbly as it melted while I was watching the tapping at a blast furnace from too close. Steel mills, mines or quarries are a dangerous place for unwary visitors.
Smart'n'Save with Wearables in Mining
Vandrico Solutions, in collaboration with the SAP Co-Innovation Lab and Illumiti, announced the launch of the MineSafe Smartwatch already in 2015. (Find more information on the co-innovation approach in this interview with Vandrico's CEO Gonzalo Tudela and Illumiti's Lorraine Howell, vice president of research and development, linked here)
According to Vandrico, the MineSafe Smartwatch is a tool to help miners identify and respond to potentially dangerous issues. The watch enables real-time communication between miners underground and personnel on the surface, and include features like:
Worker location tracking
Real-time incident reporting
Proactive real-time communications
Mine workers can use a one-touch distress signal to send an urgent notice to the surface for immediate, coordinated response.
Safety Process Automation at OMK
OMK (Объединенная металлургическая компания) is a leading international producers of steel products including large diameter pipes, railway wheels and automotive springs based in Moscow. OMK simplified and automated the process of identifying, documenting and reducing labor safety rule violations using SAP's Environment, Health and Safety solution.
Employees are able to quickly capture risks, and OMK's health & safety department can identify risk hot spots much faster, and take needed preventive measures.
In the first 6 months approximately 300 000 violations were logged, investigated and eliminated. OMK reduced their injuries already by 10% since the project runs, and expects by 2021 to achieve a 30% reduction.
From a change management perspective alone, I consider this is a significant achievement, and is only sustainable when capturing incidents is simple and straightforward for the worker, and counter-measures are taken timely.
Besides the health & safety benefits, OMK expects to save 1.5m RUB in staff time & cost in the next 5 years through more accurate and automated reports.
NLMK pilots 3D employee positioning system & wearable live-monitoring system
NLMK has developed a pilot for a 3D-positioning system for shop-floor employees in their continuous hot dip galvanizing mill at NLMK's Lipetsk site. From a risk point of view, the galvanizing line is their mot difficult equipment - including hazardous chemicals, hot metals, height and galleries.
The positioning system tracks in real-time the employee's location, and the asset and machine condition. The workers carry a wearable sensor tag that tracks locations, unusual behaviour, immobility, falls, aprupt changes in body position.
The sensor tag also allows a bidirectional communication: the worker can call for help via a button on the tag. The sensor can vibrate to alert all workers in a dangerous zone.
Each worker has dedicated save zones where it is save to move. If he moves outside the allowed zone, an alert is triggered as well.
The tracking information is collected in a database and later analyzed to enhance Operational Health and Safety (OHS), Human Resource and contractor management practices. The system will notify about OHS risks and eliminate them in advance. At the moment, the system is being prepared for full-scale industrial operations.
The NLMK-solution is built on the SAP Cloud Platform, utilizes RTLS-UWB for positioning, incorporates 3D-imaging and LoRaWan wireless communication technology.
A common problem for IoT in the steel industry are the harsh conditions including high temperatures and strong vibrations - making it often near impossible to work with normal sensor solutions. Some companies decided to instead analyse photos and videos e.g. close to the furnace (but even those may need to be watercooled to survive). Machine learning and specifically image classification can be used to identify normal vs. hazardous situations, like people in the wrong place, or machines no longer working properly.
NLMK's strategic motivation behind this is clear: They want to be "a trendsetter, not a follower", says Kirill Sukowykh, NLMK's head of the SAP-Co-Innovation Lab. They expect to jointly develop breakthrough solutions to bring steel production technology and business processes to a qualitatively new level.
They do this through combining newest digital technology, design thinking and agile methodology, and NLMK deep functional domain expertise. The employee tracking pilot was developed in just 2 months.
The tracking solution is one of the first projects of the NLMK-SAP innovation lab, and was built jointly with the National Centre of Internet of Things (NCIT).