Tag Archives: dust monitoring

Teck leverages Nanozen tech to improve occupational health at mine sites

As part of its work towards eliminating occupational disease, Teck has completed a pilot project using an innovative combination of on-the-ground data and video technology to help better understand potentially harmful dust exposures at a task level.

The Nanozen pilot project, completed in 2020, was devised to understand task level exposures so the company could “laser focus” critical control strategies to reduce employee exposures.

As the company says, occupational exposures that can give rise to occupational disease represent the single most significant health and safety risk in the mining industry globally.

The large-scale pilot project it carried out, which included its Greenhills, Fording River, and Highland Valley Copper Operations, was funded by Teck’s Ideas at Work program. The pilot program leveraged the power of advanced analytics to collect real-time exposure data for job roles including pit crews, mechanics and equipment operators.

Exposure to dust at mine sites is a potential health and safety hazard, leading to respiratory diseases if proper precautions are not taken, Teck says. For years it has been industry standard to rely on daily sampling methods, averaged over the length of a shift, to determine dust exposure. These sampling methods provide one value indicating an employee’s overall dust exposure for a shift.

By making use of Nanozen’s real-time monitoring technology, Teck says it has been able to greatly improve the collection of information about dust levels during a work shift. Instead of a single value for an entire shift, it can now monitor live, accurate information on the concentration of dust exposures.

An overview of the instruments and tools deployed for the Nanozen pilot project

“This has enabled us to better understand how and when these exposures occur, and to target controls that reduce exposures from higher-risk activities,” the company said.

In 2020, the Nanozen pilot project was initiated at sites to deploy this technology into a wide range of roles including field and shop mechanics, pit utility and cable crews, bulldozer and grinding operators, and laboratory workers involved in sample processing. Teck’s Occupational Health and Hygiene team leveraged advanced analytics, diving deep into the data to find meaningful results and actionable changes, it said. This increased volume of research data, the company says, has helped it pinpoint the specific activities and times where dust exposures occur and prioritise approaches to mitigate them.

Dan Sarkany, Lead, Occupational Hygiene at Teck Coal, said: “Applying analytics to real-time particulate monitoring helps us determine exactly which activities lead to high dust exposures, allowing us to recommend and implement targeted controls to improve employee health and safety.”

This pilot project coupled Nanozen real-time dust monitoring technology with on-site video recordings and video analysts trained to recognise job activities. The footage collected maintained confidentiality and privacy by blurring faces and skin tone, and no audio was recorded. Teck said it had the full support of its workforce to undertake this work.

Corrine Balcaen, Director, Occupational Health & Hygiene, said: “This project represents a leading health and safety initiative in the mining industry and other industries with dust exposures.”

Real-time dust monitoring, and the targeted controls developed as a result of the learnings, will continue to be implemented throughout its operations going forward, the company said.

“This technology serves a key role in improving exposure controls and working towards Teck’s goal of eliminating occupational disease,” it added.

In 2019, Teck employed Nanozen’s real-time dust monitoring technology at Greenhills as part of a study looking to gain detailed, real-time data on dust exposure levels throughout a typical haul truck driver shift.

This is an edited version of the story that first appeared on Teck’s website, here.

ennomotive challenges developers to supress the dust problem

Chile-based ennomotive recently launched an open innovation challenge to look for IoT solutions to monitor dust contamination in “extreme work environments” like mining.

During this process, 43 applications – including companies, scholars, freelancers, and employees from other companies – participated in the challenge. Six startups from France, India, Argentina, Chile, and Indonesia also proposed an adaptation of their technologies.

As ennomotive explained, there are already some devices in the market specifically designed to monitor air quality in urban settings, but they only measure low level dust concentrations. “The sensors in these devices are not robust enough to operate under extreme industrial conditions since they get dirty very easily, collapse, stop measuring, and need constant maintenance.

“Extreme work environments need easy-to-install and autonomous devices that can measure PM10 particles and 50 mg/m3 concentrations. The minimum number of particles must be 500 mg/m3 and maximum 200 mg/m3.”

IoT devices are an able alternative to solve this problem, ennomotive says, with industrial IoT devices safer, more robust, and reliable for extreme environments (high temperatures, powerful vibrations, dust, humidity, corrosion, wear, etc).

ennomotive said the open innovation challenge ruled out existing commercial solutions due to their lack of robustness (too sensitive to endure extreme environments), reliability (high failure probability for some components) or precision (indirect measuring).

As part of the challenge, three solutions were selected with the following technologies:

  • Autonomous laser interferometer technology with a sensor-cleaning system and Edge computing for local alert-management data processing;
  • Combination of LED sensor and broadband photodetectors, and automatic calibration of the receive paths with mathematical processing; and
  • The development of a new sensor based on light scattering: an Arduino board converts the measurements into intensity relations and sends them to a central server as concentrations.

The first three prototypes were evaluated on site according to measurement quality, maintenance, autonomy, data transmission, etc. The result was a more robust prototype that combined the strengths of the three previous technologies, ennomotive said.

Thanks to the challenge, it was possible to design and evaluate different technologies, prototype, and test in a record time of five months, ennomotive said. “Open innovation has proven to be a very efficient tool to accelerate the development of new products.”

To read more about the winners, follow these links below:

https://www.ennomotive.com/power-consumption-optimization-iot/

https://www.ennomotive.com/artificial-intelligence-industry/

https://www.ennomotive.com/winner-maksym-gaievskyi/