modelling human health vulnerability using different machine learning algorithms in stone quarrying and crushing areas of dwarka river basin, eastern india - sciencedirect
Stone dust induced risk and vulnerability in the developing nations is very thought-provoking and therefore is necessary to address scientifically to manage it. Identifying vulnerable areas using the robust method is preliminary and essential steps. The present study has intended to delineate Human health vulnerability models (HHVMs) using machine learning algorithms and justify whether ensemble prediction can provide improved results in stone quarry and crushing dominated Middle catchment of Dwarka river basin. Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF), Reduced Error Pruning (REP) Tree, Gaussian Process algorithms and ensemble prediction have been applied for HHV modelling. Total 6.9 to 7.37% in cluster 1, 9.11 to 9.6% in cluster 2, 19.63 to 26.79% and 5.34 to 12.85% areas in cluster 3 and 4 is found into very high human health vulnerable class as per the five applied models. REPTree model is found consistent for predicting vulnerability in case of all the clusters followed by GP model. As per the result of RMSE, the RF model is appeared as the most consistent model followed by REPTree. Some of the ensemble prediction models are potential for yielding improved result than individual algorithm.
productivity - stone three
The costs associated with heavy industries can be preventative. Operational costs and capital costs keep ballooning every day not to mention the burden that lost-time injuries and unplanned downtime can place on an already strained budget. Add in the expense of equipment failure as well as maintenance and energy costs, and it becomes clear just how pressure-driven the industry is by margins and revenue alone.
Given the exorbitant costs of building new plants, the only workable solution is for mining and other heavy industry companies to work with the assets they already have to increase their productivity and their efficiency in order to extract as much value as possible from their existing capacity.
Its here where Stone Three comes in offering end-to-end digital solutions that help to increase yield and optimise processes through real time analysis and instant problem-solving. In this way, our products can help to decrease unplanned downtime and maximise productivity, while saving millions in the process.
By leveraging the power of machine vision and machine learning, Stone Three has developed a range of digital productivity solutions that have been adopted by leading enterprises not just locally, but internationally as well. These include:
With a highly skilled team of specialists in place, were able to support the global mining industry with end-to-end services that include process diagnostics and integration with advanced process control platforms, in order to deliver actionable insights and outcomes-based solutions. Or to put it more simply, were dedicated to developing technology that not only increases your productivity significantly, it saves you valuable time and money as well.
A working primary crusher is of key importance in the mining industry, and is a vital link between the mine and plant. If rocks or other materials are oversized when entering the crusher, they can cause significant damage, which can be costly to repair. The Stone Three Truck Particle Size Measurement Solution uses machine vision laser-based sensors to measure and monitor the particle size distribution of ore as it goes into the crusher, improving uptime, increasing efficiency and providing actionable feedback, ultimately resulting in huge savings for your company.
Overloading and underloading can present certain challenges to the haul trucks carrying materials between pit and plant challenges that the Stone Three Truck Payload Volumetric Measurement Solution has been specifically designed to offset. With this machine vision system in place, your haul truck loads will be monitored via AI-augmented smart sensors, with overloading or underloading alerts sent to you in real time, allowing you to manage any potentially dangerous or costly issues before they escalate. The benefits? More productivity, more visibility, and more control of your precious cargo.
Grinding mills are costly to run, and so ensuring their ongoing efficiency and productivity is vitally important. Irregular feed size can lead to inefficient grinding and reduced throughput, which can ultimately cause damage, delays, and unforeseen expenses. With the Stone Three Milling Diagnostics and Analytics Solution, youll be able to use the machine vision system to continuously monitor your feed size distribution and detect oversized materials in time, improving your mills performance and your uptime as well.
Managing your key assets is always vital to keeping costs down on site, particularly when it comes to conveyor belts. Belt failures can be dangerous, disruptive and costly but thankfully, can also be prevented. A machine vision system, the Stone Three Belt Condition Monitoring Solution will identify surface features on your conveyor belts, such as splices, tears and edge deformations, while detecting belt drift at the same time. This type of enhanced early detection helps to simplify the belt inspection process, resulting in improved maintenance scheduling and helping to keep costs and downtime at a minimum.
A healthy mineral extraction process relies on optimal crusher performance and complications like improper gap settings, irregular feed size and unpredictable liner wear can compromise this. With Stone Threes machine vision Crusher Diagnostics and Analytics Solution, youll be able to continuously monitor the feed and product size distribution in real time, while improving your maintenance planning, increasing your crusher uptime, and optimising your crusher control at the same time.
Looking for increased recovery and more accurate grade control with your froth flotation process? Our Flotation Diagnostics and Analytics Solution uses a machine vision system to continuously monitor your key froth and pulp metrics, allowing for automatic detection of suboptimal froth states, measurement of mass pull per cell and estimation of grade and recovery, ultimately resulting in improved flotation circuit control overall.
Its not enough to just tell you that our digital productivity solutions save you time and money. We need to prove it too by showing you just how positive an impact our products and services have had on the industry as a whole:
What these compelling statistics demonstrate is that increased productivity isnt just probable its completely possible. And thats why we do what we do at Stone Three. Designing, developing and producing solutions and services that make your life easier, that save you valuable time and money, and that help your company perform to the very best of its ability. Its the power of AI, and its here to drive your continued longevity and success.
The most important thing to keep in mind when developing solutions for the Mining Industry is that one needs to be customer focused. You need to provide tangible value for your customers by applying the recipe of the right technology, processes and people.
In three years, I would like Stone Three to be the preferred global partner in digital safety and productivity solutions. I believe that this will be achieved by implementing innovative solutions that directly address market needs and by providing unparalleled after sales support to our customers.
To solve the biggest problems, you need a clear goal, a good team, and a willingness to be self-critical. Our teams passion and unique skill set are what enables us to build successful global technology solutions.
I grew up in a combination of Malawi, Stellenbosch and Worcester, studied Industrial Engineering, my first job was something of everything in a small startup that built a solution for mobile sales reps in the age before smartphones. I was very fortunate to be exposed to a bit of everything in such an early stage of my career.
I am most inspired by an opportunity to make doing something more efficient. Right now, we have an amazing opportunity to help clients navigate through challenging times, through digital solutions which bring
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stone crushing equipment market- global industry analysis, size and forecast, 2015 to 2025
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A stone crushing equipment is used to reduce the size, or to change the shape of the raw material mix by breaking down the stones into small pieces, so that they are easily differentiated for the desired end use. The crushing equipments are made up of metal surfaces which are capable of compressing all varieties of material, such as stones, quartzite, rocks, coke, iron, and many others. The crushing equipments operate by applying compressive strength to the material and crushing it by means of collision between the machine and the materials.
The stone crushing machines finds use in a variety of fields such as building materials, mining, metallurgy, highways, chemistry, and railways etc. Based on the requirement put forth by the type of construction activity such as highways, roads, canals, buildings, and bridges etc., the stone crushing equipments can produce various sizes of crushed stone. With the current growth rate of global urbanization, the stone crushing equipment market is anticipated to witness a surge in demand for crushers applied in construction of infrastructure and other activities. `
The stone crushing equipments are required to be located close to the demand centers such as cities, canals, and bridges, etc. as the hauling of the crushed stone over long distances sums up to the cost of the final product. Stone Crushing equipments also demand a heavy electricity supply and a large manpower for operation and also requires access roads for the movement of crushed stone products. Owing to these reasons, most stone crushing equipments are located in the vicinity of major construction projects or along the periphery of the cities.
Global stone crushing equipments market is segmented into types, application, and region. The global stone crushing equipment market is segmented on the basis of types as: Jaw crusher, cone crusher, impact crusher, and others.
Owing to the continuous development of the construction industry all over the world, the inland as well as the marine reserves of natural sand and stone are gradually depleting. This has led to an increased attention on the artificial stone and sand manufacturing industry. This in turn has fueled the demand for crushing equipments globally.
Introduction of new technologies such as mobile crushers are also driving the growth of the global stone crushing equipment market The rising prices of the crushing equipments all over the world proves to be a restraint to the growth of the global stone crushing equipment market
Some of the major players identified in the global stone crushing equipment market are Metso Oyj, Sandvik AB, Terex Corporation, Caterpillar Inc., Komatsu Ltd., Joy Global Inc., BUCY International, and CNH Global N.V., etc.
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