Tasks of the center:
Development and implementation of strategies for automation and digitalization of technological business processes of industrial enterprises in Kazakhstan to create a critical mass of enterprises — market drivers (~20% of the pool of enterprises of MMC, NGS, mechanical engineering, etc.), actively implementing new technologies to acquire financial and operational advantages.
Platform for Industry 4.0
Industrial artificial intelligence platform Brains.app allows to make real-time decisions for the mining, oil and gas, manufacturing, energy and logistics industries.
This platform creates a process simulation environment that continuously synchronizes with real-time data, identifies process bottlenecks, executes "what if" scenarios, and trains operators to choose the most effective approach in such situations. Big data analysis increases the efficiency of technologies and equipment.
Digitalization Assessment Toolkit
The module allows you to analyze the business processes of an enterprise in order to draw up plans and stages for automation, which makes this process more productive.
Goals of the center
Optimization of the grinding cycle at the beneficiation plant of JSC "AK Altynalmas" using the industrial AI platform
In 2019, IntelliSense-LAB completed the implementation of a pilot project based on the Aktogay gold recovery plant of JSC "AK" Altynalmas "in terms of the development of artificial intelligence systems for predictive analysis of the" grinding cycle "process.
This is the first model production in the country using artificial intelligence technologies and the Internet of Things for predictive analysis of the “grinding cycle” process in order to reduce costs and increase productivity.
Brains.app, an industrial AI platform, predicts ball loading and liner wear and prevents mill overloads, resulting in increased process transparency and reduced mill downtime.
As part of the implementation of the task of optimizing the grinding cycle, the following results were achieved:|
- the "Ball loading" model shows the level of the ball charge in an operating SAG mill in real time, which made it possible to exclude technological production downtime associated with manual measurement of the level of the ball charge;
- advance notification of operators about the upcoming overloading of the SAG mill allowed to reduce the number of overloads, which in turn led to an increase in finished product output;
- The Lining Wear model monitors the wear rate of the drum linings in an SAG mill, allowing us to manage the life of the drum linings and plan for major repairs.
Cumulatively under the Grinding Cycle Optimization initiative, the annual gross economic effect / income was $ 1.3 million.
Thanks to the introduction of digitalization elements into technological processes, JSC "AK Altynalmas" became the winner of the prestigious OEE Award, which was presented on December 6 in Moscow as part of the international conference and industrial marathon "Effective Production 4.0".
The OEE Award is the first executive award awarded annually for excellence in efficient manufacturing. Among the hundred enterprises of the CIS, JSC "AK Altynalmas" won the first prize in the category "Predictive Service and Equipment Repair" for the "Digital Mine" project.
Learn more about the effects of injection here: https://youtu.be/iHBQPm7Z5I8
IntelliSense.io began operations in 2014 with a mission to significantly improve the efficiency of capital and asset-intensive industries (mining, oil and gas) and reduce health and safety risks through the use of digital technologies.