At ANDRITZ, we understand that achieving autonomy in mineral processing is a journey filled with intricacies. We believe that technology, specifically AI, machine learning, and digital twins, is not a one-size-fits-all solution, but a powerful tool that requires careful application.
Our 5 steps towards mineral processing autonomy is designed to revolutionize the mining industry while highlighting essential steps for success. See how!
STEP 1: Embrace a Comprehensive Array of Automation and Digitalization Technologies
The journey towards achieving full autonomy in mineral processing operations begins with operators harnessing the complete spectrum of available automation and digitalization technologies within the plant environment. ANDRITZ, a global technology group, has been at the forefront of implementing ~200 digital technologies in mineral processing plants worldwide over the past decade.
- Revolutionize Your Plant Environment: Harness the power of automation and digitalization within your plant environment.
- Unlock Success: Tap into ~200 digital technologies effectively implemented worldwide over the past decade.
STEP 2: Adoption of AI and Digital Twin Integration:
ANDRITZ has been an early adopter in the realm of mineral processing, integrating artificial intelligence (AI) through digital twin technology. This approach involves training AI within the processing plant, effectively mitigating risks associated with implementation. This step ensures that AI becomes an integral part of the operational framework.
STEP 3: Incremental Integration of Foundational Technologies
Similar to the gradual incorporation of advanced features in modern cars, the integration of AI follows an incremental approach. Foundational technologies, such as the Model Predictive Controller BrainWave, Metris platform for asset management, and IDEAS simulation software, form the basis for achieving the ultimate goal of autonomy in concentrator environments. This stepwise approach systematically enhances mineral processing operations.
STEP 4: Implementation of Advanced Process Control and Increased Instrumentation
ANDRITZ focuses on reducing variability in mineral processing through advanced process control. This strategy leads to substantial throughput increases, recovery gains, and reduced power consumption. With the addition of more instrumentation, throughput can be further raised. These improvements set the stage for the utilization of advanced technologies like digital twins and machine learning.
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STEP 5: Training Artificial Intelligence and Synergy of Multiple Technologies
Instead of relying solely on operator training through simulators, ANDRITZ embarked on training artificial intelligence. This innovative approach circumvents the challenge of limited relevant data availability. Leveraging a digital twin of the process, reinforcement learning AI algorithms are employed to train specific unit area operations, similar to characters in video games having awareness of their surroundings. This methodology is extended to various plant operations, ultimately constructing an autonomous operation through the synergy of multiple technologies.
The journey of reducing variability, enhancing instrumentation, and increasing production unfolds progressively, guided by experience, culminating in the desired outcome.
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