In the ever-evolving landscape of industrial technology, artificial intelligence (AI) and machine learning (ML) are making significant strides in various sectors, including mixing technology.
Jongia Mixing Technology is at the forefront of this revolution, integrating state-of-the-art sensor technology with advanced data science to optimize mixing processes. As part of our commitment to innovation, we have established ‘LiquidZ,’ a team focused only on the leverages of these cutting-edge technologies to deliver advanced process improvements.
Introducing LiquidZ: Revolutionizing Mixing Technology with AI and ML
The ‘LiquidZ’ team at Jongia Mixing Technology is dedicated to pushing the boundaries of what is possible in the field of mixing technology. By merging Artificial intelligence, Machine Learning, and advanced sensor technology, LiquidZ offers a comprehensive approach to understanding and optimizing mixing processes.
Applications of LiquidZ Technology
The ‘LiquidZ’ technology offers numerous applications in mixing technology. First, it provides insight into mixing data by analyzing mixing times, stabilization phases, and batch consistency, uncovering inefficiencies and areas for improvement. Additionally, it excels in anomaly detection, identifying deviations that may indicate quality issues, allowing for early interventions. It also ensures batch completion and product readiness by predicting batch endpoints and monitoring real-time product specifications to maintain consistency and quality.
Moreover, LiquidZ supports process optimization and cost saving through continuous process improvements and by identifying opportunities to reduce energy and raw material usage. Quality assurance is enhanced with robust quality control measures based on data-driven insights. Finally, LiquidZ enables comprehensive data integration by combining sensor data with existing process data, providing a complete view of the mixing process.
How the Process Works
- Mixing case: The customer has a mixing case with a (optimization) problem.
- Problem definition: In consultation with the client, the problem is defined.
- Sensor implementation: A sensor will be installed.
- Data analysis: By combining the sensor data with additional customer data, the process is analyzed. This is done with the help of data analysis and machine learning techniques.
- Combining knowledge: By combining data analysis with mixing knowledge, process insights are gained.
- Mixing optimization: Recommended adjustments will be implemented in the process.
- Process optimization: Implementation of the results leads to an improvement in the process.
By leveraging advanced data analysis and Machine Learning (ML) techniques, Jongia Mixing Technology’s ‘LiquidZ’ team provides customers with the tools and insights needed to optimize their mixing processes. This innovative approach not only enhances process efficiency but also offers substantial cost savings and quality improvements.
For more information, please refer to our LiquidZ brochure.
Want to know more about Jongia Mixing Technology? If so, please feel free to contact us at www.jongia.com or sales@jongia.com
Contact our specialized team for all your questions
Tom Pruymboom
Sales Director
Area Worldwide
Bart Brouwer
Area Sales Manager
Area Worldwide
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