Use case Artificial Intelligence:
Optimization of Distillation Process
Use case Artificial Intelligence
Optimization of Distillation Process
If you are looking for ways how to apply Data Science or Artificial Intelligence in industrial production, you’ve come to the right place.
HAI is an expert in developing and implementing data science applications in industry.
This Use Case in a chemical plant was the winning project of the worldwide SAS Hackaton, and can be applied in many other industrial processes.
| Industry | Chemical Industry |
| Process | Distillation process |
| Objective | Optimize process: cutting energy consumptions, process improvement and complying with sustainability goals |
| Results | AI model that optimizes quality, yield and energy consumption |
| Award | Winning Project of the Global SAS Hackaton for Manufacturing |
Background
Years ago this chemical production plant was one of the early adopters of applying data analysis to support their daily operations.
Over time, they managed to develop a data science application supporting operator decision making for their distillation process.
The model used data from product quality test results along with historical yield data, to support optimum process control of the distillation process.
The challenge for a more sustainable and cost-effective operation
The Chemical Plant is actively seeking opportunities to enhance its sustainability efforts by minimizing energy consumption. This imperative is further underscored by escalating energy prices, which significantly affect operational costs. In response, the Technology & Innovation Team has chosen to collaborate with HAI to augment their existing system, which previously prioritized quality and yield, by incorporating comprehensive data on energy usage.
Manufacturing Insights tool for Sustainability and Process Optimization
Drawing upon input from the Manufacturing Team, HAI experts have crafted a robust Manufacturing Insights tool designed for advanced statistical process monitoring and predictive modeling. This tool offers comprehensive analysis and insights into CO2 production.
The Manufacturing Insights tool provides process technologists with detailed insights into energy consumptions, and opportunities for process improvements and cost reductions. In the past, it took them much time to collect and analyze these data.
How to implement the AI-tool in the daily operations
Furthermore, the AI tool has been seamlessly integrated into the daily operations of operators, serving as an integral component of their routine tasks. This integration enables real-time support for operator decision-making processes. Achieved through the incorporation of the AI model within digital operator logsheets, this approach ensures active utilization of the model by operators. Moreover, it facilitates automatic model enhancement through the continuous accumulation of new data, thereby ensuring its ongoing refinement and effectiveness.
Operator feedback loop
Operator involvement is crucial with application like this. That’s why the company decided to include an operator feedback loop in the digital logsheets. This enables operators to provide feedback on how and why the advice from the AI-tool was followed. This helps to improve the AI-tool and ensures operator involvement.
Winning project in the global SAS Hackaton
The global SAS Hackathon focuses on innovating software solutions to tackle critical societal and business challenges. Teams comprised of data scientists, technology enthusiasts, and visionaries collaborate with experts and SAS mentors to address significant issues faced by industries and governmental bodies. Among the projects, the Manufacturing Insights tool emerged as the Winning Solution for Manufacturing, recognizing its excellence in addressing industry challenges.
Read more about HAI’s successful implementations of Artificial Intelligence in Industries: https://hai.nl/artificial-intelligence/
Get inspired
Interested in more best practices of smart use of factory data, in the Food and Chemical Industry?
Get inspired by successes of others when it comes to OEE, quality, positive release, golden batch, CIP-cleaning, operator support, factory data anaytics, in-line measurements, production & technology dashboards… and much more.
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