Competition Topics
Technical Case Study

Theme: Artificial Intelligence in Chemical Engineering

Title: "Harnessing AI for Sustainable Waste Management in the Chemical Process Industry"

This competition challenges participants to design an AI-driven waste management system for a chemical manufacturing facility. The solution should focus on reducing waste, improving recycling, and enhancing risk management. Participants will evaluate their design based on innovation, feasibility, environmental and economic impact, and the challenges of implementation. The presentation must include clear objectives, practical insights, challenges, and recommendations for further research, all backed by solid evidence and references.

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Technical Video

Theme: Artificial Intelligence in Chemical Engineering

The competition explores various ways AI is revolutionizing chemical engineering. Topics include:

  1.                                                                                                                                                                                                                                                                                                                 AI-Driven Process Optimization in Chemical Plants: Explore AI algorithms that enhance efficiency in chemical plants by analyzing parameters like temperature, pressure, and flow rates in real time to reduce waste and energy usage.

  2. Sustainable Chemical Process Using AI: Highlight how AI aids in sustainability through optimized resource use, reduced emissions, and the development of eco-friendly chemicals, green chemistry practices, and renewable energy solutions.

  3. AI in Chemical Reaction Engineering: Show AI's role in predicting reaction conditions, modeling kinetics, and designing reactors to bridge lab and industrial applications.

  4. AI-Powered Process Control Systems: Emphasize the importance of AI in real-time monitoring and automatic adjustments for production stability and prevention of equipment failure.

  5. AI Applications in Waste Management in Chemical Engineering: Focus on AI-enhanced sorting, processing, and recovery systems that minimize environmental impact.

  6. Predictive Maintenance in Chemical Engineering with AI: Demonstrate AI's impact in predicting machinery failures using sensor data, thus preventing unexpected shutdowns and prolonging equipment life.

  7. AI-Assisted Material Design for Chemical Engineers: Show AI’s role in designing new materials, predicting properties, and optimizing chemical compositions to accelerate innovation.

  8. Data-Driven Innovations in Chemical Engineering through AI: Illustrate AI’s potential in handling large datasets to improve process safety, optimize production, and drive innovation.

Participants should explore these topics in detail and discuss their real-world applications in the chemical industry.

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Technical Essay

Theme: Artificial Intelligence in Chemical Engineering

The competition explores various ways AI is revolutionizing chemical engineering. Topics include:

  1. Optimizing Chemical Processes: How AI improves efficiency and yield while reducing resource usage and environmental impact.

  2. Predictive Maintenance: AI’s role in enhancing equipment reliability, saving time and costs.

  3. AI-Driven Material Discovery: Accelerating innovation by using AI to discover new materials.
  4. Machine Learning in Reaction Optimization: AI's impact on speeding up processes, saving energy, and improving product quality.

  5. Real-Time Quality Control: How AI ensures defect detection during manufacturing.

  6. Sustainability Practices: AI's contribution to eco-friendly practices by optimizing resource use and minimizing waste.

  7. Ethical Implications: Navigating challenges such as data privacy and fairness in AI systems.

Participants should explore these topics in detail and discuss their real-world applications in the chemical industry.

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Technical Infographic

Theme: AI-Powered Cleaning in Chemical Engineering: Revolutionizing Industrial Processes

This topic explores how AI is revolutionizing cleaning in the chemical engineering field, particularly in ensuring equipment longevity, reducing downtime, and
minimizing environmental impacts.

  1. Predictive Maintenance and Cleaning
    Eg : AI for Predictive Analytics, Cost Savings

  2. Automated Cleaning Systems
    Eg : Robotics and AI Integration, Improved Safety.

  3. AI for Optimizing Chemical Cleaning Agents
    Eg : Smart Formulation of Cleaning Agents, Real-Time Adjustments.
  4. Sustainability in Cleaning Processes
    Eg : Energy and Water Efficiency, Minimizing Waste and Emissions.
  5. Data-Driven Process Optimization
    Eg : Continuous Monitoring, Customization of Cleaning Procedures

  6. Applications in Various Industries
    Eg : Automated cleaning systems (Food and Beverage Industry), Predictive maintenance
    (Biotechnology).

Participants should explore these topics in detail and discuss their real-world applications in the chemical industry.

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Technical Debate
Topics include:
 
1.
AI-Powered Customization: Ethical concerns about privacy and equitable access to AI-driven chemical products.
 
2.
AI in Industrial Optimization: AI’s role in improving efficiency and sustainability while balancing ethical considerations.
 
3.
Predictive Maintenance: Using AI for better equipment reliability and cost-saving.
 
4.
AI in Plant Operations: Enhancing emission reduction while considering safety risks.
 
5.
AI-Enhanced Simulations: The potential of AI to replace physical experiments and its impact on accuracy.
 
6.
Ethical AI Systems: Discussing if AI should prioritize profit or be regulated for ethical and environmental sustainability.
 
7.
Process Automation: AI-driven automation's impact on the role of skilled engineers.
 
8.
AI and Cybersecurity: Addressing the risks of AI-driven systems in critical infrastructures.
 
Participants should discuss these topics in detail and explore their real-world applications in chemical engineering.
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Plant Design Competition
Theme: Wastewater Treatment Plant Design (NACES 2024)
 
The competition focuses on addressing hazardous waste management and optimizing wastewater treatment plants (WWTP) using advanced technologies like AI.
 
1.
WWTP Specifications: Identify the design requirements and raw materials.
 
2.
Process Flow Development: Design unit operations and describe the flow of the treatment process.
 
3.
Waste Minimization: Strategies for reducing hazardous waste.
 
4.
Environmental Quality Act Compliance: Ensuring the design aligns with regulations.
 
5.
Mass and Energy Balance: Perform basic calculations to assess efficiency.
 
6.
Cost Estimation: Estimate the treatment cost based on the design.
 
7.
Safety Considerations: Address safety issues in the WWTP design.
 
8.
AI Applications in Wastewater Treatment: Explore AI's role in optimizing water treatment and recycling.
 
9.
Sustainability and SDGs: Reflect on how the design promotes sustainability and aligns with SDGs.
 
Participants are expected to create a complete design addressing efficiency, safety, and sustainability using advanced AI technologies.
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