SPE On Demand Workshop
Harnessing Artificial Intelligence in Polymer Processing: Fundamentals and Practical Applications with a Focus on Injection Molding
Summary
This immersive, three-day, six-hour hands-on workshop is designed to equip participants with the essential knowledge and practical tools needed to successfully implement artificial intelligence (AI) in polymer processing, with a strong focus on injection molding.
Session 1 introduces the fundamentals of AI and its transformative role in polymer processing. Participants will explore machine learning basics, digital twins, generative AI, and quality control applications, gaining a solid foundation in how AI enhances precision, efficiency, and sustainability in manufacturing.
Session 2 focuses on the practical implementation of AI—from understanding data requirements (sensor data, synthetic data, material databases) to exploring key AI applications like energy-saving process adjustments, virtual design of experiments, and mold optimization. Participants will also examine the cost-benefit aspects of AI adoption and compare cloud-based and edge computing solutions, concluding with an interactive use-case development exercise.
Session 3 shifts toward strategic planning and overcoming industry-specific barriers. Topics include system integration challenges, workforce readiness, regulatory and ethical considerations, and building a step-by-step roadmap for AI deployment. The day concludes with a collaborative discussion addressing participants' specific challenges and a guided planning session for next steps.
By the end of the workshop, participants will be able to evaluate AI opportunities within their operations, define actionable pilot projects, and outline a personalized roadmap for successful AI integration in polymer processing.
Session 1 Outline
- Welcome & Workshop Objectives
- A Brief History of AI
- Why AI is Transforming Polymer Processing
- Key Challenges in Injection Molding (e.g., cycle time optimization, defects, material variability)
- How AI Enhances Precision, Efficiency, and Sustainability
- AI & Machine Learning Basics for Polymer Engineers
- Supervised vs. Unsupervised Learning in Defect Detection
- Digital Twins for Real-Time Process Monitoring in Injection Molding
- Generative AI for Simulating Material Behavior & Mold Design Optimization
- Case Studies in Injection Molding
- AI-Driven Quality Control
- (e.g., warpage prediction, sink marks)
- Predictive Maintenance for Molding Machines
- AI-Optimized Process Parameters for Different Polymers
Session 2 Outline
- Data Requirements for AI in Polymer Processing
- Sensor Data: Pressure, Temperature, Viscosity
- Using Synthetic Data When Real Data Is Limited
- Importance of Material Databases (e.g., Polymer Flow Characteristics)
- Key AI Applications in Injection Molding
- Reducing Scrap & Energy Consumption Through AI-Driven Process Adjustments
- AI-Powered Mold Design & Cooling Optimization
- Virtual DoE (Design of Experiments) for Faster Process Validation
- Cost-Benefit Analysis & ROI of AI Implementation
- Estimating Cost Savings from Reduced Defects & Downtime
- Comparing AI Solutions: Edge Computing vs. Cloud-Based Systems
- Hands-On Exercise: Identifying AI Use Cases in Participants’ Molding Processes
Session 3 Outline
- Data Requirements for AI in Polymer Processing
- Sensor Data: Pressure, Temperature, Viscosity
- Using Synthetic Data When Real Data Is Limited
- Importance of Material Databases (e.g., Polymer Flow Characteristics)
- Key AI Applications in Injection Molding
- Reducing Scrap & Energy Consumption Through AI-Driven Process Adjustments
- AI-Powered Mold Design & Cooling Optimization
- Virtual DoE (Design of Experiments) for Faster Process Validation
- Cost-Benefit Analysis & ROI of AI Implementation
- Estimating Cost Savings from Reduced Defects & Downtime
- Comparing AI Solutions: Edge Computing vs. Cloud-Based Systems
- Hands-On Exercise: Identifying AI Use Cases in Participants’ Molding Processes
Outline
- Challenges in Adopting AI for Injection Molding
- Data Silos Between Machines & ERP/MES Systems
- Legacy Equipment Compatibility & Retrofitting Solutions
- Workforce Training for AI-Assisted Decision-Making
- Creating a Custom AI Implementation Plan
- Pilot Project Selection (e.g., Defect Detection or Predictive Maintenance)
- Phased Rollout: From Small-Scale Trials to Full Production Integration
- Partnering with AI Vendors vs. In-House Development
- Regulatory & Ethical Considerations
- Ensuring AI Compliance with Industry Standards (e.g., ISO, FDA for Medical Molding)
- Bias Prevention in AI Models (e.g., Material Batch Variations)
- Group Discussion & Q&A: Addressing Participant-Specific Challenges in Polymer Processing
- Closing & Next Steps
On Demand Costs
| SPE Premium Member |
$540 |
| SPE Members |
$600 |
| Nonmembers |
$800 |
Purchase On Demand
ON DEMAND ACCESS ENDS APRIL 30, 2026!
Not an SPE member? Join today and purchase this workshop at a discounted rate!
Workshop Packs
Strengthen your team’s skills and take advantage of group savings with an SPE Workshop Pack.
Go here for Workshop Pack information and registration.
Instructor
Andres Urbina
Processing / Tooling Specialist
Carcoustics International GmbH
Andres Urbina is a highly accomplished professional with a Bachelor's degree in Mechanical Engineering and a master's degree in Materials & Manufacturing Processes, specializing in Simulation and Plastic Processing. His distinguished international career spans Latin America, the USA, and Europe, showcasing exceptional expertise in optimizing the supply chain value of plastics across various industries.
In addition to his role as a full-time engineer at a Tier 1 company in Germany and certified as a RJG Master Molder I, Andres has made significant contributions to academia. He served as a Professor at the University of Barcelona and held the position of Senior Trainer at the Injection Center (CEI) in Colombia. Beyond his professional engagements, he is an avid writer, contributing over 10 technical articles to esteemed publications such as Tecnología del Plástico and Metalmecánica. Currently, he serves as a technical editor for Plastics Engineering, focusing on the European region.
Questions? Contact:
For questions, contact Iván D. López.
Who Should Purchase On Demand?
This workshop is designed for professionals across the plastics industry who are looking to leverage artificial intelligence for enhanced efficiency, cost savings, and innovation. It is ideal for:
- Business Leaders in Plastics Manufacturing: Gain strategic insights to drive AI adoption and stay competitive.
- IT and Operations Managers: Learn how to integrate AI and Digital Twin technologies to streamline production and optimize processes.
- Financial and Strategy Planners: Understand the cost benefits, ROI, and scalability of AI-driven solutions.
- Sales & Technical Sales Professionals Involved in RFQ Phases: Enhance proposal accuracy and value propositions with AI insights.
- Purchasing Managers: Optimize supply chain and procurement decisions using AI data analysis.
- Set-Up Technicians, Process Engineers, and Plant Managers: Discover practical tools for real-time monitoring and process optimization.
- Product, Material, and Technical Development Engineers: Explore how AI can improve product design, material selection, and performance.
- Moldmakers, Tooling Engineers, and Tooling Managers: Implement AI for predictive maintenance and tooling efficiency.
- Industrial Engineers, Tool Designers, and IT Professionals in Plastics Manufacturing: Leverage AI for production planning, automation, and system integration.
- Students (B.Sc., M.Sc., Ph.D. Candidates): Gain a competitive edge by understanding the latest advancements in AI for polymer proc
Whether you're looking to lead AI initiatives, optimize operations, or stay ahead in your field, this workshop will equip you with the tools and knowledge needed to harness AI in polymer processing.
Why Should You Purchase On Demand?
Are you looking to harness the power of artificial intelligence in polymer processing and injection molding?
Whether you’re in manufacturing, product development, or process optimization, understanding how AI can enhance efficiency, reduce waste, and improve product quality is essential.
Struggling to integrate AI and Digital Twin technologies into your operations?
This hands-on workshop provides practical tools and strategies to seamlessly incorporate AI solutions, including Digital Twins, synthetic data, and generative AI, into your manufacturing processes.
Concerned about the costs, scalability, or data challenges of AI adoption?
Learn how to navigate common challenges and create a tailored roadmap for successful AI implementation—covering data integration, cost analysis, and long-term scalability.
Want to stay ahead of the curve with cutting-edge AI applications?
Discover real-world examples of successful AI implementations that drive operational improvements, streamline production, and enhance product quality.
This Harnessing Artificial Intelligence in Polymer Processing Workshop offers a comprehensive, six-hour, hands-on experience designed to equip participants with the knowledge and tools needed to effectively implement AI in polymer processing, with a focus on injection molding. From foundational concepts to practical applications, you'll gain valuable insights to make informed decisions about AI adoption.
