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Web Handling Control Strategies: Model, Analyze, and Optimize with MapleSim
Wednesday, May 27, 2026 02:00 PM
Language:
English
Web breaks, sagging material, and unstable tension are among the most frustrating and costly problems in roll-to-roll converting. Web handling control can be surprisingly complex to diagnose and optimize — and understanding how the control system affects web behavior isn't always straightforward. Getting control parameters right, understanding how sensors and actuators interact, and anticipating real-world disturbances are all challenges that are difficult and expensive to solve through trial and error on a live machine.
Simulation gives engineers a safe, cost-effective way to build, test, and optimize control systems before commissioning and to diagnose problems on existing lines without disrupting production.
In this webinar, René Noack, Senior Application Engineer at Maplesoft, takes you inside MapleSim for Web Converting Systems and shows how it can be used to simulate the full range of control strategies used in real converting processes. Using practical, hands-on examples, René will walk through how to build control loops from the ground up and progressively add real-world complexity — giving you a clear picture of how your control system will behave before it ever runs on the floor.
Key Takeaways:
A clear understanding of the most common control strategies used in web handling and how to model them in MapleSim
Practical insight into how real-world factors — bearing losses, sensor noise, and radius measurement errors affect control quality and what you can do about them
Confidence in using MapleSim's ready-to-use control components to build and test control loops quickly
A framework for using simulation to diagnose, analyze, and fix web handling control problems without touching the machine
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Asking Better Questions in an AI World: Using Math Tools to Build Understanding
Thursday, June 18, 2026 02:00 PM
Language:
English
AI has changed the kinds of questions students can answer — and the kinds of questions educators need to ask. When AI can solve a problem instantly, the real learning opportunity shifts to exploring the mathematics behind the answer, testing assumptions, interpreting results, and explaining why the answer makes sense.
In this webinar, we’ll look at practical examples of how math tools such as Maple can help educators ask better questions: questions that invite students to visualize, experiment, compare approaches, investigate “what if” scenarios, and build intuition. We’ll also discuss how AI can be used productively — not as a replacement for student work, but as a tool for questioning, checking, refining, and reflecting.
This session is for educators who want to adapt their teaching for an AI-enabled world while keeping the focus on student thinking, mathematical reasoning, and deep conceptual learning.
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Connected Engineering Workflows in Maple Flow: Improving Calculation Traceability and Analysis Efficiency
Thursday, June 25, 2026 03:00 PM
Language:
English
Modern engineering workflows increasingly depend on the ability to integrate calculations, documentation, data sources, and analytical tools into a cohesive and traceable process. As projects become more multidisciplinary and data-driven, engineers require environments that support transparency, reproducibility, and efficient analysis without compromising technical rigor.
In this webinar, Samir Khan will demonstrate how Maple Flow supports connected engineering workflows through an interactive, document-centric calculation environment. Unlike traditional spreadsheet-based approaches, Maple Flow enables engineers to combine mathematical analysis, documentation, units-aware calculations, and data connectivity within a single auditable workspace.
Attendees will gain insight into how Maple Flow can be applied to everyday engineering tasks involving iterative calculations, technical communication, and connected analysis workflows.
What you'll walk away knowing
Connected workflows: Learn how to connect data sources, documentation, and calculations in a single, live environment.
Practical use of AI-assisted engineering tools: Understand where AI-assisted features can help accelerate engineering workflows
Computation traceability by design: Learn how to structure calculation sheets so every assumption, input, and derived result is auditable and review-ready.
Beyond spreadsheets: Examine where traditional spreadsheet workflows become limiting for engineering analysis and how Maple Flow addresses those challenges.
A faster design iteration loop: See how a live, recalculating environment can reduce the overhead associated with design changes and support more efficient exploration of engineering alternatives.
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