Transforming the Shop Floor:
A No BS Look at Data Science in Manufacturing
Transforming the Shop Floor: A No BS Look at Data Science in Manufacturing
The concept of digital transformation isn’t new to manufacturers. In fact, it’s probably something you’ve been hearing and thinking about for some time as part of Industry 4.0 initiatives. A huge part of that transformation involves maximizing the value of your data—making it accessible, using it to predict future outcomes & basing key process decisions on those predictions.
Accessibility may not seem all that intimidating—most manufacturers have collected and stored data for specialized purposes. On the other hand, if you’re like many of your peers, data science and predictive analytics may seem farfetched, or even unattainable.
The truth is, they don’t have to be. Manufacturers who are already leaning on data science aren’t throwing out their playbooks completely—they’re just using all the existing information at their fingertips to reimagine them so they can compete well into the future. The result? These early adopters are expecting close to double the ROI of competitors with less developed data science initiatives in the next 2 to 3 years.
Join us on LinkedIn Live on Thursday, October 28th at 10am ET to learn how you can lead a similar transformation—not by starting from scratch, but by getting more from what you already have. By walking through a series of real-world examples that show how your data and machine learning can be used to make smarter process decisions, you’ll leave with concrete takeaways that’ll help you fulfill the promise of data and analytics within your organization by lowering costs, creating efficiencies, and better serving your customers.
Randy LeBlanc, Vice President of Customer Success
In the day’s first session, you’ll see how allowing machines to process visual inputs can help you gather real-time data from a video feed, analyze people’s actions within it, and detect inconsistencies against pre-defined standards.
Scott Genzer, Data Scientist
In this session, we’ll demonstrate how you can use image analysis tools to create a more efficient process by transforming a standard .mp4 video file of an analog pressure gauge into precise, digitized, and timestamp-indexed data table.
This session will show you how you can use data science to move from preventive to predictive maintenance by using RapidMiner to conduct anomaly detection on real-time data. Production teams that successfully make this shift are able to mitigate unplanned downtime while ensuring that they’re not replacing parts that are still perfectly usable.
In this session, you’ll learn how RapidMiner can help you continuously monitor the shop floor by accessing industry-standard data storage programs like OSI-PI and OPC-UA, then make your team aware of important developments in real-time.
Fabian Temme, Data Scientist
In the last session of the day, you’ll learn how data science can help to address challenges in the beer-brewing process. We’ll go through an end-to-end example for Malt Yield Optimization that’s based on a research project we’re working on with some of the world’s most forward-thinking breweries. We’ll cover everything from data preprocessing to modeling, and eventually, how the right model can be deployed in a complex production environment.
3 Reasons to Attend Live
Learn how your peers are successfully leading digital transformations across their organizations with real-world examples.
Exclusive Insights from the Experts
Hear directly from our experts and interact with them live as they demonstrate cutting edge data science use cases on the shop floor.
Immediately apply what you learn to your organization to help lower costs, create efficiencies, and better serve customers.
Who Should Attend?
- Data & Analytics Leaders
- Digital Transformation Execs
- Quality Assurance Professionals
- Process Improvement Leaders
- Plant Managers
- OEE Managers
- RapidMiner Enthusiasts