Industry 4.0: How AI Learning Is Used in Plastic Injection Molding

Today, when looking for plastic injection molding manufacturers, it isn’t just factors like price per part or delivery times to consider but what technology drives their processes. As Industry 4.0 continues to lead to breakthroughs in AI learning and its interactions with connected systems and robotics, working with manufacturers who utilize all three is paramount. Today we’re going to talk about systems and how they lead to more efficient and higher quality plastic parts production.

What Is Industry 4.0 in Manufacturing?

While it can be used as a buzzword for almost anything, when it comes to manufacturing, the Fourth Industrial Revolution or Industry 4.0 refers to “smart manufacturing” that employs sensors, machine learning, networked controllers, and advanced robotics. When paired together, these systems can not only automate tasks to free up workers for more skilled work, but can learn over time and become more efficient, help eliminate manufacturing defects, and be remotely monitored and controlled.

AI Learning Systems in Plastic Injection Molding

Understanding how AI and learning systems work can be easier with a real-world example. Here at Midstate Mold, we recently added a Shibaura EC-SXIII series All Electric Injection Molding Machine. This machine is built for use with their Injectvisor V70 Controller, which massively expands its functionality. This, combined with the two Yushjin YD Series Cartesian Robots we employ, allows for several systems to learn from and be controlled with AI.

Industry 4.0 Controllers

The heart of smart factories are the controllers—powerful hardware and networking systems that plug into the smart systems in manufacturing equipment to monitor, adjust, and learn from utilizing AI learning. Some features it provides in smart manufacturing include:

• Deep Production Customization: The controller combined with the state-of-the-art electric molding machine means everything can be customized and controlled, from clamp sequences to cycle times.
• More Efficient Mold Machines: Learning systems can analyze as the machine works, optimizing cycle times and speeding up mold set-ups for higher productivity and efficiency in machines and robotics.
• Quality and Predictive Maintenance: At Midstate Mold, we take quality control and mold maintenance very seriously. AI systems can help detect and remedy part defects, along with predicting maintenance for the mold and machine.
• MES and ERP Systems: Being able to network with other machines and robotics is only the start. Systems like the V70 can also link with manufacturing execution systems (MES) and enterprise resource planning (ERP) systems.

Learning Robotics Systems

As we detailed in our Utilizing Robotics in Plastic Injection Molding Industry blog, robotic systems can free up skilled labor from repetitive tasks and interface with industry 4.0 networks to better monitor actions and improve over time. Everything from tracking required times for robot cycle operations to optimizing those times is possible. AI learning can also make more complicated processes, such as composite part production like overmolding and two-shot molding, more efficient.

At Midstate Mold, we think all of our clients should benefit from local parts production utilizing the best parts of Industry 4.0 for better, faster parts. AI learning, networked systems, and robotics are only part of what sets us apart from other injection molders: by being mold makers and maintainers, having almost 60 years in the plastic injection industry, and focusing on the quality needed for medical and life science-grade parts and tolerances, we’re ready to tackle any project. Learn more by contacting us today or jumping right into a quote.