Artificial intelligence (AI) is transforming the plastics industry, and the injection molding sector is no exception. From optimizing production processes to enhancing quality control, AI is proving to be a game changer. Here are some of the latest advancements from leading injection molding machine and equipment manufacturers in integrating AI applications.

Arburg

ARBURG customers are increasingly using digital tools like the arburgXworld online platform to work faster and smarter with AI-powered features. Two standout apps, “Ask ARBURG” and “Programs”, boost productivity significantly.

Ask ARBURG, part of the Premium arburgXworld package, is an AI chatbot that quickly answers machine and process-related questions. It taps into ARBURG’s vast knowledge database to provide precise solutions, saving time in troubleshooting and helping employees verify their expertise. Constantly learning, it improves over time and speeds up root cause analysis.

Arburg has launched the “Ask ARBURG” AI chatbot for answering machine and process-related questions.

Programs is an app that centrally manages machine data, even from different brands, making it ideal for multi-brand molding operations. It enables comparison and optimization of machine programs across sites and converts data for use. This ensures all machines are integrated, streamlining scheduling and saving time through centralized management.

ENGEL

ENGEL sees AI and digital twins as key to the future of injection molding process optimization. At its Digital Days event held in last year, ENGEL showcased the prototype of ENGEL GPT, a large language model designed to reduce reliance on internal emergency services and mitigate knowledge loss within the organization.

Integrated into the customer portal, ENGEL GPT allows shop floor employees to access machine and process data as well as extensive and interconnected knowledge directly using voice input.

ENGEL introduced the prototype of ENGEL GPT at the Digital Days last year.

ENGEL’s suite of iQ software apps is an AI-powered platform for controlling injection molding progress. For instance, iQ weight control detects fluctuations in the injection volume and material viscosity and automatically compensates for them, and the iQ process observer analyzes hundreds of parameters simultaneously, displaying deviations and corrective measures.

KraussMaffei

KraussMaffei has long offered production monitoring technologies to optimize machine operation and energy consumption. Its cloud-based socialProduction collects and visualizes machine data while enabling real-time monitoring and analysis. Machines independently send chat messages to report events or issues, and users can communicate via text and images for seamless collaboration.

processSupport, one of the socialProduction components, uses AI to detect process deviations and alert users proactively. Built on KraussMaffei’s deep plastics process knowledge, which has been embedded in a complex algorithm for this purpose, the technology leverages all available machine parameters within socialProduction for visualization and analysis, ensuring efficient and informed decision-making.

The socialProduction platform of KraussMaffei collects and visualizes machine data while enabling analysis.

WITTMANN Group

At the WITTMANN Competence Days 2024, participants had the opportunity to experience AIM4Help, an AI-driven expert system for technical support and troubleshooting.

Accessible via a web portal, AIM4Help assists with mold settings, robot programming, and more. Trained on WITTMANN’s extensive documentation, including technical documents, charts and error analyses, the system ensures efficient and accurate responses.

Besides, an extensive database supports maintenance and servicing to boost efficiency. WITTMANN's “health factor” monitors the condition of servo-hydraulic axes, helping predict wear and pump defects. This enables proactive planning for repairs and timely ordering of spare parts, reducing machine downtime.

The injection molding sector is increasingly embracing AI to actively adjust processes for optimizing the yield and quality of injection-molded parts in series production. Far from being a futuristic concept, AI has become a present-day imperative for the sector.