Digital Technologies for the Plastic Industry

The manufacturing industry is undergoing a digital transformation. While the main tasks and workflow in a production may remain the same, the approach in a digitalized company can significantly enhance efficiency and maximize benefits.

The main tool for achieving digitalization in production is the Manufacturing Execution System (MES), which can support standard workflows and offer more sophisticated functionalities to facilitate this change. An efficient and well-designed MES can also improve interconnectivity between the users by recording the data and offering a usable interface. This tool is the key point in transferring the experiences from a skilled employee to another employee, reducing the effort of employee training.

But how will this system be affected in the future? Considering the inevitable improvements in the digital world, we can expect MES systems to evolve and become even smarter. With the help of artificial intelligence and optimization logic, the system can become even more insightful, helping companies to grow to their full potential.

To meet the increasing demand for high quality production in the Injection Moulding process it is important to keep a stable process, despite the changes in viscosity coming from changes in melt index, tool temperature and other external parameters. These parameters can be compensated by adjusting manually the tip temperatures of the hotrunner, but this is a time-consuming task.
Kistler has now developed and fine-tuned Multiflow, an automatic hotrunner fill-balancing technology based on the cavity pressure sensors. The system can run with most hotrunner controllers and we have optimized the ease of installation and use together with the German hotrunner controller manufacturer Fiege.

Mouldflo is ready to take a step into IOT with Mouldlive, to support cooling processes and mould maintenance QA and QC processes for organizations requiring high quality standards.
Mouldflo will show how Mouldflo products can support the processes and how Mouldlive makes data acquirable on a big scale.

Too many opportunities are missed when successful digitalization is only measured in terms of ERP, AI, or RPA implementations. In fact, ‘go big or go home’ is a common misconception when it comes to digitalization. Barely any organization can swallow a whole elephant all at once, but almost all organizations can eat it bite for bite. The key to successful digitalization is starting small, being aware of your business’ daily operation and involving frontline employees in identifying the best areas for improvement.
At Gluu we argue that digitalization comes in many forms and business processes can bridge the gap to the truly revolutionary digitalization – with incremental improvements towards the goal.

Digitalization is a great buzz-word, but if we copy our manual behavior into an automated process, we will miss the opportunity of improving the process. Digitalization requires process know-how and valid data to succeed. The transition from human error to automated error should be avoided by knowledge and analysis. The knowledge of your process, your data, and you customer’s expectations.

One of my questions is – do you know the difference between correlations and causalities? I will try to give you at least part of the answer.

Additive manufacturing of soft-tools for injection molding is becoming a standard process to increase speed of prototyping and reduce costs of tools manufacturing. Standards have been developed over the past years, but the process had shown some limitations in precision, resolution, and surface quality, which limited its use in the micro-manufacturing world.

Integrating high-speed 2PP micro-3D printing and a unique micro-injection molding expertise, NanoVoxel is the first company worldwide to offer micro-molded parts with fastest delivery time down to two weeks, precisions down to single digit micrometers, freedom of design with radii potentially below 1 µm, surface roughness down to 10 nm and production quantities ranging from few prototypes to mass production.

3D-printed injection mold tooling is emerging as an attractive cross-over from 3D-printed prototypes to injection-molded parts. However, conventional 3D-printed tooling solutions have been based on the same design principles and design constraints as conventional injection mold tooling. Addifab is pioneering the use of soluble 3D-printed injection mold tooling elements to dramatically accelerate advanced product development and remove design constraints. Lasse Staal, co-founder of Addifab, will share key learnings from researchers and companies using soluble tooling to transform their product management.

The manufacturing of mould components for high-volume production injection moulding today can be conducted with only subtractive-based technology, or integrating metal additive manufacturing, to increase the moulding performance with improved designs. However, effective methods are missing for the selection of the most suitable technology for a given tooling project.
In this presentation a method to compare the two process chains (based on additive and conventional subtractive technologies) is shown. The comparison is based on a technology focused-performance analysis through computer simulation, highlighting potential bottlenecks for production, and a cost analysis, to reveal the major drivers in the final cost of the manufactured mould component.

With polymer selective laser sintering (SLS) is possible to produce highly customized plastic components. However, the long cooling time of the powder matrix limits the maximum system productivity.
In this talk a method to reduce the cooling time of SLS without compromising on quality will be presented. The method is based on the integration of in-printed cooling channels within the powder matrix. A cooling solution is realized using printed channels, and corresponding thermal simulations are developed to predict cooling rates for different channel configurations. Experimental and simulation results show that a 45% cooling time reduction can be achieved while maintaining the same geometrical quality characteristics in terms of dimensions and form error of parts obtained with long cooling times.

Increasing demand for plastic parts in today’s world leads to more focus on plastic parts’ manufacturing methods. The old empirical methods have been replaced with different modern techniques including digital twins, statistical models, and machine learning approaches. These are the key enabling techniques connecting injection molding to industry 4.0.
This talk will revolve around the manner and the results of adopting these techniques for a case study (Blush defect).

Polymer extrusion is a well-established technology due to its high productivity and the ability to manufacture complex cross-section products. However, for highly customized products and small batches, the die design and manufacturing are lengthy processes that limit new products development and their production. Recent development in polymer AM have enabled composite materials and tough polymers to be manufactured. AM offers flexibility by enabling streamlined die design which results in more flow balance and lower die head pressure. Flow simulations were performed to predict the die head pressure and melt flow velocity across the profile extrusion section. Furthermore, simulation contributes to process die design since the objective function of die geometry optimization is performed based on the average velocity and velocity distribution of polymer melt across the profile cross section in the die channel and the die exit. Therefore, the opportunity is foreseen to integrate additive manufacturing and simulation into the extrusion process and value chain.