Digital Solutions for Polymer Science

As a bridge between research and industry, the PCCL is in a unique position. Thanks to our role as a bridge between research and industry, we are able to transfer both traditional and state-of-the-art robotics technologies from research into industrial applications. This is particularly true of our unique expertise in the field of high-speed testing of 3D-shaped components.

Automated surface inspection of 3D free-form components requires precise and efficient robot-based automation solutions. By combining cutting-edge research with industrial applicability, we at the PCCL offer the most suitable solution for inspecting any specific 3D component. This includes the selection of hardware (e.g., robots, optical devices), software development, as well as the creation and optimization of efficient robotic scanning and the precise evaluation of detected defects. All these steps are carried out in close collaboration with our project partners from industry. 

As a project partner to several major manufacturers, we understand the importance of flexibility and reliability in an image processing and inspection system. One of the main goals of the PCCL is therefore to provide a solution for automatically optimizing and adapting the robotic system to new 3D components and changes during production. In this way, a robot can generate and optimize its scan path with minimal human supervision to obtain visual data from the surface of a free-form part, taking all task requirements into account.

The evaluation is based on the latest research in the field of deep learning, distinguishing between good anomalies and actual defects to significantly reduce the rejection of defective components.

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Flyer “Measuring the Visible[LE1]”

Humans excel at sensing and perceiving the haptic properties of surfaces. In this context, robots can learn from humans. At the PCCL, we develop intelligent measurement systems that outperform the limitations of the human sense of touch.

In industrial applications, the characterization of the tactile properties of surfaces - such as perceived friction, roughness, or hardness - is still largely performed manually or often omitted entirely. This is primarily due to the challenges humans face in producing objective, consistent, and reproducible evaluations, as well as the lack of suitable automated testing capabilities.

Our primary goal is to develop and provide automated systems that deliver quantitative, standardized results regarding haptic surface effects. These testing systems enable inline quality control, i.e., the detection of haptic surface defects (e.g., burrs, cuts, creases), and they support data-driven decisions throughout the entire value chain.

PCCL testing systems provide accurate, reproducible assessments of tactile surface properties in a short time, particularly where subjective perception reaches its limits.

In collaboration with industry partners, we continuously refine our inspection strategies to meet real-world production requirements, including those involving complex component geometries and composite materials. This includes capabilities for handling complex free-form surfaces, optimizing robot-assisted exploration movements, and reducing testing times - all with the goal of further improving the usability in industrial applications.

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Flyer “Haptic Research”

The accurate description of material behavior is a key prerequisite for reliable simulations and the virtual development of modern polymer-based components. Polymeric materials exhibit complex, nonlinear, and time-dependent properties that are strongly influenced by manufacturing processes, environmental conditions, and loading scenarios.

At PCCL, experimental material characterization and numerical modeling are closely integrated. Simulation objectives are used to define the required material data, while experimental investigations are conducted to develop and calibrate physics-based material models. This simulation-driven approach enables an efficient and application-oriented description of material behavior.

A particular focus is placed on the characterization and modeling of damage and failure mechanisms. In addition to conventional material properties, fracture and damage characteristics are specifically determined and incorporated into suitable material models. This allows realistic prediction of crack initiation, delamination, progressive damage, as well as aging- and load-dependent degradation.

The main focus areas include:

• Nonlinear material behavior 
• Viscoelastic and viscoplastic properties 
• Process-dependent material behavior 
• Anisotropic and orthotropic material models 
• Fracture and damage modeling 
• Multi-material and composite systems 
• Aging- and degradation-related material behavior 

By closely linking material characterization, model development, and simulation, a continuous virtual product development workflow is enabled — from the material level to component performance. This methodology reduces development time, improves prediction accuracy, and supports the development of reliable polymer-based components.

Modern polymer-based materials and multi-material systems are subjected to various physical loads during manufacturing and operation. The interactions between material behavior, process conditions, and operational loads significantly determine component performance and reliability.

At PCCL, multi-physics and multi-scale simulation methods are developed to realistically capture these complex interactions. Coupled simulations are applied to account for interactions between different physical effects as well as across multiple length and time scales.

The main focus areas include:

• Coupled thermo-mechanical simulations 
• Cure-dependent material behavior 
• Hygro-thermo-mechanical material behavior 
• Process-induced stresses and deformations 
• Multi-material and interface effects 
• Multi-scale simulation from material to system level 

These multi-physics and multi-scale approaches enable a realistic assessment of complex materials and components, as well as improved prediction of performance and reliability. By combining different scales and physical effects, both local phenomena and global component behavior can be accurately captured.

Manufacturing processes and resulting material states strongly influence the performance of polymer-based components. Process-induced effects such as residual stresses, deformations, or local material variations significantly affect component behavior and lifetime.

At PCCL, integrated simulation methodologies are developed to link manufacturing processes with component performance. Process simulation, structural mechanics, and reliability assessment are combined to systematically analyze the influence of manufacturing processes on the final component performance.

Automated simulation workflows enable extensive parameter studies and sensitivity analyses to identify critical influencing factors and optimize them efficiently. In addition to well-established deterministic optimization approaches, machine learning and data-driven methods are increasingly applied to replace or complement computationally expensive simulations using surrogate models. This enables efficient large-scale parameter studies, accelerated design optimization, and probabilistic reliability analyses.

The main focus areas include:

• Simulation of manufacturing processes 
• Analysis of process-to-performance relationships 
• Sensitivity analyses and design optimization 
• Automated simulation workflows 
• Machine-learning-based surrogate modeling 
• Data-driven optimization 

This integrated and data-driven optimization approach enables targeted improvements in materials, designs, and manufacturing processes, while significantly reducing development time and prototype effort.

PCCL develops tailored simulation solutions for specific industrial applications. By combining physics-based modeling, automated simulation methods, and application-oriented validation, real-world engineering challenges can be addressed efficiently.

Typical application areas include:

• Microelectronics
• Battery systems and energy storage 
• Photovoltaic modules and components 
• Polymer-based medical technology 

A particular focus is placed on the automation of simulation routines and the development of parameterized models. This enables efficient execution of variant studies, sensitivity analyses, and design optimizations.

These application-specific simulation solutions enable direct industrial implementation, shorten development cycles, and contribute to the development of high-performance and reliable polymer-based products.