Data-driven and Knowledge-based Engineering for Circular Polymer Production Processes

The global challenge of countering climate change, along with its negative environmental impacts, is creating an urgent need for more sustainability-centered solutions in production and society. Implementing a Circular Economy is a key strategy to enhance environmental sustainability and reduce the environmental impact, particularly in the production sector, which is a major contributor to the global environmental impact. Circular Production applies principles of the Circular Economy to production. One focus material is polymers, as they are widely used in industry and have high potential for enhancing environmental sustainability. Nevertheless, the implementation of circular (polymer) production processes is still described as slow. Data-driven engineering approaches offer significant potential to accelerate the implementation and improve circular production processes, but certain challenges, such as the lack of standardized tools, must be overcome. In addition, an effective management of information and knowledge plays a crucial role. Therefore, knowledge-based engineering approaches offer significant potential to enhance the potential of data-driven approaches for circular production. The developed concept integrates data-driven and knowledge-based engineering approaches to implement and improve circular polymer production processes. The key focus is to provide a holistic guideline for data analysis that supports the knowledge gain of the stakeholder groups, facilitated by the integration of knowledge-based approaches. The concept encompasses a process and a life cycle perspective, supporting applications for various stakeholder groups. With the implementation of this concept, stakeholder groups are empowered to derive recommendations for actions, enabling them to make informed decisions and enhance the circular processes. The overall focus is on the knowledge gained by the stakeholder groups. To ensure knowledge gain, data-driven approaches are integrated. A holistic guideline for their application, from defining the data input to evaluating the modeling results, is given. The guideline, based on CPPS and CRISP-DM, is modular and can be adapted to the requirements of each use case. It supports achieving a high level of transparency for the process and life cycle perspective, benefiting from the knowledge gained. To maximize the knowledge gain and facilitate the structured acquisition, storage, retrieval, and distribution of knowledge, knowledge-based approaches from Knowledge Engineering and Knowledge Management, such as CommonKADS and knowledge warehouse. The concept provides a modular toolbox and a procedure model to enable a simple and flexible application to various circular production processes. The toolbox facilitates decision support for different stakeholders. A prototypical implementation of the concept as a web-based application is developed using the Python programming language. It demonstrates the concept in an easy-to-use user interface. The use cases focus on the two perspectives integrated. Their focus is on injection molding processes using polymer materials. The analysis goals focus on different types of materials (PP-GF and PP-TD), different material qualities, different material origins, and different shares of recyclate. Furthermore, the influences of process parameters and various aging conditions (adapted from the requirements for automotive parts) are analyzed. The applicability of the concept is validated, and the potential knowledge gain is demonstrated.