Developing Sustainable Concepts for the Textile Industry Using Production Simulation – A Problem-Based Learning Approach

Practice Paper Recommended citation: Guerne, M. G., Müller, K., Block, B.-M., & Heger, J. (2025). Developing Sustainable Concepts for the Textile Industry Using Production Simulation – A Problem-Based Learning Approach. In Kangaslampi, R., Langie, G., Järvinen, H.-M., & Nagy, B. (Eds.), SEFI 53rd Annual Conference. European Society for Engineering Education (SEFI), Tampere, Finland. DOI: 10.5281/zenodo.17631230. This Conference Paper is brought to you for open access by the 53rd Annual Conference of the European Society for Engineering Education (SEFI) at Tampere University in Tampere, Finland. This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License. DEVELOPING SUSTAINABLE CONCEPTS FOR THE TEXTILE INDUSTRY USING PRODUCTION SIMULATION – A PROBLEMBASED LEARNING APPROACH M. G. Guernea, 1 , K. Müller a, B.-MBlock a, J. Hegera aLeuphana University, Lueneburg, Germany Conference Key Areas: Sustainability and society in engineering, Digital tools and AI in engineering education Keywords: Problem-based Learning, Simulation, Sustainable Engineering, Textile Industry, Engineering Education ABSTRACT This practice paper describes the implementation of a problembased learning approach that deals with the multifaceted problems of the textile industry. Therefore, an interdisciplinary module was implemented that deals with the topics of the textile value chain, sustainability and production simulation. The students develop solutions to increase sustainability in the textile industry and use simulation software to test their ideas. To ensure successful student outcomes and to respond to the individual programming questions of the students, constructive feedback and dialogue were key elements of the seminar. The seminar is developed using the design-based research approach. Within the scope of this paper, the first implementation of the designed learning approach is described and reviewed based on student and teacher feedback. 1 INTRODUCTION The textile industry is one of the oldest and most optimized industries in the world and continues to be an important economic factor (Feldbaumer et al., 2023; Wünsche et al., 2025). The textile industry generates an annual turnover of hundreds of billions of dollars and employs millions of people (Wünsche et al., 2025). However, the textile industry causes many environmental and social problems along its supply chain: excessive resource consumption, environmental pollution and often precarious working conditions are just some of the negative side effects (Stamm et al., 2019; Wünsche et al., 2025). 1 M. G. Guerne [email protected] It is estimated that the textile industry is responsible for 20 % of global water pollution (European Parliament, 2024). Every year, 1.7 billion tons of CO2 are emitted by the sector (WWF, n.d.). For every ton of finished product produced, 200350 m3 of contaminated wastewater is generated (Stamm et al., 2019). The identified challenges in the textile industry highlight both an urgent need for action and significant potential for innovation. Therefore, an elective module was designed and implemented. Unlike traditional teaching methods that mainly rely on theoretical instruction, this module introduces an innovative approach by engaging students with real-world problems. By integrating programming skills using AnyLogic simulation software, the module fosters practical, interdisciplinary problem-solving that prepares students for complex challenges. The pedagogical approach includes problem-based learning (PBL), which is particularly characterized by learner-directed and self-motivated student learning. The seminar thus contributes to sustainable education. Moreover, the seminar addresses and promotes SDG 6, 8, 12 and 13 by: - making the textile supply chain more environmentally friendly and offering consumers more sustainable products (SDG 12), - fair working conditions and fair wages (SDG 8), - developing concepts on how to use water resources more efficiently and treat wastewater in a way that the surrounding ecosystem is not polluted (SDG 6). The module aims at students from all degree programs and therefore intends to strengthen interdisciplinary teamwork, prevent silo thinking and promote holistic approaches to solutions. An original perspective and the acquisition of important skills will be promoted by analyzing problems using production simulation. To this end, the methodology, design and implementation of the seminar will be introduced in sections 2 and 3. Two solutions developed by students for a more sustainable textile industry are presented as examples. In section 4, the feedback and potential for improvement of the intervention will be discussed. Section 5 summarizes this work and gives an outlook for further application of the designed seminar. 2 DESIGN-BASED RESEARCH APPROACH The methodological approach chosen for the design and implementation of the module was Design-Based Research (DBR) as outlined by McKenney and Reeves (2013). This approach aims to generate research-based insights that improve both theoretical understanding and pedagogical practice (McKenney & Reeves, 2013; Kelly, 2013). The process consists of three interrelated phases: Analysis, Design and Evaluation. These phases are interdependent and require the application of specific methodological strategies. Continuous feedback loops allow for continuous refinement and adaptation (McKenney & Reeves, 2013). In the analysis phase, the problem is analysed and defined (McKenney & Reeves, 2013). The authors identified a gap in the curriculum at Leuphana University. During lectures, students were asked about their interest in a module that uses simulation to address problems in the textile industry and the responses were positive. The aim of the seminar is to provide both engineering and non-engineering students with interdisciplinary knowledge about the textile industry. In this way, non-engineers should also be introduced to the methods and possibilities of engineering practice. In the design phase of the DBR model, a concept for an educational intervention or a learning environment is created, implemented and tested. A teaching concept on textile industry is developed. The aim of the module is for students to develop and simulate solutions to problems in the textile industry. To achieve this, students should learn how to use specific software tools and familiarise themselves with the PBL approach. Barrows (1986) defines PBL as a learning method that uses real-life problems as the basis for acquiring knowledge. Solving these problems helps students build competences and skills that are relevant to professional practice. PBL has several advantages: It increases student motivation by positioning them as active participants in the learning process, it enables student-directed learning, it fosters teamwork and improves collaboration skills and it promotes a studentcentered approach that transforms learners from passive recipients to active, responsible and autonomous participants (Barrows, 1986; Amol, 2020; Williams, 2016). This innovative, interdisciplinary seminar has five main learning goals, guided by the six levels of Bloom’s Taxonomy (Marzano & Kendall, 2007): Knowledge, Comprehension, Application, Analysis, Synthesis, and Evaluation: 1) Acquiring knowledge along the textile value chain, production and logistics simulation, 2) Addressing problems along the textile value chain, 3) Development of sustainable and future-proof production concepts, 4) Programming and analyzing with AnyLogic software to model and simulate the developed concepts. 5) Evaluation the developed concept Students are prepared for PBL using the Case Method, in which they receive a case study and conduct research in preparation for classroom discussion. This teacherled instruction is followed by opportunities for students to identify own problems and engage in independent, problem-based work. This includes active exploration and evaluation of the problem, supported by the teacher’s mentoring (Stentoft, 2019). Finally, in the evaluation phase, the implementation of the module is analysed, assessed, and refined. Student feedback is collected through a post-course survey. 3 CONTEXT AND PRACTICAL WORK 3.1 Context of the Seminar This interdisciplinary seminar targets students from all disciplines interested in sustainable and future-proof textile production, with a particular focus on production and logistics simulation. While it is designed primarily for engineering students, the seminar also aims to introduce non-engineers to fundamental engineering methods, especially in the context of digitalization and sustainability. The scope of the seminar is summarized in Fig.1. Fig. 1. Scope of the interdisciplinary seminar approach. The seminar provides students with a comprehensive overview of the textile value chain, from raw material extraction to the final product, emphasizing material properties, production processes, and sustainability issues such as the EU textile strategy. Key methods include lectures, a flipped classroom approach and a material quiz. Students are exposed to real-world textile supply chains and then conduct independent research on the supply chains of selected case studies. This research becomes the foundation for a creativity workshop where students develop innovative concepts for improving the sustainability of these supply chains. Students are introduced to production and logistics simulation. They analyse relevant research studies and gain hands-on experience with AnyLogic through two official tutorials (AnyLogic, 2025a; AnyLogic, 2025b). Since all students have completed a basic programming course (DATAx) in Python, the seminar does not cover general programming, but it does include a theoretical and practical introduction to the AnyLogic simulation environment. Group projects form the core of the practical phase. Supported by individual coaching, students develop their own simulation models based on their redesigned supply chains. The seminar concludes with a 15minute presentation and a 15-page written report per group. This seminar design prepares students for future work in sustainability or systems thinking. The students learn to program with a new software tool. As we now live in a digitalized world, programming is a central component of modern engineering education. Furthermore, the students reflect on the existing approaches in textile supply chains and rethink these by developing alternatives. This procedure can easily be transferred to other industries and supply chains. 3.2 Practical Implementation The seminar was first implemented in the summer term of 2024 as part of the Leuphana Bachelor complementary studies program. Participation was voluntary and limited to 35 students. In its first run, 35 students enrolled and 21 successfully completed the seminar, resulting in a 40 % dropout rate. Participants represented diverse fields such as engineering, sustainability studies, international business, digital media, information systems, and cultural studies. The seminar followed a hybrid schedule: weekly 90-minute sessions for theoretical grounding and coaching, and a two-day block seminar. The first day of the block seminar focuses on sustainability in the textile sector, while the second concentrates on simulation concepts and practical training using AnyLogic. AnyLogic software was selected due to its unique integration of discrete event, agent-based, and system dynamics modelling within one software. Alternatives for the simulation of production and logistics processes could be MATLAB/Simulink, Siemens Plant Simulation, Simio or Arena. The reasons why we decided to use AnyLogic are especially the Personal Learning Edition, which is free of charge and can easily be installed and used on a computer, as it does not have any special hardware requirements. One limitation of AnyLogic software is that it is java based. Users unfamiliar with Java may face a steep learning curve (AnyLogic, 2025a). However, due to the possibility to use Large Language Models for programming support and the AnyLogic Help website, it is possible for the students to deal with this limitation. To adapt our concept to other classes, we recommend the tutorials on the AnyLogic website (AnyLogic, 2025b). After the block seminar the students work in groups on their projects, while the weekly seminar serves as individual work phase or coaching session with constructive feedback and dialogue. 3.3 Exemplary Student Work of the Problem-Based-Projects The variety of approaches developed exceeded our expectations. Two selected approaches will be introduced shortly in the following. One approach examined the wool washing process as part of the wool yarn production. This process is very energy intensive and consumes a lot of water. The student group built a simulation model of the current wool washing process and a model of the innovative approach using ultrasound described by Bahtiyari & Duran (2013). Within a simulation study of both processes they compared the energy and water consumption as well as the washing time for both processes. The results of the simulative study show, that the energy consumption can be reduced by 19.3 %, while the water consumption and the washing time can even be reduced by 40 %. A section of the simulation models in AnyLogic, showing the overview of the measured key performance indicators is shown in Fig. 2. Another approach analyses the potential reduction of CO2 emission in silk trade through bioreactors. This approach claims that silk production currently has high CO2 emissions due to long transportation routes. The reason for the long transportation routes is the geographical separation of production and consumer markets. Furthermore, animal suffering in traditional silk production poses a significant ethical challenge. Thousands of silkworms die during the cocoon boiling process to produce silk (Karthik & Rathinamoorthy, 2017). The approach to solve these problems is to produce silk in bioreactors. These can produce silk close to the consumers to reduce the transport length and prevent animal suffering of the silkworms. Therefore, a simulation model of both transport routes is designed and a simulation study is done. This simulation study shows the great potential to reduce the CO2 emissions due to transport ways by 82 % when using bioreactors for silk production near to the customer. Fig. 2. Example cut-out from the simulation model showing the key performance indicators to examine the different wool washing processes modelled with AnyLogic. 4 RESULTS AND INSIGHTS 4.1 Participant Feedback In the final teaching evaluation, 11 out of 21 students (52,38 %) took part. The evaluation shows that the students are overall very satisfied with the seminar and their knowledge gain. On a 5-point Likert scale (1 = strongly disagree; 5 = strongly agree), they rated the course with an average score of 4.1 (N = 11). It is particularly noteworthy that many students had little prior knowledge about textile materials, their environmental impact and their influence on climate change before the seminar. They rated their increase in knowledge as 4.0. The question ‘The course encourages me to think and reflect further on the topic’ was answered with 4.4. The thematic focus of the seminar was particularly positively emphasised. Five participants stressed that it was an extremely relevant and interesting topic on which they would like to deepen their specialist knowledge. Two students highlighted the link to sustainability aspects and the encouragement to think critically about supply chains and production processes. One person emphasised the consideration of different perspectives. Two other students appreciated the didactic approach and the independent work. In addition, five students emphasised the pleasant working atmosphere, which they found to be open, friendly and relaxed. They recognised the enthusiasm of the teaching staff and described their own work as creative. The students' suggestions for improvement related in particular to the use of the AnyLogic programme. Five students wished for a more comprehensive introduction to the functions of the software in order to gain a better understanding of its possibilities. Three participants suggested formulating the expectations and learning objectives of the seminar more clearly at the beginning. Two students requested more resources, for example on data research in the textile sector or alternative programmes to AnyLogic. One person suggested additional dates for individual coaching sessions and consultation hours in order to better understand also the progress of the other groups. 4.2 Teaching Enhancement and Improvement Suggestions As lecturers, we scheduled about 20 minutes after each unit to reflect on the session. This was done particularly in line with the design-based research approach: by continuously evaluating and reflecting on the individual components, we were able to take student feedback into account promptly and adapt the seminar structure at short notice (McKenney & Reeves, 2013). One specific improvement approach relates to the first day of the weekend seminar. On this day, an introduction to the topic of sustainability and a definition of the term were given. The participants then analyzed the problems of the textile industry. The lecturers presented various textile labels. In addition, the students worked on the supply chain law and the EU textile strategy and presented their findings. In a future implementation, we would adapt the sequence: The students should first research various labels in small groups and present their findings before the teachers take over the classification as well as the topics of supply chain law and EU textile strategy. It would also be desirable to incorporate a game-based approach on this day in order to convey the topic of sustainability in the textile industry even more vividly. On the second day of the weekend seminar, it became apparent that both the individual download of the software and the internet connection at the university were problematic. To avoid technical difficulties, students should download the software in advance. An optimal solution would be to provide a computer room in which AnyLogic is already pre-installed on all computers. To summarize, the following recommendations can be made for future implementation to make the seminar even more structured, interactive and efficient: - Clearer communication of learning objectives: The expectations and objectives of the seminar should be made even clearer at the beginning. - Greater support for AnyLogic: A more detailed introduction to the functions of the software would help students to better understand the possibilities of the software. In addition, the software should be downloaded in advance or a computer room should be used for preparation. - Provide more interactive elements: A game-based approach to the topic could further increase student motivation. 5 CONCLUSION This practice paper describes the successful implementation of a PBL Module to familiarize students with the complex challenges of the textile industry. The interdisciplinary approach of the course combined with production simulation enabled students to develop innovative and sustainability-oriented solutions. Feedback from participants highlights the relevance of the topic, the effectiveness of the independent project work and the supportive learning environment. However, improvements in the introduction to AnyLogic, clearer communication of learning objectives and additional interactive elements could further enhance the seminar experience. A clear goal for future iterations should also be to reduce the drop-out rate of 40%. The findings will be integrated into future sessions to optimize student engagement and learning outcomes. At least two more iterations of the seminar are planned, and the concept will be continuously optimized. The approach helps to raise awareness, gain new skills and promote innovation for a more sustainable textile industry and future. 6 ACKNOWLEDGEMENTS The authors thank all students and participants of the seminar for their engagement, creativity, and valuable contributions to developing sustainable solutions. Thanks in advance to the unknown reviewers for their comments in the early phase of this paper. REFERENCES Adámate, A. C., & Mane, S. U. (2020). PBL based Teaching-learning Strategy for Inculcating Research Aptitude in CS/IT Students. Journal of Engineering Education Transformations, 33 (Special issue), 585. https://doi.org/10.16920/jeet/2020/v33i0/150125 AnyLogic. (2025a, March 19). AnyLogic: Simulation Modeling Software Tools & Solutions for Business. https://www.anylogic.com/ AnyLogic. (2025b, March 19). Get started with AnyLogic - AnyLogic Simulation Software. https://www.anylogic.com/getting-started/ Barrows, H. S. (1986). A taxonomy of problem-based learning methods. Medical Education, 20(6), 481–486. https://doi.org/10.1111/j.1365-2923.1986.tb01386.x Bahtiyari, M. I., & Duran, K. (2013). A study on the usability of ultrasound in scouring of raw wool. Journal Of Cleaner Production, 41, 283–290. https://doi.org/10.1016/j.jclepro.2012.09.009 European Parliament. (2024, March). The impact of textile production and waste on the environment (infographics). https://www.europarl.europa.eu/topics/en/article/20201208STO93327/the-impact-oftextile-production-and-waste-on-the-environment-infographics Feldbaumer, M., Granzer-Sudra, K., & Ganglberger, E. (2023). Sekundärrohstoffe für die österreichische Textilindustrie. Bundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation und Technologie. Karthik, T., & Rathinamoorthy, R. (2017). Sustainable silk production and its environmental impact. Textile Environmental Studies, 12(1), 45-58. https://doi.org/10.1016/B978-0-08-102041-8.00006-8 Kelly, A. E. (2013). Design-Based Research in Engineering Education. In A. Johri & B. M. Olds (Eds.), The Cambridge handbook of engineering education research (pp. 497–518). Cambridge University Press. Marzano, R. J., & Kendall, J. S. (2007). The New Taxonomy of Educational Objectives (2nd ed.). Corwin Press