Investigating Sustainability Dimensions in Selected Intralogistics and Production Processes

In order to investigate the impact of economic, environmental and social factors on the industrial environment, it is important to integrate sustainability dimensions into the planning and design of intralogistics and production processes. In the context of a primarily technology-driven Industry 4.0 and a more sustainable and human-centered Industry 5.0, this dissertation examines the benefits and applications of quantitative approaches in data-driven decision-making processes. It shows how different approaches can increase adaptability, optimize the use of resources and improve working conditions in intralogistics and production processes. Sustainability is not viewed as an isolated goal, but as an integral dimension that influences economic, environmental, social, and operational decisions. By addressing operational planning and design, a holistic perspective is developed on how sustainable, human-centered principles and resilience can transform industrial systems beyond improvements. This cumulative dissertation comprises seven contributions to the scientific literature written between 2019 and 2025. Four of these contributions were published in peer-reviewed scientific journals and two contributions were published in peer-reviewed conference proceedings. In addition, one working paper is included that had not yet been published at the time the dissertation was completed. The contributions address in different ways the overarching themes of economic growth, environmental sustainability, social responsibility, as well as human-centricity and resilience, in the application areas of intralogistics and production. The seven contributions contained in this cumulative dissertation contribute to three thematic research streams. The first stream deals with smart lighting systems and their relevance for energy-efficient and flexible intralogistics environments. The second stream examines demand response programs, in particular incentive-based programs, to regulate electricity consumption in production scheduling. The third stream is dedicated to planning-related challenges in production scheduling in the context of demographic change, particularly regarding an aging workforce. Despite the heterogeneity of the three research streams in terms of objectives and methodological approaches, they are conceptually linked by the overarching principle of a sustainable, human-centric and resilient approach. The first research stream focuses on smart lighting systems in intralogistics and comprises the first three contributions. The first contribution introduces the concept and practical relevance of smart lighting systems, showing their potential to reduce energy consumption and improve worker well-being. The second contribution conducts a systematic literature review on smart lighting systems and identifies a research gap in industrial applications. It integrates scientific literature with expert knowledge based on expert workshops to formulate hypotheses for future research using the example of order picking in warehouses. Based on the findings of the second contribution, the third contribution develops a simulation model to evaluate the operational strategies of smart lighting systems in warehouse environments. The results, validated by expert workshops and a case study, demonstrate significant cost and energy savings as well as practical implications for the implementation of smart lighting systems. The second stream of research comprises contributions four to six and examines incentive-based programs and their integration into and impact on production scheduling. The fourth contribution presents a bi-objective job-shop scheduling model with variable machine speeds that aims to balance energy efficiency and scheduling performance under incentive-based programs. Based on this model, the fifth contribution develops a genetic algorithm to approximate Pareto-optimal solutions for large datasets and provides insights into the complex interactions between production flexibility and different incentive-based programs. The sixth contribution extends the analysis by investigating how changes in the production schedule induced by incentive-based programs affect downstream supply chain performance. A simulation-based approach reveals the impact on inventory policies and highlights the trade-offs between energy flexibility and supply reliability. The third stream of research comprises contribution seven and addresses demographic change in production planning, with a focus on an aging workforce. The seventh contribution presents a systematic literature review on age-appropriate production planning and identifies research gaps related to the assignment of older workers in sequential production processes. It develops a practical production planning model that incorporates worker age and experience into scheduling decisions. This contribution demonstrates how considering employee diversity can lead to more inclusive and sustainable production systems.