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Item type:Publication, Access status: with files , Resilience, sustainability and Industry 4.0 in PPC: A survey of german manufacturers(publish-Ing., 2026-09-01); ; ; ; Manufacturing companies face increasing demands related to supply-chain resilience, sustainability, and digitalisation, creating new requirements for production planning and control (PPC). This paper presents selected findings from the 2024 PPC Report, a recurring survey of German manufacturing companies conducted by four production technology research institutes. Based on 39 completed questionnaires, the study provides a descriptive benchmarking snapshot of resilience, sustainability practices, and Industry 4.0 adoption and complements descriptive results with selected bivariate subgroup comparisons. The findings show that most respondents expect their production systems to be similarly or better positioned for future crises than during past disruptions, while no clear relationship with company size emerges. Respondents reporting the use of risk-management approaches predominantly assess their future resilience as stable or improved. Material and energy efficiency are among the most frequently selected measures for reducing the carbon footprint of production, while the reported composition of energy-data practices differs across company-size groups, with operational uses accounting for larger shares among medium-sized and large companies. Regarding Industry 4.0, advanced integration remains limited: mostly or fully connected OPC UA implementations and Asset Administration Shell adoption are still uncommon. An analysis of software use in commissioning further reveals descriptive differences between implementation approaches. Across the three areas, the findings highlight the growing importance of combining organisational practices, data availability, and system integration within PPC. Given the exploratory design and small sample, the results should be interpreted as a benchmarking snapshot rather than as representative of German manufacturing as a whole.Publicationtype: Journal Article36 9 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Analysing sequencing in make-to-order companiesSufficient order sequencing configuration and implementation are key to achieving high schedule reliability and, consequently, customer satisfaction in make-to-order companies. This paper proposes a multi-method analysis approach to evaluate sequencing in make-to-order production. The approach consists of two phases: (1) data collection, including interviews, an order-level feedback data analysis, the value stream analysis for make-to-order companies, and process observations, and (2) an interpretative analysis to identify configuration and implementation deficits. As part of the feedback data analysis, a rank-based correlation analysis is introduced and validated using simulation data, providing visually accessible insights into sequencing implementation through characteristic correlation patterns. The multi-method analysis is validated in a case study, demonstrating its practical applicability and the benefits of integrating multiple analytical methods.Publicationtype: Conference Paper31 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Line balancing for energy efficiency in production: a qualitative and quantitative literature analysis(2025-04-21); ; ; ; In the rapidly evolving landscape of hyperconnected digital manufacturing, known as Industry 4.0, achieving energy efficiency has become a critical priority. As manufacturers worldwide strive to meet sustainable development goals, enhancing energy efficiency is essential for reducing operational costs and minimizing environmental impact. In this context, line balancing is a pivotal strategy for optimizing energy consumption within manufacturing processes. This study presents a comprehensive literature review on the Line Balancing Problems (LBPs) focused on enhancing energy efficiency. The review aims to provide a holistic understanding of this domain by examining past, present, and future trends. A systematic literature review is conducted using the PRISMA method, incorporating both qualitative and quantitative analyses. The quantitative analysis identifies prevalent patterns and emerging trends in energy efficiency optimization within the LBP domain. Concurrently, the qualitative analysis explores various aspects of existing studies, including configurations of lines, managerial considerations, objectives, solution methodologies, and real-world applications. This review synthesizes current knowledge and highlights potential avenues for future research, underlining the importance of energy efficiency in driving sustainable practices in Industry 4.0 and the emerging Industry 5.0 paradigm.Publicationtype: Journal Article58 49 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Development of a multi-method analysis for make-to-order manufacturersFor make-to-order manufacturing, short delivery times and high delivery reliability are crucial logistical objectives. There are various well-known approaches for identifying the causes of missed logistical objectives, such as the Value Stream Analysis and the Feedback Data Analysis. Depending on their characteristics, the methods have shortcomings, such as a high dependency on the data quality or the exclusive consideration of information from the day of recording. A combined approach is intended to balance out the weaknesses and enable analysers to identify potentials for improving the logistical performance. This paper presents a multi-method analysis approach implemented in a Web App and applies it in a case study.Publicationtype: Conference Paper53 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Multi-objective optimization of transfer line balancing problem considering cycle time and energy expenditure(2024-05); ; ; Burmeister, CarstenThe transfer lines are among highly complex automated production systems that manufacture a large volume of identical or similar products with high demand. Recently, the design of environmentally friendly production systems has become the focus of more and more enterprises as one of the sustainable manufacturing strategies. In light of the recent energy-efficient manufacturing trends, this paper investigates the transfer line balancing problem (TLBP), considering both efficiency and energy aspects. The problem arises in the automated transfer lines equipped with dedicated machining centers and automated material handling systems, producing a large volume of specific products. The operations are performed at machines by realizing particular processing requirements, including machining features, inclusions, and exclusions considerations. The objectives to be minimized are the cycle time and the total energy consumption. The latter objective consists of machines’ operating and non-operating energy costs. The problem is first formulated as a mixed-integer linear programming model. Due to the problem’s complexity, an efficient multi-objective optimization algorithm based on the non-dominated sorting genetic algorithm (NSGA-II) is also proposed. The performance of the proposed algorithm is compared with the e-constraint method in terms of the Pareto-front metrics while solving various test problems and a case study. The computational results show the effectiveness of the proposed algorithm in dealing with the TLBP.Publicationtype: Conference Paper42 23 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , A review on sensor‐integrating machine elements(Wiley, 2024-01-28); ; ; 38 26