Article
Engineering, Manufacturing
O. Damm, M. Bezuidenhout, E. Uheida, L. Dicks, W. Hadasha, D. Hagedorn-Hansen
Summary: This study investigates the use of microorganisms to substitute mineral oil in metalworking fluids, showing similar or better performance in terms of cutting forces, tool wear, and workpiece surface finish. The findings provide early evidence for the potential to reduce or eliminate mineral oil use in metalworking fluids, leading to benefits in process efficiency, health and safety, and sustainability.
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY
(2021)
Article
Engineering, Industrial
Juan De Anton, Felix Villafanez, David Poza, Adolfo Lopez-Paredes
Summary: This paper provides a framework to formalize the production planning problem in additive manufacturing (AM) based on an analysis of existing literature. A coding strategy is developed and applied to review relevant works proposing models for the production planning of AM systems.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Review
Chemistry, Multidisciplinary
Brook S. Kennedy, Jonathan B. Boreyko
Summary: Freshwater scarcity is a critical global challenge, and atmospheric water harvesting (AWH) shows great promise for addressing this problem. Mesh-based fog harvesters have gained attention for their passive qualities, but their water yield has only developed modestly. Scientific understanding of passive fog collection processes is advanced, but practical application at scale still faces challenges. However, with advancements in manufacturing technology, particularly in mesh design, there are opportunities for further development.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Engineering, Industrial
Beatriz Flamia Azevedo, Ruben Montano-Vega, M. Leonilde R. Varela, Ana Pereira
Summary: This study developed a multi-objective optimization model to solve the production scheduling problem using various performance measures and algorithms. The results demonstrated the effectiveness of the proposed approach in improving efficiency and robustness of production scheduling, and the cluster analysis provided decision support.
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING COMPUTATIONS
(2022)
Reprint
Engineering, Manufacturing
Berend Denkena, Marc-Andre Dittrich, Siebo Stamm, Marcel Wichmann, Soren Wilmsmeier
Summary: The transfer of experience-based knowledge and the flexibility and adaptability of biological systems have similarities in the context of production technology. By applying biological mechanisms to digital production, a more flexible, learning, and self-optimizing production can be achieved. The concept of Gentelligence integrates the genetic and intelligent properties of technical components, leading to innovative production systems that enhance efficiency.
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Young Hoon Lee, Seunghoon Lee
Summary: Efficient production planning and scheduling decisions are crucial in the semiconductor industry to improve manufacturing productivity, ensuring that scheduling can execute the production plan to avoid failures. This study employs deep reinforcement learning to optimize scheduling processes within production plans, outperforming other scheduling methods in diverse cases with a novel state, action, and reward combination.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Materials Science, Multidisciplinary
Stephen Daynes, Stefanie Feih
Summary: The use of functionally graded lattice structures in topology optimization can effectively reduce deformation in statically loaded structures and solve problems with multiple load cases. The bio-inspired design approach leads to lattice topologies resembling those found in bones. While the optimized lattice structures may be 12% less stiff than traditional approaches, they excel in multifunctional applications such as heat transfer and eliminate the need for support structures in additive manufacturing.
MATERIALS & DESIGN
(2022)
Article
Engineering, Industrial
Milad Elyasi, Basak Altan, Ali Ekici, Okan Orsan Ozener, Ihsan Yanikoglu, Alexandre Dolgui
Summary: This paper examines the impact of the global crisis on supply chain resilience and suggests the implementation of flexible/hybrid manufacturing systems as a viable strategy. Using Vestel Electronics as a case study, the research proposes a flexible/hybrid manufacturing production setup to address uncertain demand. By employing a scenario-based approach and a heuristic algorithm based on column generation, the optimization model demonstrates effective and cost-efficient solutions.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Automation & Control Systems
Andrey Kutin, Mikhail Turkin, Mikhail Kliuev
Summary: This paper focuses on the technological and operational aspects of manufacturing process planning for multiple values of decision parameters. A discrete parametric model is proposed to generate multiple process plans for a given or proposed production system. An automated platform-based system is built around this model to generate and analyze multiple manufacturing process plans based on the chosen priority criteria.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Computer Science, Interdisciplinary Applications
Zai Mueller-Zhang, Thomas Kuhn, Pablo Oliveira Antonino
Summary: In order to ensure production efficiency, it is essential to have an adequate scheduling system capable of managing diverse process flows and handling unforseen changes. This paper presents an approach leveraging Digital Twins (DTs) and Deep-Q-Learning to perform integrated process planning and scheduling for service-based production.
COMPUTERS IN INDUSTRY
(2023)
Review
Materials Science, Multidisciplinary
Zhao-jun Xu, Zhong Zheng, Xiao-qiang Gao
Summary: Research has been conducted on operation optimization of steel production, however, current techniques are often found to be independent and unsystematic. Future work should focus on integrating multiple technologies and disciplines to optimize the steel manufacturing process.
INTERNATIONAL JOURNAL OF MINERALS METALLURGY AND MATERIALS
(2021)
Article
Engineering, Industrial
Mingxing Li, Ming Li, Haoran Ding, Shiquan Ling, George Q. Huang
Summary: This paper discusses the issue of PSE decision mechanism in the context of Industry 4.0 and proposes the Graduation inspired Synchronization (GiSync) framework. By combining advanced technology data collection with management philosophy, GiSync enables real-time, flexible, and resilient decision-making in the Industry 4.0 environment, with better performance in statistical indicators.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Engineering, Industrial
Yujie Ma, Gang Du, Yingying Zhang
Summary: This paper introduces a dynamic hierarchical collaborative optimization (DHCO) mechanism that optimizes process planning and production scheduling decisions in a platform-based manufacturing environment. A bilevel mixed 0-1 nonlinear programming model is used for solving, with a nested genetic algorithm (NGA) employed. A case study demonstrates the feasibility and benefits of integrating crowdsourcing strategies into process planning activities for enhancing platform competitiveness.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Engineering, Industrial
Behdin Vahedi-Nouri, Reza Tavakkoli-Moghaddam, Zdenek Hanzalek, Alexandre Dolgui
Summary: This paper explores an integrated production scheduling and workforce planning problem in a Reconfigurable Manufacturing System (RMS) using reconfigurable machines and human-robot collaboration. A new Mixed-Integer Linear Programming (MILP) model and an efficient Constraint Programming (CP) model are developed to solve the problem. Computational experiments show the superiority of the CP model over the MILP model in smaller instances and its ability to find high-quality solutions for larger instances within a reasonable computation time. It provides recommendations for managers dealing with this complex problem.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Nanoscience & Nanotechnology
Ze Wang, Hanliang Ding, Delei Liu, Conghao Xu, Bo Li, Shichao Niu, Jian Li, Linpeng Liu, Jie Zhao, Junqiu Zhang, Zhengzhi Mu, Zhiwu Han, Luquan Ren
Summary: This work presents a novel large-scale flexible antireflection film inspired by cicada wings, which successfully addresses the challenge of consistency between artificial and biological structures, demonstrating excellent antireflection performance. The technology holds great promise for applications in the photovoltaic industry, optical devices, and flexible displays.
ACS APPLIED MATERIALS & INTERFACES
(2021)
Article
Engineering, Manufacturing
P. Kuhlemann, B. Denkena, T. Grove
Summary: Current research demonstrates that the mechanical surface-strengthening process of deeprolling is effective in improving the strength and life span of highly stressed components. Adjusting the process temperature during deep-rolling can further increase the mechanical life span, especially in soft machining operations where higher degrees of plastic deformation are induced in the subsurface.
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY
(2021)
Article
Engineering, Industrial
Berend Denkena, Alexander Kroedel, Arne Muecke, Lars Ellersiek
Summary: Surface quality is crucial in 5-axis ball end milling for determining component performance. This paper introduces a new method to predict surface defects, allowing for the selection of suitable process parameters without extensive experimental efforts.
CIRP ANNALS-MANUFACTURING TECHNOLOGY
(2021)
Article
Engineering, Manufacturing
Berend Denkena, Fritz Schinkel, Jonathan Pirnay, Soren Wilmsmeier
Summary: This paper introduces a new method for process-parallel Flexible Job Shop Scheduling based on quantum computing optimization, showcasing its good performance and practicality through a scientific benchmark and application to a real use-case. A managerial insight demonstrates how this approach can be integrated into existing production planning and control IT infrastructure.
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY
(2021)
Review
Engineering, Manufacturing
Berend Denkena, Benjamin Bergmann, Alexander Schmidt
Summary: This study investigates the capability of sensor fusion based on principal component analysis to monitor preload loss of single nut ball screws, by studying features of different preload levels of the ball screw through selecting different ball diameters. The results show that this method can reliably detect preload levels.
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY
(2021)
Article
Engineering, Industrial
Berend Denkena, Patrick Ahlborn
Summary: This paper presents a novel linear-rotary direct drive for machine tools, which combines linear and rotary movement in one drive to enhance the overall dynamics of the machine and reduce installation space.
CIRP ANNALS-MANUFACTURING TECHNOLOGY
(2022)
Article
Engineering, Industrial
Carolin Kellenbrink, Nicolas Nuebel, Andre Schnabel, Philipp Gilge, Joerg R. Seume, Berend Denkena, Stefan Helber
Summary: This paper presents a cyber-physical system demonstrator for the maintenance, repair, and overhaul (MRO) of high-pressure turbine blades of aircraft engines. By using a virtual layer and a virtual twin, the system handles the variability in damage patterns and achieves individual, flexible, and economically optimized MRO actions. It showcases the combination and innovation of research results from multiple disciplines.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Engineering, Multidisciplinary
Lars Schoenemann, Oltmann Riemer, Bernhard Karpuschewski, Per Schreiber, Heinrich Klemme, Berend Denkena
Summary: The research has found that ultra-precision cutting based on digital surface twins can accurately predict surface features and characteristics, thus supporting the development of tool offset compensation methods and improving productivity.
PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY
(2022)
Article
Engineering, Manufacturing
B. Denkena, A. Kroedel, M. Wilckens
Summary: The use of larger CBN grains in grinding can improve material removal rates for hardened steel components and achieve higher depths of cut. Grinding with coarse grains results in lower process forces, higher residual stress, and rougher surfaces, with minimal wear observed. In some cases, using larger grains can enhance tool performance and allow for higher feed rates.
PRODUCTION ENGINEERING-RESEARCH AND DEVELOPMENT
(2021)
Article
Engineering, Electrical & Electronic
Berend Denkena, Benjamin Bergmann, Matthias Witt
Summary: To achieve increased automation and flexibility in production, it is necessary to monitor component-specific characteristics and evaluate signals highly correlated with process quality. The use of material-specific cutting force improves the sensitivity of confidence limits to process errors, allowing the force-sensitive machine to substitute the dynamometer for process monitoring.
Article
Engineering, Manufacturing
Berend Denkena, Marc-Andre Dittrich, Hai Nam Nguyen, Konrad Bild
Summary: Self-optimizing process planning uses machine learning models to correlate process parameters with surface quality, automatically adjusting optimal parameters to achieve target roughness.
PRODUCTION ENGINEERING-RESEARCH AND DEVELOPMENT
(2021)
Article
Engineering, Manufacturing
Berend Denkena, Bernd-Arno Behrens, Benjamin Bergmann, Malte Stonis, Jens Kruse, Matthias Witt
Summary: This study predicts variations in dimension and cavities during cross-wedge rolling of shafts based on measured tool pressure. Multi-linear regression models are developed to determine the resulting diameters of the shaft shoulder, showing better prediction accuracy than models based on meta-data. The sensor concept for a new cross-wedge rolling machine and the approach for monitoring machining processes of workpieces with dimensional variations are presented for upcoming studies.
PRODUCTION ENGINEERING-RESEARCH AND DEVELOPMENT
(2021)
Article
Engineering, Manufacturing
Berend Denkena, Alexander Kroedel, Steffen Heikebruegge, Kolja Meyer, Philipp Pillkahn
Summary: This study investigates the impact of machining parameters on surface topography after deep rolling, and introduces a novel tool concept to explore the predictability of surface topography for milled specimens. By adjusting parameters gradually, the minimum pressure and lateral displacement conditions were identified to ensure accuracy in predicting surface topography.
PRODUCTION ENGINEERING-RESEARCH AND DEVELOPMENT
(2021)
Article
Engineering, Manufacturing
B. Denkena, O. Pape, A. Kroedel, V. Boss, L. Ellersiek, A. Mucke
Summary: This study presents a dynamic multi-dexel based material removal simulation for additive manufacturing processes, which is able to predict high-resolution surface topography and stable parameters to improve efficiency and accuracy in repair operations.
PRODUCTION ENGINEERING-RESEARCH AND DEVELOPMENT
(2021)
Article
Engineering, Manufacturing
B. Denkena, B. Breidenstein, A. Kroedel, V. Prasanthan
Summary: The requirements for massive high-performance components are constantly increasing, and by joining different materials in one component, these contradictory requirements can be met. The final step of machining in the process chain of manufacturing hybrid components has a decisive influence on the surface and subsurface properties.
PRODUCTION ENGINEERING-RESEARCH AND DEVELOPMENT
(2021)
