Article
Chemistry, Analytical
Long Tian, Jianhui Zhao, Bing Pan, Zhaoyang Wang
Summary: This study introduces a new method for full-field bridge deflection measurement based on off-axis DIC, which determines the scale factors of all points of interest with a spatial straight-line fitting scheme and employs reliability-guided processing and a fast initial parameter estimation strategy for real-time and accurate image-matching analysis. An indoor cantilever beam experiment validated the accuracy of the method, while a field test on a high-speed railway bridge showcased the robustness and practicality of the technique.
Article
Optics
Yehe Liu, Michael W. Jenkins
Summary: This paper demonstrates that using two single-axis scanners can generate a 2D scanning pattern nearly identical to a single-pivot gimbaled scanner through a previously undiscovered simple geometry, thus addressing the limitations of previous complex designs.
Article
Engineering, Mechanical
Dongqian Wang, Lars Penter, Albrecht Haenel, Yang Yang, Steffen Ihlenfeldt
Summary: This paper proposes a complete and practical model for micro-milling process, including dynamic tool deflection and a stability lobe diagram with runoutdependent effect. The study identifies the frequency response function at the tool point using a multi-sections discretization method combined with dynamic tests. The dynamic tool deflection is then developed based on force decomposition and the frequency response function. The interaction between feed per tooth, runout, and dynamic tool deflection is examined, resulting in the proposed stability lobe diagram.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Editorial Material
Multidisciplinary Sciences
Hongkui Zeng, Saskia E. J. de Vries
Summary: Using functional imaging and gene-expression profiling, researchers have measured the activity of transcriptomically defined neurons in live mice. They have identified 35 subtypes of neurons and revealed a gene-expression axis that governs the activity of each subtype.
Review
Computer Science, Interdisciplinary Applications
Melvin Alexis Lara de Leon, Jakub Kolarik, Radek Byrtus, Jiri Koziorek, Petr Zmij, Radek Martinek
Summary: This article reviews and analyzes the approaches utilized for monitoring cutting tool conditions, focusing on the use of Machine Learning and statistical processes. It quantifies the typical signals used by researchers and scientists, such as vibration, cutting force, and temperature, to determine tool degradation and product quality. The article also presents statistical techniques used to cleanse collected data and extract relevant information for prediction and classification purposes.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Engineering, Mechanical
Xing Zhang, Yang Gao, Zhuocheng Guo, Wei Zhang, Jia Yin, Wanhua Zhao
Summary: A physical model-based tool wear and breakage monitoring method is proposed in this paper. The comprehensive feature is extracted from the seven-channel specific cutting force coefficients (SCFCs) through the measurements of milling force, spindle box vibration and driving current for tool wear monitoring. An efficient tool breakage monitoring method is also put forward. The verification results indicate that the proposed method can accurately estimate the cutting status of the tool and provide a research basis for the potential industrial application of tool wear and breakage monitoring technology.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Manufacturing
Bo Peng, Yang Luo, Yuanxin Luo, Ziyong Ma
Summary: Gear roll forming process is an innovative technology for efficient gear manufacturing, while the proposed elliptical tooth root transaction curve enhances strength and stiffness, reduces maximum root stress, and improves rolling performance.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2021)
Article
Chemistry, Analytical
Sriraamshanjiev Natarajan, Mohanraj Thangamuthu, Sakthivel Gnanasekaran, Jegadeeshwaran Rakkiyannan
Summary: A technique based on Digital Twins is proposed to achieve accurate monitoring and prediction of tool conditions. By collecting vibration and sound signal data from physical systems, such as milling machines, and training the data with machine learning algorithms, the tool condition can be accurately monitored and predicted.
Article
Engineering, Manufacturing
Yen-Po Liu, Zekai Murat Kilic, Yusuf Altintas
Summary: This paper proposes a method for monitoring the in-process force coefficients for toolpaths with varying radial immersions or feed rates, and validates the effectiveness of this method.
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Stephanie Michel, Luka Franco Baraka, Alfredo J. Ibanez, Madina Mansurova
Summary: A methodology using gas chromatography coupled to mass spectrometry was developed to differentiate fine flavor cocoa beans of Peruvian chocolate, based on their aromatic profile. This method helps to understand the cocoa flavor development during each stage of the industrial processes and can be used as a quality control protocol in the chocolate industry.
Article
Computer Science, Artificial Intelligence
Pengfei Ding, Xianzhen Huang, Chengying Zhao, Huizhen Liu, Xuewei Zhang
Summary: In modern manufacturing, micro-milling technology is crucial for producing high-precision and complex micro-size parts. Understanding the changing rule of time-varying cutting is significant for comprehending the micro-milling mechanism and improving machining efficiency. Additionally, identifying and updating tool wear in advance can enhance the accuracy and sustainability of micromachining. This study proposes a tool wear prediction framework for micro-milling using a temporal convolution network, bi-directional long short-term memory, and a multi-objective arithmetic optimization algorithm. A new integrated model for real-time micro-milling cutting force monitoring is then developed, considering factors such as tool deformation, tool runout, time-varying cutting coefficient, chip separation state, and tool wear estimation results. The accuracy of the proposed tool wear prediction and cutting force model is verified through micro-milling experiments with Al6061 workpiece material. The developed model provides theoretical guidance for statics and dynamics analysis in micro-milling.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Agriculture, Dairy & Animal Science
Masoumeh Alinaghi, David Nilsson, Nikita Singh, Annika Hojer, Karin Hallin Saeden, Johan Trygg
Summary: Ripening is a crucial step in cheese manufacturing, and its assessment is challenging. This study used near-infrared hyperspectral imaging to monitor the biochemical and sensory attribute changes of paraffin wax-covered long-ripening hard cheeses during ripening. The results demonstrated the effectiveness of NIR-HS imaging for rapid monitoring of cheese maturity, with fat content and moisture being the most important variables correlated to the images.
JOURNAL OF DAIRY SCIENCE
(2023)
Article
Automation & Control Systems
Renjie Ge, Song Zhang, Renwei Wang, Xiaona Luan, Irfan Ullah
Summary: This research aims to investigate the energy consumption of machine tools and establish a cutting power model for ball-end milling. By conducting experiments, the study revealed and validated mathematical functions for spindle power and feed power. Results showed that the proposed method accurately predicted spindle power, feed power, and cutting power. The study's proposed power investigation method provides technical support for understanding machine tools' energy consumption characteristics.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Materials Science, Paper & Wood
Bartosz Swiderski, Izabella Antoniuk, Jaroslaw Kurek, Michal Bukowski, Jaroslaw Gorski, Albina Jegorowa
Summary: This article presents an automatic approach to tool condition monitoring, with the best solution achieving an overall accuracy of 94.33% and only 9 misclassification errors. This method is particularly important for the wood industry, as it allows for efficient evaluation of cutting tools, saving time and costs while improving productivity.
Article
Engineering, Industrial
E. Traini, G. Bruno, F. Lombardi
Summary: This paper presents a data-driven framework for estimating tool wear status and predicting its remaining useful life using machine learning techniques. The framework includes data preprocessing, feature engineering, and development of prediction models. A case study in a milling process demonstrates the potential of the framework for tool condition monitoring.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Engineering, Mechanical
Filipe Figueiredo dos Santos, Sandro da Costa Silva, Alexandre Mendes Abrao, Berend Denkena, Bernd Breidenstein, Kolja Meyer
Summary: Surface integrity is crucial for the functional performance of mechanical components, and deep rolling is an important surface treatment method. The study found that deep rolling significantly improves surface finish, but excessive pressure and feed can increase roughness. Increasing the number of rolling passes, however, helps improve surface finish.
JOURNAL OF TRIBOLOGY-TRANSACTIONS OF THE ASME
(2021)
Article
Engineering, Manufacturing
Berend Denkena, Marc-Andre Dittrich, Siebo Stamm, Marcel Wichmann, Soren Wilmsmeier
Summary: This passage discusses the challenges faced by production systems, bio-inspired production systems, and the concepts of "Gentelligence" and "process-DNA," as well as their performance in different applications.
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY
(2021)
Article
Engineering, Manufacturing
Berend Denkena, Alexander Kroedel, Sascha Beblein
Summary: The current state of the art shows that the friction behavior during machining is not yet fully understood, requiring further research. A novel method for analyzing friction mechanisms in machining was proposed in this study, revealing a significant influence of the sliding velocity of the chip on the coefficient of friction across a wide range of coating properties and cutting velocities.
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY
(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
Automation & Control Systems
Ran Jiao, Wenjie Liu, Ramy Rashad, Jianfeng Li, Mingjie Dong, Stefano Stramigioli
Summary: A novel end-effector bilateral rehabilitation robotic system (EBReRS) is developed for upper limb rehabilitation of patients with hemiplegia, providing simulations of multiple bimanual coordinated training modes, showing potential for application in home rehabilitation.
Article
Automation & Control Systems
Qiaosheng Pan, Yifang Zhang, Xiaozhu Chen, Quan Wang, Qiangxian Huang
Summary: A resonant piezoelectric rotary motor using parallel moving gears mechanism has been proposed and tested, showing high power output and efficiency.
