Tool Wear Monitoring for Ultrasonic Metal Welding of Lithium-Ion Batteries

Shao, Chenhui; Kim, Tae Hyung; Hu, S. Jack; Jin, Jesse S.; Abell, Jeffrey A.; Spicer, J. Patrick

doi:10.1115/1.4031677

Cited by 41 publications

(25 citation statements)

References 26 publications

(59 reference statements)

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“…The time domain features were extracted to get reliable information for the motion. In this work, we used Fisher's ratio for the screening and selection of features. As Fisher's ratio increases, the separation between the classes also increases.…”

Section: Resultsmentioning

confidence: 99%

Utilizing a 5G spectrum for health care to detect the tremors and breathing activity for multiple sclerosis

Haider

Ren

Fan

et al. 2018

Trans Emerging Tel Tech

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Utilizing fifth‐generation (5G) sensing in the health care sector with increased capacity and massive spectrum range increases the quality of health care monitoring systems. In this paper, 5G C‐band sensing operating at 4.8 GHz is used to monitor a particular body motion of multiple sclerosis patients, especially the tremors and breathing patterns. The breathing pattern obtained using 5G C‐band technology is compared with the invasive breathing sensor to monitor the subtle chest movements caused due to respiration. The 5G C‐band has a huge spectrum from 1 to 100 GHz, which enhances the capacity and performance of wireless communication by increasing the data rate from 20 Gb/s to 1 Tb/s. The system captures and monitors the wireless channel information of different body motions and efficiently identifies the tremors experienced since each body motion induces a unique imprint that is used for a particular purpose. Different machine learning algorithms such as support vector machine, k‐nearest neighbors, and random forest are used to classify the wireless channel information data obtained for various human activities. The values obtained using different machine learning algorithms for various performance metrics such as accuracy, precision, recall, specificity, Kappa, and F‐measure indicate that the proposed method can efficiently identify the particular conditions experienced by multiple sclerosis patients.

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Section: Resultsmentioning

confidence: 99%

Utilizing a 5G spectrum for health care to detect the tremors and breathing activity for multiple sclerosis

Haider

Ren

Fan

et al. 2018

Trans Emerging Tel Tech

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“…Innovative manufacturing processes that consume less energy are also important for sustainability. For instance, due to its numerous advantages over traditional fusion welding techniques, ultrasonic metal welding has been popularly adopted in various industrial applications, such as lithium-ion battery assembly [34][35][36][37][38], automotive body construction [39], and power device packaging [40]. Two important advantages of this process are its short cycle time and low energy consumption.…”

Section: Process Levelmentioning

confidence: 99%

Enhancing Sustainability and Energy Efficiency in Smart Factories: A Review

et al. 2018

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With the rapid development of sensing, communication, computing technologies, and analytics techniques, today’s manufacturing is marching towards a new generation of sustainability, digitalization, and intelligence. Even though the significance of both sustainability and intelligence is well recognized by academia, industry, as well as governments, and substantial efforts are devoted to both areas, the intersection of the two has not been fully exploited. Conventionally, studies in sustainable manufacturing and smart manufacturing have different objectives and employ different tools. Nevertheless, in the design and implementation of smart factories, sustainability, and energy efficiency are supposed to be important goals. Moreover, big data based decision-making techniques that are developed and applied for smart manufacturing have great potential in promoting the sustainability of manufacturing. In this paper, the state-of-the-art of sustainable and smart manufacturing is first reviewed based on the PRISMA framework, with a focus on how they interact and benefit each other. Key problems in both fields are then identified and discussed. Specially, different technologies emerging in the 4th industrial revolution and their dedications on sustainability are discussed. In addition, the impacts of smart manufacturing technologies on sustainable energy industry are analyzed. Finally, opportunities and challenges in the intersection of the two are identified for future investigation. The scope examined in this paper will be interesting to researchers, engineers, business owners, and policymakers in the manufacturing community, and could serve as a fundamental guideline for future studies in these areas.

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“…Ultrasonic welding schematic for battery tabs (see [9]). Figure 5 shows these components in a schematic of an ultrasonic welding application for battery tabs [9][10][11]. The battery cells used in the Volt battery come as pouches with tabs for electrical connection as shown in Figure 6(a).…”

Section: Offline Learningmentioning

confidence: 99%

Big Data-Driven Manufacturing—Process-Monitoring-for-Quality Philosophy

Abell

Chakraborty

Escobar

et al. 2017

Journal of Manufacturing Science and Engineering

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Discussion of big data (BD) has been about data, software, and methods with an emphasis on retail and personalization of services and products. Big data also has impacted engineering and manufacturing and has resulted in better and more efficient manufacturing operations, improved quality, and more personalized products. A less apparent effect is that big data have changed problem solving: the problems we choose to solve, the strategy we seek, and the tools we employ. This paper illustrates this point by showing how the big data style of thinking enabled the development of a new quality assurance philosophy called process monitoring for quality (PMQ). PMQ is a blend of process monitoring and quality control (QC) that is founded on big data and big model (BDBM), which are catalysts for the next step in the evolution of the quality movement. Process monitoring (PM) for quality was used to evaluate the performance of the ultrasonically welded battery tabs in the new Chevrolet Volt, an extended range electric vehicle.

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Tool Wear Monitoring for Ultrasonic Metal Welding of Lithium-Ion Batteries

Cited by 41 publications

References 26 publications

Utilizing a 5G spectrum for health care to detect the tremors and breathing activity for multiple sclerosis

Utilizing a 5G spectrum for health care to detect the tremors and breathing activity for multiple sclerosis

Enhancing Sustainability and Energy Efficiency in Smart Factories: A Review

Big Data-Driven Manufacturing—Process-Monitoring-for-Quality Philosophy

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