Mechatronics applications of measurements for smart manufacturing in an industry 4.0 scenario

D’Emilia, Giulio; Gaspari, Antonella; Natale, Emanuela

doi:10.1109/mim.2019.8674633

Cited by 17 publications

(8 citation statements)

References 19 publications

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“…The following possible classifiers available in a commercial software [38] have been used for comparison purposes, which are typically used for CM applications. Among these, a preliminary selection has been carried out based on the classification accuracy.…”

Section: Methodsmentioning

confidence: 99%

Physical and Metrological Approach for Feature’s Definition and Selection in Condition Monitoring

D’Emilia

Gaspari

Natale

2019

Sensors

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In this paper, a methodology is described aiming at emphasizing physical and metrological criteria in feature selection for condition monitoring of a real scale mechatronic system. The device is used for packaging applications according to the movements of its end effector, driven by a couple of brushless servomotors and a kinematic mechanical linkage. The approach is hybrid, meaning that the starting feature set is built with reference to both experimental data from different sensors and to the indication of a simplified kinematic and dynamic model of the mechanical linkage itself. A critical comparison and mixing of theoretical and experimental data, based also on a physical interpretation of differences, suggests some more features, with respect to the classical ones, of hybrid type, which could be mostly correlated to the effects of statuses and defects of the system to be identified. The whole procedure is step by step validated, in order to evaluate the variability of features, throughout the whole procedure. The variability is analyzed depending on the actions that are realized in order to define, select, and use the proposed features for data processing by advanced algorithms, like the most typically used classifiers and artificial neural networks. A comparison with the state-of-the-art automatic feature’s selection procedure is also presented. Experimental results show that the proposed methodology is able to classify with high accuracy many statuses of the mechatronic system, which are only slightly different as for set-up settings and/or mechanical wear and lubrication conditions of mechanical parts of the mechatronic system. Issues to be pursued to a more effective generalization of the method are also discussed.

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Section: Methodsmentioning

confidence: 99%

Physical and Metrological Approach for Feature’s Definition and Selection in Condition Monitoring

D’Emilia

Gaspari

Natale

2019

Sensors

Self Cite

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“…Augmented Reality (AR) will play a major role in changing how humans and machines relate providing workers with the ability to have more information available to them as well as enabling work to be done remotely in real-time [51]. It is currently applied in the automobile sector where it is deployed in AR glasses which highlights the location where each part is to be mounted during the manufacturing process, reducing error and increasing accuracy [52].…”

Section: Augmented Realitymentioning

confidence: 99%

Enviable roles of manufacturing processes in sustainable fourth industrial revolution – A case study of mechatronics

Afolalu

Ikumapayi

Abdulkareem

et al. 2021

Materials Today: Proceedings

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“…Nowadays, the term "Industry 4.0" has become a keyword in the development and research of all industrial applications. The main goal that resides behind this concept is to achieve optimization in terms of production and profits and to reduce the risks and the footprint on the environment [1,2]. In order to do that, the development of self-learning factories, capable of elaborating great quantities of data and being able to implement Internet-of-Things (IoT)-oriented technologies [3,4] to handle the transmission and the acquisition of all the information inside the productive system has become the main aim in this industrial phase [5].…”

Section: Introductionmentioning

confidence: 99%

Towards a State of Health Definition of Lithium Batteries through Electrochemical Impedance Spectroscopy

Patrizi,

Canzanella,

Ciani

et al. 2024

Electronics

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In the era of Industry 4.0, achieving optimization in production and minimizing environmental impact has become vital. Energy management, particularly in the context of smart grids, plays a crucial role in ensuring sustainability and efficiency. Lithium-ion batteries have emerged as a leading technology for energy storage due to their versatility and performances. However, accurately assessing their State of Health (SOH) is essential for maintaining grid reliability. While discharge capacity and internal resistance (IR) are commonly used SOH indicators, battery impedance also offers valuable insights into aging degradation. This article explores the use of Electrochemical Impedance Spectroscopy (EIS) to define the SOH of lithium batteries. By analyzing impedance spectra at different frequencies, a comprehensive understanding of battery degradation is obtained. A life cycle analysis is conducted on cylindrical Li–Mn batteries under various discharge conditions, utilizing EIS measurements and an Equivalent Circuit Model (ECM). This study highlights the differential effects of aging on battery characteristics, emphasizing the variations at different life stages and the behavior changes on each region of the impedance spectrum. Furthermore, it demonstrates the efficacy of EIS and the advantages of this technique compared to the solely IR measurements used in tracking SOH over time. This research contributes to advancing the understanding of lithium battery degradation and underscores the importance of EIS in defining their State of Health for Smart Grids applications.

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Mechatronics applications of measurements for smart manufacturing in an industry 4.0 scenario

Cited by 17 publications

References 19 publications

Physical and Metrological Approach for Feature’s Definition and Selection in Condition Monitoring

Physical and Metrological Approach for Feature’s Definition and Selection in Condition Monitoring

Enviable roles of manufacturing processes in sustainable fourth industrial revolution – A case study of mechatronics

Towards a State of Health Definition of Lithium Batteries through Electrochemical Impedance Spectroscopy

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