Prediction of the Product Quality of Turned Parts by Real-time Acoustic Emission Indicators

Albers, Albert; Stürmlinger, Tobias; Wantzen, Knut; Bartosz,; Gładysz, Bartłomiej; Münke, Friedrich Rieken

doi:10.1016/j.procir.2017.03.173

Cited by 8 publications

(6 citation statements)

References 13 publications

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“…• Modeling -Business Analytics method used to analyse the data. , while other works focused on outliers detection and statistical analysis (Albers et al 2017;Stein et al 2016). The last table of this SLR (Table 10) presents the practical cases that used Prescriptive Analytics.…”

Section: Qualitative Analysismentioning

confidence: 99%

Business analytics in Industry 4.0: A systematic review

Silva

Cortez

Pereira³

et al. 2021

Expert Systems

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Recently, the term "Industry 4.0" has emerged to characterize several Information Technology and Communication (ICT) adoptions in production processes (e.g., Internet-of-Things, implementation of digital production support information technologies). Business Analytics is often used within the Industry 4.0, thus incorporating its data intelligence (e.g., statistical analysis, predictive modeling, optimization) expert system component. In this paper, we perform a Systematic Literature Review (SLR) on this Business Analytics usage, covering a selection of 169 papers obtained from six major scientific publication sources from 2010 to March 2020. The selected papers were first classified in three major types, namely, Practical Application, Reviews and Framework Proposal. Then, we analyzed with more detail the practical application studies which were further divided into three main categories of the Gartner analytical maturity model, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. In particular, we characterized the distinct analytics studies in terms of the industry application and data context used, impact (in terms of their Technology Readiness Level) and selected data modeling method. Our SLR analysis provides a mapping of how data-based Industry 4.0 expert systems are currently used, disclosing also research gaps and future research opportunities.

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Section: Qualitative Analysismentioning

confidence: 99%

Business analytics in Industry 4.0: A systematic review

Silva

Cortez

Pereira³

et al. 2021

Expert Systems

View full text Add to dashboard Cite

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“…It is shown that with increasing wear of the processing tool, a non-linear increase in the stored energy of the AE signals occurs. In [13], it is noted that the parameters of the initial AE signal do not make it possible to determine the state of the cutting tool. However, when filtering the signal at a certain frequency before the destruction of the instrument, an increase in AE energy is observed.…”

Section: проведено експериментальнI дослIдження впливу зносу обробногmentioning

confidence: 99%

A study to determine the onset of catastrophic wear of a processing tool by statistical parameters of acoustic emission

Filonenko

Stakhova

2019

EEJET

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“…For example, improved efficiency of machine state identification from AE data was reached when features extracted in both time and frequency domains were combined and then reduced with the linear discriminant analysis [23]. A high-frequency acoustic emission signal with further acquired data was used to develop characteristic factors to predict product quality and to detect tool defects [24]. In one study, acoustic signals were captured for an entire grinding cycle until abrasive grains of girding wheel become dull [25].…”

Section: The Sound Pattern As the Basis For Identification Of Type Anmentioning

confidence: 99%

Use of sound spectral signals analysis to assess the technical condition of mechanical devices

Maciąg

Chałko

2019

MATEC Web Conf.

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The article presents the results of a part of research conducted by the authors into a wide range of work on automation of public safety systems. Their main purpose is to create, on the basis of sound signals analysis, system of warning against the use of firearms monitored public places not only at the time of shooting, but at the stage of preparing - the firearm reloading process. The range of acoustic measurements presented in the article and their analyzes included variability of sound emission of selected type of firearms depending on the number of operations and thus the degree of wear. Analysis of the recorded data will allow in the future to develop a system enabling not only to determine a type of firearm or tp narrow down the search area of individual specimens, but also to determine the degree of wear in terms of suitability for further use. The results discussed in the article correspond to two states of the same firearm model. The first is the initial state from the manufacturer’s factory after returning 50 control shots, the other after over 20,000 cycles. The used firearm was technically fully efficient, with no need to replace the elements during operation as well as tests. The presented scope of measurements includes spectral analysis of sound in the near field and time analysis of sound emission levels in the successive operation phases of the firearm mechanisms.

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Prediction of the Product Quality of Turned Parts by Real-time Acoustic Emission Indicators

Cited by 8 publications

References 13 publications

Business analytics in Industry 4.0: A systematic review

Business analytics in Industry 4.0: A systematic review

A study to determine the onset of catastrophic wear of a processing tool by statistical parameters of acoustic emission

Use of sound spectral signals analysis to assess the technical condition of mechanical devices

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