Challenges and trends in manufacturing measurement technology – the
“Industrie 4.0” concept

Imkamp, Dietrich; Berthold, Jürgen; Heizmann, Michael; Kniel, Karin; Manske, Eberhard; Peterek, Martin; Schmitt, Robert; Seidler, Jochen; Sommer, Klaus-Dieter

doi:10.5194/jsss-5-325-2016

Cited by 56 publications

(36 citation statements)

References 13 publications

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“…“Industry 4.0” represents an initiative for the future development of industrial production [ 1 ]. The idea aims to link the manufacturing industry and information technology to make production more flexible, where the flexibility offers the possibility to manufacture customized products through efficient manufacturing processes.…”

Section: Introductionmentioning

confidence: 99%

Traceability of On-Machine Tool Measurement: A Review

Mutilba

Gomez-Acedo

Kortaberria

et al. 2017

Sensors

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Nowadays, errors during the manufacturing process of high value components are not acceptable in driving industries such as energy and transportation. Sectors such as aerospace, automotive, shipbuilding, nuclear power, large science facilities or wind power need complex and accurate components that demand close measurements and fast feedback into their manufacturing processes. New measuring technologies are already available in machine tools, including integrated touch probes and fast interface capabilities. They provide the possibility to measure the workpiece in-machine during or after its manufacture, maintaining the original setup of the workpiece and avoiding the manufacturing process from being interrupted to transport the workpiece to a measuring position. However, the traceability of the measurement process on a machine tool is not ensured yet and measurement data is still not fully reliable enough for process control or product validation. The scientific objective is to determine the uncertainty on a machine tool measurement and, therefore, convert it into a machine integrated traceable measuring process. For that purpose, an error budget should consider error sources such as the machine tools, components under measurement and the interactions between both of them. This paper reviews all those uncertainty sources, being mainly focused on those related to the machine tool, either on the process of geometric error assessment of the machine or on the technology employed to probe the measurand.

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Section: Introductionmentioning

confidence: 99%

Traceability of On-Machine Tool Measurement: A Review

Mutilba

Gomez-Acedo

Kortaberria

et al. 2017

Sensors

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“…Intelligent decisions of complex systems are based on the knowledge of the system as well as ambient conditions and influence factors provided with high accuracy by sensors. The importance of sensors, measurement science, and smart evaluation for Industry 4.0 has been recognized and acknowledged by various authors (Imkamp et al, 2016;Sommer and Schütze, 2016;Walter, 2017) and has already led to the statement "Industry 4.0: nothing goes without sensor systems" ("Industrie 4.0: Ohne Sensorsysteme geht nichts") (Arnold, 2014). It should be acknowledged that notwithstanding all the euphoria and expectations for higher sensor production and sales volumes -especially when thinking about the Trillion sensor roadmap (Bryzek, 2013) -paradigm changes are expected, as is often the case in the digital revolution.…”

Section: Discussionmentioning

confidence: 99%

Sensors 4.0 – smart sensors and measurement technology enable Industry 4.0

Schütze

Helwig²,

Schneider³

2018

J. Sens. Sens. Syst.

204

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Abstract. "Industrie 4.0" or the Industrial Internet of Things (IIoT) are two terms for the current (r)evolution seen in industrial automation and control. Everything is getting smarter and data generated at all levels of the production process are used to improve product quality, flexibility, and productivity. This would not be possible without smart sensors, which generate the data and allow further functionality from self-monitoring and selfconfiguration to condition monitoring of complex processes. In analogy to Industry 4.0, the development of sensors has undergone distinctive stages culminating in today's smart sensors or "Sensor 4.0". This paper briefly reviews the development of sensor technology over the last 2 centuries, highlights some of the potential that can be achieved with smart sensors and data evaluation, and discusses success requirements for future developments. In addition to magnetic sensor technologies which allow self-test and self-calibration and can contribute to many applications due to their wide spectrum of measured quantities, the paper discusses condition monitoring as a primary paradigm for introducing smart sensors and data analysis in manufacturing processes based on two projects performed in our group.

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“…The importance of using 3D scanning systems is also related to the amount of information that those systems can yield [1]. A 3D optical based scanner is able to provide information for a 2D dimensional analysis, as well as, a 3D analysis involving a 3D comparison, which allows detecting, more immediately, the criticalities of a manufacturing process.…”

Section: Application To Additive Manufactured Tcp Step Gaugesmentioning

confidence: 99%

“…As the geometrical complexity of industrial components increases, the advantages of using these technologies increase as well. Their capability to acquire large amounts of points in a relatively short time, also in the presence of free-form shaped parts, makes these techniques particularly attractive, as fast, flexible, and holistic systems [1]. When the close range is considered, the mostly adopted optical techniques are laser scanners, structured light scanners, and photogrammetry.…”

Section: Introductionmentioning

confidence: 99%

Use of Miniature Step Gauges to Assess the Performance of 3D Optical Scanners and to Evaluate the Accuracy of a Novel Additive Manufacture Process

Guerra

Chiffre

Lavecchia

et al. 2020

Sensors

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In this work, we show how miniature step gauges featuring unidirectional and bidirectional lengths can be used to assess the performance of 3D optical scanners as well as the accuracy of novel Additive Manufacturing (AM) processes. A miniature step gauge made of black polyphenylene sulfide (PPS) was used for the performance verification of three different optical scanners: a structured light scanner (SLS), a laser line scanner (LLS), and a photogrammetry-based scanner (PSSRT), having comparable resolutions and working volumes. Results have shown a good agreement between the involved scanners, with errors below 5 μm and expanded uncertainties below 10 μm. The step gauge geometry due to the bidirectional lengths, highlights that there is a different interaction between the optical properties of the step gauge under measurement and each optical instrument involved and this aspect has to be considered in the uncertainty budget. The same geometry, due to its great significance in the detection of systematic errors, was used, as a novelty, to evaluate the accuracy of Lithography-based Ceramics Manufacturing (LCM), a proprietary additive manufacturing technology used for the fabrication of medical implants. In particular, two miniature step gauges made of Tricalcium Phosphate (TCP) were produced. Measurements conducted with the SLS scanner were characterized by a negligible error and by an uncertainty of about 5 μm. Deviations of the manufactured step gauges with respect to the Computer Aided Designed (CAD) model were comprised between ±50 μm, with positive deviations in the order of 100 μm on vertical sides. Differences in the order of 50 μm between the two step gauges were registered.

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Challenges and trends in manufacturing measurement technology – the “Industrie 4.0” concept

Cited by 56 publications

References 13 publications

Traceability of On-Machine Tool Measurement: A Review

Traceability of On-Machine Tool Measurement: A Review

Sensors 4.0 – smart sensors and measurement technology enable Industry 4.0

Use of Miniature Step Gauges to Assess the Performance of 3D Optical Scanners and to Evaluate the Accuracy of a Novel Additive Manufacture Process

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