The effect of stylus tip radius on Ra, Rq, Rp, Rv, and Rt parameters in turned and milled samples

Neto, Walter dos Santos Motta; Leal, José Eduardo Silveira; Arantes, Luciano José; Arencibia, Rosenda Valdés

doi:10.1007/s00170-018-2630-5

Cited by 13 publications

(4 citation statements)

References 15 publications

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“…The physical dimension of the stylus tip prevents the probe from perfectly following the shape of the surface, especially when there is a sharp peak in roughness. The state of art in industrial application of styluses shows that a 2 µm tip is the lower limit to the probe tip radius [ 44 ]; in fact even recent literature studies the effect of stylus tip radius in R a . Our simple model is descriptive of best case scenarios in terms of tip radius in industrial applications.…”

Section: Discussionmentioning

confidence: 99%

Design and Metrological Analysis of a Backlit Vision System for Surface Roughness Measurements of Turned Parts

Baleani

Paone

Gladines

et al. 2023

Sensors

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The focus of this study is to design a backlit vision instrument capable of measuring surface roughness and to discuss its metrological performance compared to traditional measurement instruments. The instrument is a non-contact high-magnification imaging system characterized by short inspection time which opens the perspective of in-line implementation. We combined the use of the modulation transfer function to evaluate the imaging conditions of an electrically tunable lens to obtain an optimally focused image. We prepared a set of turned steel samples with different roughness in the range Ra 2.4 µm to 15.1 µm. The layout of the instrument is presented, including a discussion on how optimal imaging conditions were obtained. The paper describes the comparison performed on measurements collected with the vision system designed in this work and state-of-the-art instruments. A comparison of the results of the backlit system depends on the values of surface roughness considered; while at larger values of roughness the offset increases, the results are compatible with the ones of the stylus at lower values of roughness. In fact, the error bands are superimposed by at least 58% based on the cases analyzed.

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Section: Discussionmentioning

confidence: 99%

Design and Metrological Analysis of a Backlit Vision System for Surface Roughness Measurements of Turned Parts

Baleani

Paone

Gladines

et al. 2023

Sensors

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“…Since it directly influences the materials' optical and mechanical qualities, roughness is an essential factor to consider when assessing the surfaces of different materials. Roughness affects a variety of qualities, including adhesion, fracture toughness, fatigue resistance, optical properties, fluid flow, heat transfer, wear, friction, lubrication, and corrosion [10]. One of the most crucial elements in tribology, roughness may be used to assess the efficiency of a machining process.…”

Section: Literature Reviewmentioning

confidence: 99%

Effect of High Speed Machining on Surface Roughness Characteristics R_a, R_q, R_Z

Khare,

Gulati,

Singh

et al. 2023

E3S Web Conf.

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Today’s machining industries experience a variety of challenges, but achieving high quality in terms of dimensional accuracy, surface quality, and production rate is their key concern. An effort has been made in the current study to investigate the impact of HSM process parameters on different Surface Roughness characteristics Ra, Rq, and Rz. The trials were conducted on Ti-6Al-4V, a material that finds extensive use in the automotive, aerospace, and biomedical industries. Depth of cut, feed rate, cutting speed, and step over were taken into account as HSM inputs for the experiment. Similar to this, the output characteristics Surface roughness parameters Ra, Rq, and Rz were used. The trials were carried out using Taguchi’s standard L9 Orthogonal Array, and the optimization of multi responses was carried out using Grey analysis. The most significant influences on the parameters of surface roughness were found to be cutting speed and depth of cut. A confirmation experiment was performed using the ideal set of parameters to validate the study, and the results were found to be in good agreement with those of the experiment. According to the findings, the HSM method produced a superior surface quality.

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“…The influence of surface texture on surface roughness is investigated in [34], while Ref. [35] analyzes the impact of the tip radius of measuring contacts on surface roughness parameters. Additionally, Ref.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Sustainable Production Processes in C45 Steel Machining Using a Confocal Chromatic Sensor

Jurko,

Paľová,

Michalík

et al. 2024

Lubricants

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Metal machining production faces a myriad of demands encompassing ecology, automation, product control, and cost reduction. Within this framework, an exploration into employing a direct inspection of the machined area within the work zone of a given machine through a confocal chromatic sensor was undertaken. In the turning process, parameters including cutting speed (A), feed (B), depth of cut (C), workpiece length from clamping (D), and cutting edge radius (E) were designated as input variables. Roundness deviation (Rd) and tool face wear (KM) parameters were identified as output factors for assessing process performance. The experimental phase adhered to the Taguchi Orthogonal Array L27. Confirmatory tests revealed that optimizing process parameters according to the Taguchi method could enhance the turning performance of C45 steel. ANOVA results underscored the significant impact of cutting speed (A), feed (B), depth of cut (C), and workpiece length from clamping (D) on turning performance concerning Rd and KM. Furthermore, initial regression models were formulated to forecast roundness variation and tool face wear. The proposed parameters were found to not only influence the machined surface but also affect confocal sensor measurements. Consequently, we advocate for the adoption of these optimal cutting conditions in product production to bolster turning performance when machining C45 steel.

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The effect of stylus tip radius on Ra, Rq, Rp, Rv, and Rt parameters in turned and milled samples

Cited by 13 publications

References 15 publications

Design and Metrological Analysis of a Backlit Vision System for Surface Roughness Measurements of Turned Parts

Design and Metrological Analysis of a Backlit Vision System for Surface Roughness Measurements of Turned Parts

Effect of High Speed Machining on Surface Roughness Characteristics R_a, R_q, R_Z

Optimization of Sustainable Production Processes in C45 Steel Machining Using a Confocal Chromatic Sensor

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The effect of stylus tip radius on Ra, Rq, Rp, Rv, and Rt parameters in turned and milled samples

Cited by 13 publications

References 15 publications

Design and Metrological Analysis of a Backlit Vision System for Surface Roughness Measurements of Turned Parts

Design and Metrological Analysis of a Backlit Vision System for Surface Roughness Measurements of Turned Parts

Effect of High Speed Machining on Surface Roughness Characteristics Ra, Rq, RZ

Optimization of Sustainable Production Processes in C45 Steel Machining Using a Confocal Chromatic Sensor

Contact Info

Product

Resources

About

Effect of High Speed Machining on Surface Roughness Characteristics R_a, R_q, R_Z