Elsevier

CIRP Annals

Volume 64, Issue 2, 2015, Pages 797-813
CIRP Annals

Calibration and verification of areal surface texture measuring instruments

https://doi.org/10.1016/j.cirp.2015.05.010Get rights and content

Abstract

In this paper, the calibration and verification infrastructure to support areal surface texture measurement and characterisation will be reviewed. A short historical overview of the subject will be given, along with a discussion of the most common instruments and directions of current international standards. Traceability and uncertainty will be discussed, followed by a presentation of the latest developments in software and material measurement standards. The concept and current infrastructure for determining the metrological characteristics of instruments will be highlighted and future research requirements will be presented.

Introduction

The understanding and measurement of three-dimensional (areal) surface topography is of critical importance in many disciplines, including modern advanced manufacturing. Conventional manufacturing processes produce stochastic surfaces resulting from the need to achieve the nominal geometry of a part. The micro- and nano-scale features of the topography are a by-product of the processing technique and little or no attempt is made to manipulate them to benefit the surface function. More recently, surfaces are increasingly structured, where processing imparts pre-determined functional properties [38], [98]. With the increasing development of advanced components, surfaces and their associated properties are recognised as the critical factor dominating function [31], [174]. Consequently, to maximise the component functionality there has been a large focus on the component surfaces and designing the surface structures to optimise a particular surface-related function [16], [23], [99], [125], [125]. To support manufacturing of such surfaces, a measurement traceability and calibration infrastructure is essential to ensure product quality.

The history of surface texture measurement can be found elsewhere [11], [71], [118], [145], [189], [193] and this section will highlight some of the important developments, specifically in calibration and performance verification. One of the earliest attempts at controlling surface texture was made in the USA by a company that mounted samples of textures produced by different methods in cases [157] which were given to the machinist, who was expected to obtain a texture on his or her workpiece as near to that specified as possible. This was a suitable method for controlling the appearance of the workpiece but did not in any way indicate the magnitude of the surface texture. Around 1947, Rolt (at the National Physical Laboratory, UK) was pressing for surface texture measurement to produce a single number that would define a surface and enable comparisons to be made. The first parameter in use was Rq, but it was soon replaced in popularity by the number most easily obtainable from a profile graph, the Ra parameter, obtained using a planimeter.

Calibration and performance verification of stylus instruments from the 1940s onwards was carried out using various techniques, which included (list adapted from [164]):

  • Checking the condition and tip radius of the diamond stylus using: metallurgical optical or stereoscan microscopes, and specially shaped (usually triangular) calibration artefacts with a Ra value that reduces as the stylus wears [203] or by tracing slowly over a sharp edge, such as a razor blade [169].

  • Determining the linearity of the input (pick-up) and output (electronic meter and/or recorder) of the instrument, usually using incremental electrical inputs.

  • Checking, or simply noting, the spatial frequency response (transmission characteristics) of the instrument – in some cases using a vibrating platform whose amplitude was monitored by a variety of techniques. Such techniques have since been further developed [5], [58], [112], but are not widespread due to the need for another relatively complex instrument. Artefacts with a series of gratings, both sinusoidal (type C1) [156], [171] and square-wave [144] have also been employed to determine the instrument spatial frequency response.

  • Calibrating the magnification of the height response using step height artefacts (type A) [190] or a series of gauge blocks with a calibration lever.

  • Verifying the capability of the instrument to output an accurate value for Ra using regular (type C) and irregular (type D) specimens (see Section 7.2) on cylindrical [183] and flat substrates [67], [181].

Work on the calibration and performance verification of optical instruments has also used a variety of approaches, for example:

  • Comparison with stylus instruments (for example, [35], [36]).

  • Calibration of the motion of scanners using traceable external or integrated sensors or through measurement of step height standards (for example, [29], [32]).

  • Comparison between instruments with different operating principles, for example comparing root-mean-square roughness obtained from total integrated scatter, stylus profilometry, optical heterodyne profilometry and a variable angle scatterometer [56].

  • Determining the instrument transfer function [33].

In 1985, an ISO specification standard on instrument calibration artefacts was published (ISO 5436), which has since been superseded (see Section 3.2). There were no serious breakthroughs or deviations from the work presented in the above list for a number of years until the work undertaken in the EU project “CALISURF”, which was completed in 2000 [179]. CALISURF was a multi-partner project with the aim of developing calibration artefacts for profile measuring instruments, which mapped onto the type A–D artefacts in ISO 5436 part 1 (see Section 3.2).

As far as specification standards were concerned, all of the above work was concentrated at surface profile measurement; traceability and characterisation for areal surface texture were first discussed by Lonardo et al. in 1996 [122]. The first breakthrough work on areal surface texture characterisation was carried out by a consortium as part of a European project led by Ken Stout from the University of Birmingham [173]. This project ended with the publication of the “Blue Book” [167], which contained the definitions of the so-called “Birmingham-14” parameters and a number of suggestions for areal instrument calibration. Following this project, ISO initiated standardisation work on areal surface texture. However, ISO experts rapidly realised that further research work was needed to determine the stability of areal parameters and their correlation with the functional criteria used by industry. A further project (“SURFSTAND”) was carried out between 1998 and 2001, by a consortium of universities and industrial partners, led by Liam Blunt of the University of Huddersfield. SURFSTAND ended with the publication of the “Green Book” [9] and generated the basic documents for forthcoming specification standards. The various sections in this paper will pick up the story from this point onwards.

The paper is organised as follows. The last part of Section 1 gives some terminology that is important for the rest of the paper. In Section 2 the instrumentation that is in use today, and which is covered by this review, will be briefly discussed. The latest specification standards are presented in Section 3, concentrating on ISO standards, and on the subjects of calibration and verification. In Section 4, traceability for areal surface texture measurement will be discussed and in Section 5, techniques for determining measurement uncertainty will be reviewed. In Sections 6 Software measurement standards, 7 Material measures, software measurement standards and material measures (physical measurement standards) are discussed respectively. Metrological characteristics and their determination are presented in Section 8 and methods to determine the spatial frequency response of an instrument are reviewed in Section 9. Performance verification techniques are discussed in Section 10. The future of areal calibration and verification, and a discussion, is presented in Section 11.

There are a number of terms relating to the field of metrology that need to be discussed briefly. Any of these terms are used almost indistinguishably in practice, which can often lead to confusion when specifying instruments. The terms used in the paper are taken from the latest version of the BIPM International Vocabulary of Metrology (VIM) [8].

Traceability—The concept of traceability is one of the most fundamental in metrology and is the basis upon which all measurements can be claimed to be accurate. Traceability is defined as follows:

Traceability is the property of the result of a measurement whereby it can be related to stated references, usually national or international standards, through a documented unbroken chain of comparisons all having stated uncertainties.

It is important to note the last part of the definition of traceability that states all having stated uncertainties. This is an essential part of traceability as it is impossible to usefully compare, and hence calibrate, instruments without a statement of uncertainty. Uncertainty and traceability are inseparable [62]. Traceability applied to surface texture measurement is discussed in Section 4.

Calibration—is defined as follows:

Operation that, under specified conditions, in a first step establishes a relation between the quantity values with measurement uncertainties provided by measurement standards and corresponding indications with associated measurement uncertainties and, in a second step, uses this information to establish a relation for obtaining a measurement result from an indication.

In simpler terms, calibration is a comparison between two measurements; one of which is a reference or standard value, and the other which is being tested. Calibration is the step from one box to another in the traceability diagram shown in Fig. 3. Again, note the use of the term uncertainty in the formal definition of calibration.

Commonly the term calibration is misused, which has led to confusion in understanding the aim of the calibration process. The frequent misuse of the calibration term is when it is confused with adjustment.

Adjustment—is defined as follows:

Set of operations carried out on a measuring system so that it provides prescribed indications corresponding to given values of a quantity to be measured

The adjustment process physically changes some parameters of a metrological tool (it can be a mechanical adjustment or it could be the result of changing the value of a software constant) to provide an indication that is closer to a known value. The adjustment process does not provide information about measurement uncertainty. Similar results could be obtained by correcting the measurement result using the results from a calibration certificate. A meaningful measurement result can be presented without adjustment, but it must have an associated uncertainty.

An example of adjustment of a stylus instrument is the physical adjustment that is performed using a calibrated step height material measure (type A) or a sinusoid with a known Ra (type C). These material measures reproduce a height value known with an associated uncertainty. Generally, during the adjustment of the instrument, the response curve (see Section 8) is changed according to the result of a single measurement. The adjustment cannot account for the uncertainty associated with the measurement result; it only uses a value from the range of possible values that are within the limits given by the measurement uncertainty. After adjustment, the measurement of the same step height can provide a different result. The basic difference between calibration and adjustment is also illustrated by the requirement in ISO 17025 [77] that an instrument should be calibrated before and after adjustment.

Verification—is defined as follows:

Provision of objective evidence that a given item fulfils specified requirements.

A verification test is designed to check whether a particular instrument attribute meets its specification. Verification, therefore, does not necessarily imply that measurement uncertainty is part of the test, but usually some form of quantitative measure is required. Often, an assertion that an instrument is within specification assumes that the test result is inside the specification by at least a “guard band”, for example, the expanded uncertainty.

Section snippets

Instrumentation

There is a range of instrumentation for measuring surface texture (see [118], [193]). This section will only consider the techniques that have either been standardised, or are under discussion in international standardisation committees (explicitly ISO technical committee 213 working group 16). This restriction to standardised (or near-standardised) techniques is because calibration methods for other instrument types are still in their infancy and excluding them reduces the scope of the review

ISO background

Surface texture specification standards are part of the scope of the International Organization for Standardization Technical Committee 213 (TC 213). This committee deals with Dimensional and Geometrical Product Specifications and Verification (as do many national committees). ISO TC 213 has developed a wide range of specification standards for surface texture measurement for both profiling and areal methods and has an ambitious agenda for future standards.

Note that ISO TC 172 also addresses

Traceability

The concept of traceability has already been defined in Section 1.2 and is further elaborated elsewhere [35]. In this paper, the traceability of a surface texture measurement is split into two parts that impact the traceability of the result. Firstly, there is the impact on traceability of the measurement process (the instrument-surface interaction), and secondly, the impact of the analysis algorithms and parameter calculations. The impact of the instrument is determined by calibrating the axes

Measurement uncertainty

It is rare to see measurement uncertainty quoted with surface texture measurements, although statements of accuracy on instrument specifications are common [34], [40]. The lack of uncertainty estimation is probably due to the complexity of the measurand and measurement process. The greatest complication when calculating uncertainties in surface texture measurement is the contribution of the surface itself. Unlike less complex measurements, such as nominally flat surfaces, the surface being

Software measurement standards

The process flow from a surface topography measurement to a parameter calculation is fairly complex and sometimes open to ambiguity. The software packages that are supplied with surface topography instruments, and stand-alone software applications, usually offer a large range of options for characterisation. These software applications can be verified by comparing them to reference software. From this comparison, the contribution to the uncertainty in a calculated parameter originating from the

Terminology

Material measure is defined in VIM [8] as:

Measuring instrument reproducing or supplying, in a permanent manner during its use, quantities of one or more given kinds, each with an assigned quantity value.

Note 2 attached to the above definition:

A material measure can be a measurement standard.

The definition of the measurement standard, also called an etalon [8], is:

Realization of the definition of a given quantity, with stated quantity value and associated measurement uncertainty, used as a

The current ISO framework

In their current format, the metrological characteristics (MCs) establish a common calibration framework for all areal surface topography instruments, contact and non-contact, which are used for surface texture measurements. The concept behind the MCs approach originated from the need for simple standardised calibration routines for areal surface topography instruments that are designed for the non-expert user. Prior to the development of the MCs framework, the draft ISO specification standards

Transfer function approaches

The metrological characteristics go some way to calibrating areal surface topography instruments, but they currently do not take into account the ability of an instrument to measure a complex surface, i.e. a surface with slopes and curvature. All surfaces have a finite spatial frequency bandwidth, that is, they can be represented as a series of sinusoidal oscillations with given amplitudes and wavelengths that are simply added together to produce the surface. In this way, a flat surface is a

Performance verification

Performance verification for surface texture measurement has not been given much attention in the research community. Whilst it is common for instrument users to carry out gauge repeatability and reproducibility (R&R) studies [34], there are no formal procedures for performance verification. ISO 25178 part 700 will contain information about how to performance verify an areal surface topography instrument and some guidance is given elsewhere [119] using an irregular (type AIR) material measure.

Discussion and future requirements

It is clear from this paper that the calibration of areal surface topography instruments has received a great deal of research attention over the last one hundred years and this work is on-going. However, often instrument users are more interested in performance verification–they simply want to know if the instrument is operating to its specification. Whist performance verification is being discussed in ISO 213 WG 16; there is a lack of research in this area and this needs urgent attention.

The

Acknowledgments

This work was partially funded by the National Measurement System Engineering & Flow Metrology Programme. The authors would like to thank Dr Peter Harris (NPL), Dr Peter de Groot (Zygo), Dr Ted Vorburger (NIST) and Dr Ludger Koenders (PTB) for their comments and additions to the manuscript.

References (205)

  • H. Haitjema et al.

    Noise Bias Removal in Profile Measurements

    Measurement

    (2005)
  • A.J. Henning et al.

    Correction for Lateral Distortion in Coherence Scanning Interferometry

    CIRP Annals

    (2013)
  • X. Jiang et al.

    Technology Shifts in Surface Metrology

    CIRP Annals

    (2012)
  • D.G. Abdelsalem

    A Comparison of Digital Holographic Microscopy and On-Axis Phase-Shifting Interferometry for Surface Profiling

    Measurement

    (2013)
  • ASMEB.89.7. 5

    Metrological Traceability of Dimensional Measurements to the SI Unit of Length

    (2006)
  • V.G. Badami et al.

    Evaluation of the Measurement Performance of a Coherence Scanning Microscope using Roughness Specimens

  • A. Baker et al.

    Final Report on APMP.L-K8: International Comparison of Surface Roughness

    Metrologia

    (2013)
  • A. Bendeli et al.

    A Surface Simulator for the Precise Calibration of Surface Roughness Measuring Equipment

    Metrologia

    (1974)
  • J.M. Bennett et al.

    Stylus Profiling Instrument for Measuring Statistical Properties of Smooth Optical Surfaces

    Applied Optics

    (1981)
  • T.S. Bergstrom et al.

    Comparison of Surface Texture Measurement Systems

  • BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP and OIML, 2012, International Vocabulary of Metrology—Basic and General...
  • L.A. Blunt et al.

    Advanced Techniques for Assessment Surface Topography

    (2003)
  • H. Bodschwinna et al.

    Oberflächenmeßtechnik mit Tastschnittgeräten in der Industriellen Praxis,

    (1992)
  • S. Boedecker et al.

    Calibration of the Z-axis for Large-scale Scanning White-light Interferometers

    Journal of Physics: Conference Series

    (2011)
  • S. Boedecker et al.

    Positioning Errors in Coherence Scanning Interferometers: Determination of Measurement Uncertainties with Novel Calibration Artifacts, In Fringe 2013

    (2014)
  • U. Brand et al.

    New Depth-Setting Standards with Grooves up to 5 mm Depth

  • S. Bui et al.

    Surface Metrology Algorithm Testing System

    Precision Engineering

    (2006)
  • Y. Chen et al.

    Fabrication and Characterization of Areal Roughness Specimens for Applications in Scanning Probe Microscopy

    Measurement Science and Technology

    (2013)
  • Chesna, J. W., Schimuzu, Y., Leach, R. K., 2013, On the use of Mercury Sessile Drops as Reference Artefacts for the...
  • J.M. Claverley et al.

    A Review of the Existing Performance Verification Infrastructure for Micro-CMMs

    Precision Engineering

    (2014)
  • D.G. Coblas et al.

    Manufacturing Textured Surfaces: State of the Art and Recent Developments

    Proceedings of the Institution of Mechanical Engineers, Part J: Journal Engineering Tribology

    (2014)
  • X. Colonna de Lega

    Aberration Characterisation Using Frequency Domain Analysis of Low-coherence Interferograms

    Proceedings of SPIE

    (2004)
  • J.M. Coupland et al.

    Optical Tomography and Digital Holography

    Measurement Science and Technology

    (2008)
  • J.M. Coupland et al.

    Coherence Scanning Interferometry: Linear Theory of Surface Measurement

    Applied Optics

    (2013)
  • K. Creath et al.

    Absolute Measurement of Surface Roughness

    Applied Optics

    (1990)
  • G. Dai et al.

    Calibration of Stylus Profilometers using Standards Calibrated by Metrological AFMs

    Journal of Physics: Conference Series

    (2005)
  • L.L. Deck et al.

    High-speed Noncontact Profiler Based on Scanning White-light Interferometry

    Applied Optics

    (1994)
  • L.L. Deck

    High Precision Interferometer for Measuring Mid-spatial Frequency Departure in Free Form Optics

    SPIE Technical Digest

    (2007)
  • P.J. de Groot et al.

    Step Height Measurements Using a Combination of a Laser Displacement Gage and a Broadband Interferometric Surface Profiler

    Proceedings of SPIE

    (2002)
  • P. de Groot et al.

    Interpreting Interferometric Height Measurements using the Instrument Transfer Function

    Proceedings FRINGE

    (2006)
  • P.J. de Groot

    Progress in the Specification of Optical Instruments for the Measurement of Surface Form and Texture

    Proceedings of SPIE

    (2014)
  • T. Estler

    Traceability

  • P. Ettl et al.

    Roughness Parameters and Surface Deformation Measured by “Coherence Radar”

    Proceedings of SPIE

    (1998)
  • C. Evans et al.

    “Structured”, “Textured”, or “Engineered” Surfaces

    CIRP Annals

    (1999)
  • C.J. Evans

    Calibration, Self-calibration and Uncertainty in Testing Optical Flats

    Proceedings of SPIE

    (2010)
  • C.J. Evans

    Clash of Cultures: Uncertainty vs. Accuracy

    Proceedings of OSA Optical Fabrication and Testing

    (2010)
  • C.J. Evans et al.

    Certification, Self–calibration and Uncertainty in Optical Surface Testing

    International Journal of Precision Technology

    (2013)
  • C. Ferri et al.

    Calibration of a White Light Interferometer for the Measurement of Micro-scale Dimensions

    International Journal of Advanced Manufacturing Technology

    (2010)
  • A.B. Forbes et al.

    Self-calibration and Error Separation Techniques in Metrology. In Advanced Mathematical and Computational Tools in Metrology V,

    (2001)
  • M.R. Foreman et al.

    Phase-Retrieved Pupil Function and Coherent Transfer Function in Confocal Microscopy

    Journal of Microscopy

    (2013)
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