Foundations of Metrology and Quality Control

Introduction

Modern manufacturing depends on the ability to make parts that conform consistently to design requirements. A shaft must fit its bearing, a gear must mesh with its mating gear, and a safety-critical component must perform reliably throughout its service life. These outcomes depend on measurement. Metrology—the science of measurement and its application—provides the concepts, standards, instruments, methods, and evidence needed to determine whether manufactured products meet specified requirements.

Quality control uses measurement information to control processes and verify products. Although inspection is an important part of quality control, quality cannot be created by inspection alone. It is achieved by designing capable processes, controlling sources of variation, selecting suitable materials and equipment, and using trustworthy measurement systems.

Metrology is therefore central to interchangeable manufacturing. Interchangeability means that a component made by one approved process can be assembled with a mating component made elsewhere without selective fitting or modification. This principle supports mass production, maintenance, global supply chains, and the replacement of worn parts.

Learning Objectives

After studying this chapter, you should be able to:

• define fundamental measurement and quality terminology;
• identify and describe a measurand;
• distinguish accuracy, precision, resolution, sensitivity, repeatability, and reproducibility;
• explain inspection, quality, conformity, and nonconformity;
• describe traceability and the role of calibration;
• relate tolerances and measurement uncertainty to interchangeable manufacture;
• explain how metrology supports quality throughout the product life cycle;
• select appropriate measurement practices for a manufacturing situation.

1. Measurement in Manufacturing

Measurement is the process of experimentally obtaining one or more quantity values that can reasonably be attributed to a quantity. In engineering practice, measurement normally involves four elements:

1. a quantity or property to be measured;
2. a measurement method and procedure;
3. a measuring instrument or system;
4. a result that includes appropriate information about reliability.

A measurement is not simply a number displayed by an instrument. The result depends on the instrument, its calibration, the environment, the operator, the workpiece, and the method used. For example, measuring a 25 mm gauge block with a micrometer requires control of temperature, cleanliness, contact force, alignment, and instrument condition.

The International System of Units (SI) provides the common language for measurement. Length is expressed in metres, mass in kilograms, time in seconds, and temperature in kelvins, although millimetres and degrees Celsius are widely used in manufacturing. Unit consistency is essential: a tolerance of 0.02 mm must not be compared directly with an uncertainty reported as 0.01 μm without conversion.

1.1 Quantity, unit, value, and indication

A quantity is a property that can be expressed numerically with a unit, such as length, angle, mass, temperature, or surface roughness. A quantity value consists of a numerical magnitude and a reference unit. For example, 40.00 mm contains the numerical value 40.00 and the unit millimetre.

An indication is the value shown by a measuring instrument. It may differ from the quantity value because of systematic effects, random variation, resolution limits, or operator influence. The indication should not automatically be treated as the true value.

A measurement result is the set of quantity values attributed to a measurand, together with relevant information such as uncertainty, units, and measurement conditions.

1.2 The measurand

The measurand is the quantity intended to be measured. Defining it precisely is a fundamental metrological task. “Diameter of a hole” may appear clear, but the actual measurand may require specification of:

• the location along the hole axis;
• whether the diameter is local, two-point, or derived from several points;
• the measurement temperature;
• the contact force or probing method;
• the reference datum and coordinate system;
• the condition of the surface and workpiece.

An incomplete measurand definition can produce a technically correct measurement of the wrong quantity. For a flexible sheet, for example, “length” may depend on the applied tension. For a threaded part, the relevant measurand may be pitch diameter rather than outside diameter.

A useful measurand statement is specific enough that different competent technicians can apply substantially the same procedure and understand what result is required.

2. Metrology and Its Structure

Metrology is commonly considered in three connected areas:

• Scientific metrology: establishes units, primary standards, and the highest levels of accuracy.
• Industrial metrology: applies measurement science to manufacturing, calibration, process control, and product verification.
• Legal metrology: applies statutory requirements to measurements affecting trade, health, safety, and consumer protection.

Industrial metrology is the principal focus of machine technology. It includes dimensional measurement, geometric measurement, surface measurement, mass, temperature, pressure, force, and specialized measurement such as optical scanning and coordinate measuring machines.

A measurement system may be represented as:

Requirement → Measurement method → Instrument and standard → Result
      ↑              ↓                    ↓                 ↓
  Tolerance ← Decision rule ← Uncertainty and traceability ← Record

The requirement establishes what must be measured. The method defines how it is measured. The instrument produces an indication, while calibration and traceability provide confidence in that indication. The result is compared with a specification using a decision rule that considers measurement uncertainty.

2.1 Standards and traceability

A measurement standard realizes, conserves, or reproduces a quantity definition or a quantity value. Examples include gauge blocks, reference masses, angle blocks, and electrical standards.

Metrological traceability is the property of a measurement result whereby the result can be related to a reference through a documented, unbroken chain of calibrations, each contributing to measurement uncertainty. Traceability is not merely possession of a calibration sticker. It requires documented links, stated uncertainties, suitable intervals, and competent calibration activities.

Calibration establishes the relationship between an instrument indication and reference values. Calibration does not necessarily adjust the instrument, and it does not automatically mean that the instrument is suitable for every application. After calibration, the user must still determine whether the instrument’s range, resolution, uncertainty, and environmental requirements are appropriate.

3. Accuracy, Error, and Uncertainty

3.1 Accuracy

Accuracy is the closeness of agreement between a measured quantity value and the true quantity value of the measurand. Accuracy is a qualitative concept; it is not normally expressed as a numerical quantity. A result can be described as more accurate than another, but “accuracy = 0.005 mm” is technically imprecise usage. A numerical specification should usually refer to error, bias, or uncertainty.

3.2 Measurement error

Measurement error is the measured quantity value minus a reference quantity value. When a reference value is available, the error may be expressed as:

where E is measurement error, x is the measured value, and x_ref is the reference value. All quantities must use the same unit. If x = 25.004 mm and x_ref = 25.000 mm, then E = +0.004 mm.

Relative error is often expressed as:

The percentage relative error is e_rel × 100%. Relative error is useful when comparing errors across different measurement magnitudes, but it becomes unsuitable when the reference value is zero or close to zero.

3.3 Systematic and random effects

Systematic effects produce a component of error that remains constant or changes predictably under specified conditions. Examples include a zero offset, a calibration correction, or thermal expansion. Systematic effects can often be estimated and corrected, although the correction itself has uncertainty.

Random effects cause variation when a measurement is repeated under specified conditions. They may arise from electrical noise, small contact-position differences, surface irregularity, or operator judgment. Repetition helps characterize random variation but does not automatically remove systematic error.

3.4 Measurement uncertainty

Measurement uncertainty is a non-negative parameter characterizing the dispersion of quantity values that could reasonably be attributed to the measurand. It reflects incomplete knowledge, not a mistake. Sources may include reference standards, instrument resolution, repeatability, temperature, alignment, material deformation, and the measurement model.

For independent standard uncertainty components u₁, u₂, …, uₙ, a commonly used combined standard uncertainty is:

This root-sum-square relationship assumes that the components are expressed as standard uncertainties and are uncorrelated. If components are correlated, covariance terms must be included. An expanded uncertainty is commonly reported as:

where k is a coverage factor selected for the intended coverage probability and assumptions. In many approximately normal situations, k ≈ 2 provides coverage of about 95%, but this is not universal. A reported result should state the value of k or the coverage probability.

Worked Example: Combining uncertainty components

A diameter measurement has the following independent standard uncertainty components:

• calibration: 0.003 mm;
• repeatability: 0.004 mm;
• temperature effect: 0.002 mm.

Thus:

Using k = 2:

The result may therefore be reported in the form x ± 0.011 mm, with the statement that the expanded uncertainty uses k = 2. The calculation is valid only under the stated independence and uncertainty-distribution assumptions.

4. Precision, Resolution, Sensitivity, and Stability

4.1 Precision

Precision is the closeness of agreement among indications or measured quantity values obtained by repeated measurements. High precision means low dispersion; it does not guarantee closeness to the reference value. A miscalibrated micrometer can give highly precise but inaccurate results.

Precision has two important conditions:

• Repeatability: precision under repeatability conditions—same procedure, operator, measuring system, location, and short time interval.
• Reproducibility: precision under changed conditions, such as different operators, instruments, locations, or times.

Repeatability studies help identify short-term measurement variation. Reproducibility studies reveal whether results depend on operator technique, equipment, laboratory, or environmental conditions.

4.2 Resolution

Resolution is the smallest change in a quantity being measured that causes a perceptible change in the corresponding indication. A digital instrument displaying 0.001 mm has a display increment of 0.001 mm, but its effective measurement capability may be poorer because of noise, calibration error, and environmental effects. Resolution is therefore not equivalent to accuracy or uncertainty.

4.3 Sensitivity

Sensitivity is the change in indication divided by the corresponding change in the quantity being measured:

where S is sensitivity, ΔI is the change in indication, and ΔQ is the change in the measured quantity. The units depend on the instrument. For an ideal linear displacement instrument, a sensitivity of 1.0 mm/mm means that a 0.1 mm change in input produces a 0.1 mm indication change. Sensitivity may vary across an instrument’s range.

4.4 Stability and drift

Stability is the property of a measuring system whereby its metrological properties remain constant with time. Drift is a gradual change in indication or calibration behavior. Wear, contamination, aging electronics, temperature cycles, and mechanical damage can cause drift. Calibration intervals should be based on risk, historical performance, usage, manufacturer information, and regulatory requirements—not on an arbitrary calendar alone.

5. Inspection, Testing, and Conformity

Inspection is the evaluation of conformity by observation and judgment, accompanied as appropriate by measurement, testing, or comparison. Inspection may occur at incoming receipt, during production, at final release, or during maintenance.

Testing determines one or more characteristics according to a procedure. Inspection commonly asks whether a requirement is met, whereas testing may investigate performance under specified conditions. Both require defined methods and controlled equipment.

A specification states requirements. A tolerance defines the permissible variation of a characteristic. For a shaft specified as 20.000 ± 0.010 mm, the nominal size is 20.000 mm and the limiting values are 19.990 mm and 20.010 mm, assuming the specification is interpreted symmetrically.

Conformity is fulfillment of a specified requirement. Nonconformity is failure to fulfill a requirement. A product may be within a dimensional tolerance but still nonconforming because of incorrect material, surface damage, missing documentation, or an unapproved process.

5.1 Decision rules and guard bands

A conformity decision compares a measurement result with specification limits. When uncertainty is significant relative to the tolerance, a result close to a limit may not support a simple “pass” or “fail” conclusion. A decision rule defines how measurement uncertainty is considered.

Under a simple acceptance rule, a part is accepted when the observed result lies within the specification limits, without an explicit guard band. This rule risks accepting some nonconforming parts and rejecting some conforming parts when uncertainty is present. A guard band narrows the acceptance zone to reduce the probability of false acceptance, but it may increase false rejection. The rule must be agreed with the customer, standard, or responsible authority and recorded before decisions are made.

5.2 Attribute and variable inspection

Variable inspection records numerical values, such as 19.998 mm. It provides more information and supports process analysis. Attribute inspection classifies a result, such as pass/fail or conforming/nonconforming. It can be efficient but may conceal trends and the magnitude of variation.

Sampling inspection evaluates selected units from a lot. It reduces inspection effort but introduces sampling risk. A sound sampling plan specifies the lot, sample size, selection method, acceptance criteria, and treatment of rejected lots. Sampling does not improve a poor process; it only provides evidence about the lot.

6. Quality and Quality Control

Quality is the degree to which a set of inherent characteristics fulfills requirements. It is not identical to luxury, price, or visual appearance. A low-cost component can have high quality if it consistently fulfills its intended requirements, while an expensive component can be poor quality if it fails to perform.

Quality control is the part of quality management focused on fulfilling quality requirements. It includes operational techniques, inspection, testing, process monitoring, corrective action, and the use of data to control variation.

Quality assurance provides confidence that quality requirements will be fulfilled through planned and systematic activities. Quality management is the broader coordinated activity that directs and controls an organization with regard to quality. In practice, these concepts overlap, but their emphasis differs:

The fundamental distinction is that inspection detects problems, while process control seeks to prevent them. Measurement supports both activities.

7. Metrology and Interchangeable Manufacturing

Interchangeable manufacture requires controlled dimensions and geometrical relationships. A hole and shaft do not need to be exactly equal to nominal size; they need compatible limits that produce the intended fit. Dimensional tolerancing establishes those limits, while metrology determines whether production remains within them.

A tolerance width is the difference between the upper and lower limits:

where T is tolerance width and L_max and L_min are the upper and lower specification limits. For 20.010 mm and 19.990 mm, T = 0.020 mm.

Tolerances should be achievable by the manufacturing process and measurable with suitable uncertainty. A very narrow tolerance may increase machining, inspection, and rejection costs. A very wide tolerance may cause poor fit or reduced performance. Tolerance selection is therefore a design, manufacturing, and metrology decision rather than a drafting detail alone.

Geometrical tolerancing controls form, orientation, location, and run-out. A component can have correct size but still fail because it is out of round, tapered, misaligned, or poorly positioned. Coordinate measuring machines, form testers, optical systems, gauges, and dedicated fixtures may be selected according to the feature and required uncertainty.

8. Measurement System Selection and Good Practice

A suitable measurement system is selected by considering:

• the measurand and its tolerance;
• required accuracy and uncertainty;
• range and resolution;
• measurement speed and production volume;
• workpiece material, geometry, and surface condition;
• environmental conditions;
• operator skill and ergonomic risks;
• calibration and traceability requirements;
• cost, maintenance, and data-management needs.

A practical measurement procedure should define preparation, instrument identification, reference standards, environmental conditions, datum selection, contact force, number and location of readings, calculation method, acceptance rule, and record retention.

Common good practices include cleaning contact surfaces, allowing workpieces and instruments to reach thermal equilibrium, avoiding excessive force, aligning the instrument with the feature, checking zero before use, using appropriate fixturing, and recording raw observations rather than only final decisions.

For a steel length measured at a temperature different from the reference temperature, thermal expansion may be relevant. A simplified linear relation is:

where ΔL is change in length, α is the coefficient of linear thermal expansion, L₀ is the reference length, and ΔT is the temperature difference. This approximation assumes uniform temperature and small expansion. For a 100 mm steel part with α = 11.5 × 10⁻⁶ /°C and ΔT = 10 °C:

A temperature difference that appears modest can therefore be significant when the tolerance is only a few micrometres.

9. Measurement System Evaluation

Before using data for process decisions, the measurement system itself should be evaluated. A measurement system analysis may examine bias, stability, repeatability, reproducibility, linearity, and resolution. A gauge repeatability and reproducibility study, often called a Gage R&R study, estimates variation associated with the equipment and appraisers.

A measurement system should be capable of distinguishing meaningful differences in the process. If measurement variation is large compared with product tolerance or process variation, the organization may make incorrect decisions, hide process trends, or argue about results that the system cannot reliably distinguish.

Measurement-system improvement may involve better fixturing, operator training, environmental control, instrument selection, calibration, automated data collection, or a clearer procedure. Replacing an instrument with one having more decimal places does not necessarily solve the problem.

10. Lifecycle Quality

Metrology contributes at every stage of a product’s life cycle:

• Design: establishes functional requirements, datums, tolerances, and verification methods.
• Process planning: selects machines, tooling, gauges, inspection points, and control plans.
• Production: monitors dimensions, detects drift, and supports adjustment.
• Acceptance: provides objective evidence of conformity.
• Assembly: verifies interfaces and supports interchangeability.
• Service and maintenance: confirms wear, alignment, and replacement-part compatibility.
• Failure analysis: supplies evidence about dimensional, material, or process causes.
• Retirement and improvement: provides feedback for redesign and process learning.

Digital manufacturing increases the importance of measurement data. Coordinate measuring machines, machine vision, laser scanners, in-process probes, and connected sensors can produce large data sets. However, data volume does not guarantee knowledge. Measurement systems must remain calibrated, data must be associated with part identity and conditions, and access must be controlled.

Artificial intelligence can assist with anomaly detection, predictive maintenance, image-based inspection, and compensation of process drift. Its outputs should not be treated as unquestionable evidence. Training data, false positives, false negatives, model changes, cybersecurity, and human oversight must be addressed. In safety-critical applications, AI-assisted decisions require validation and a clearly defined responsibility structure.

11. Case Study: Dimensional Control of a Bearing Housing

The following is an illustrative case based on a typical manufacturing situation.

Background

A manufacturer produces aluminium bearing housings for an automated assembly line. The bore specification is 50.000 ± 0.015 mm. The bore must accept a standardized bearing without forceful assembly, while excessive clearance would reduce alignment and service life.

Problem

Customer complaints indicate intermittent assembly difficulty. Production records show that final inspection results are mostly within limits, but different inspectors report different values for the same parts.

Analysis

An investigation identifies several possibilities: temperature differences between the machining area and inspection room, inconsistent cleaning, variation in bore measurement location, and inadequate alignment of the internal-diameter instrument. The instrument display resolution is 0.001 mm, but no recent repeatability and reproducibility study is available.

Ten housings are measured twice by three inspectors using the existing instrument. The results show substantial differences between inspectors. A reference ring indicates a small positive bias, and the bore has measurable taper that is not detected when only one axial location is measured.

The central issue is not simply whether individual readings lie between 49.985 mm and 50.015 mm. The measurement method does not adequately define the measurand or capture the bore geometry relevant to assembly.

Approach and solution

The company takes the following actions:

1. defines the measurand as bore diameter at specified axial sections and angular positions;
2. cleans and thermally stabilizes parts before measurement;
3. introduces a fixture that aligns the instrument with the bore axis;
4. uses a calibrated setting ring and records the correction;
5. measures several locations to detect taper and out-of-roundness;
6. trains inspectors using a common procedure;
7. conducts a new measurement-system study;
8. adds in-process probing to detect tool wear before final inspection;
9. establishes a documented decision rule for results near specification limits.

Outcome

The revised study shows substantially lower operator-related variation. Process data reveal gradual bore growth as the cutting tool wears. Tool replacement is scheduled from measured condition rather than a fixed number of parts. Assembly complaints decline, and the manufacturer gains evidence that final inspection results are comparable across shifts.

Learning points

The case demonstrates that quality problems may originate in the measurement system rather than solely in the manufacturing process. It also shows why a nominally adequate resolution, a calibration certificate, and an apparent pass result do not by themselves establish reliable conformity. Clear measurands, controlled conditions, capable methods, and process feedback are all necessary.

12. Limitations, Ethics, and Governance

Measurement decisions can affect worker safety, customer confidence, financial loss, and legal compliance. Records must not be altered to obtain a desired acceptance outcome. If an instrument is found out of calibration, the organization should assess potentially affected products and document the evaluation.

Important governance practices include controlled procedures, authorized personnel, equipment identification, calibration records, environmental records where relevant, secure data storage, audit trails, and clear responsibility for release decisions. Results should be reported honestly, including limitations and uncertainty when they influence interpretation.

A competent inspector must remain impartial. Pressure to meet production targets must not override evidence of nonconformity. Conversely, unnecessary rejection caused by a poorly understood or excessively conservative method can waste resources and damage supplier relationships. Sound metrology supports fair decisions for both producer and customer.

Contemporary Developments and Best Practices

Current industrial practice is moving toward connected and model-based metrology. Digital twins can link design requirements, process data, and inspection results. Inline optical and tactile sensors can detect variation earlier than end-of-line inspection. Automated statistical monitoring can identify drift, while advanced manufacturing requires three-dimensional characterization of complex surfaces.

Best practice remains grounded in basic principles:

• define the measurand before selecting an instrument;
• use traceable standards and suitable calibration;
• distinguish accuracy, precision, resolution, and uncertainty;
• control environmental and operator influences;
• verify measurement-system capability;
• use a documented decision rule;
• preserve raw data and measurement conditions;
• use measurement results to improve the process, not merely sort products;
• review the method when design, material, machine, or software changes;
• maintain professional independence and data integrity.

Chapter Summary

Metrology is the science and application of measurement, while quality control uses measurement and other operational techniques to fulfill requirements. A valid measurement begins with a clearly defined measurand and a suitable method. The indication from an instrument is not automatically the true value; calibration, traceability, environmental control, and uncertainty must be considered.

Accuracy describes closeness to a reference value, whereas precision describes agreement among repeated results. Repeatability concerns unchanged conditions, while reproducibility considers changed conditions. Resolution is the smallest perceptible input change, and sensitivity relates a change in indication to a change in the measured quantity. None of these terms alone proves that a measurement system is fit for purpose.

Inspection determines conformity, but inspection alone cannot create quality. Effective quality control combines capable processes, suitable measurement systems, statistical evidence, corrective action, and lifecycle feedback. Tolerances and geometrical requirements make interchangeable manufacturing possible, provided that the manufacturing process and measurement system can achieve and verify them.

Finally, metrology supports design, production, assembly, maintenance, failure analysis, and continual improvement. Reliable measurement is technical evidence and must therefore be governed by competence, traceability, documented methods, ethical conduct, and appropriate consideration of uncertainty.

Key Terms

Metrology: The science of measurement and its application.

Measurand: The quantity intended to be measured.

Measurement result: A value attributed to a measurand together with relevant supporting information.

Indication: The value shown or provided by a measuring instrument.

Accuracy: Closeness of agreement between a measured value and a reference value.

Precision: Closeness of agreement among repeated measured values.

Measurement error: The measured value minus a reference value.

Measurement uncertainty: A parameter describing the dispersion of values reasonably attributable to a measurand.

Resolution: The smallest change in the measured quantity that produces a perceptible indication change.

Sensitivity: Change in indication divided by the corresponding change in measured quantity.

Repeatability: Precision under unchanged measurement conditions.

Reproducibility: Precision under changed specified conditions.

Calibration: Establishment of a relationship between instrument indications and reference values.

Traceability: Relationship of a result to a reference through a documented calibration chain.

Inspection: Evaluation of conformity by observation, measurement, testing, or comparison.

Conformity: Fulfillment of a specified requirement.

Nonconformity: Failure to fulfill a specified requirement.

Tolerance: Permissible variation of a specified characteristic.

Interchangeability: Ability to assemble compatible components without selective fitting or modification.

Quality control: Operational techniques used to fulfill quality requirements.

Review Questions

Short Answer Questions

1. What is a measurand, and why must it be defined precisely?
2. Distinguish accuracy from precision.
3. What is the difference between repeatability and reproducibility?
4. Why is resolution not the same as measurement uncertainty?
5. What is meant by metrological traceability?

Long Answer Questions

1. Explain the role of calibration, standards, and uncertainty in industrial measurement.
2. Discuss how metrology enables interchangeable manufacturing.
3. Compare inspection, quality assurance, quality control, and quality improvement.
4. Explain the principal sources of measurement variation and methods for controlling them.
5. Describe how metrology contributes throughout the product life cycle.

Analytical / Application Questions

1. A component has a tolerance of ±0.010 mm, but the measurement system has an expanded uncertainty of ±0.012 mm. Analyze the risks of making conformity decisions and recommend actions.
2. An instrument gives nearly identical readings for repeated measurements, but all readings are 0.020 mm larger than a calibrated reference. Diagnose the measurement behavior and propose corrective actions.
3. Design a measurement procedure for a precision bore used in an interchangeable assembly. State the measurand, environmental controls, instrument requirements, sampling plan, records, and decision rule.

Multiple Choice Questions with Answers

Question 1

Which statement best defines a measurand?

A. The smallest display increment of an instrument

B. The quantity intended to be measured

C. The error found during calibration

D. The permissible variation in a specification

Correct Answer: B. The quantity intended to be measured

Question 2

A micrometer produces readings of 20.004, 20.005, and 20.004 mm, while the reference value is 20.000 mm. What characteristic is demonstrated most directly?

A. High precision with a positive bias

B. Low precision with zero bias

C. High accuracy with low resolution

D. Poor repeatability with no systematic effect

Correct Answer: A. High precision with a positive bias

Question 3

Which term describes precision under the same operator, instrument, method, and short time interval?

A. Accuracy

B. Reproducibility

C. Repeatability

D. Sensitivity

Correct Answer: C. Repeatability

Question 4

An instrument has a sensitivity of 2 mm/mm. If the input quantity changes by 0.05 mm, what indication change is expected under linear conditions?

A. 0.025 mm

B. 0.05 mm

C. 0.10 mm

D. 2.05 mm

Correct Answer: C. 0.10 mm

Question 5

For independent standard uncertainty components of 0.003 mm and 0.004 mm, what is the combined standard uncertainty?

A. 0.001 mm

B. 0.005 mm

C. 0.007 mm

D. 0.012 mm

Correct Answer: B. 0.005 mm

Question 6

A shaft has specification limits of 19.990 mm and 20.010 mm. What is its tolerance width?

A. 0.010 mm

B. 0.020 mm

C. 19.990 mm

D. 20.010 mm

Correct Answer: B. 0.020 mm

Question 7

Which statement about calibration is correct?

A. Calibration always adjusts an instrument

B. Calibration proves that an instrument is suitable for every application

C. Calibration establishes a relationship between indication and reference values

D. Calibration eliminates all measurement uncertainty

Correct Answer: C. Calibration establishes a relationship between indication and reference values

Question 8

Why can a part with a correct size still be nonconforming?

A. Size is never relevant to conformity

B. Geometrical, material, surface, or documentation requirements may also apply

C. All conforming parts must be exactly nominal size

D. Inspection is unrelated to specifications

Correct Answer: B. Geometrical, material, surface, or documentation requirements may also apply

Question 9

Which action most directly improves the reliability of bore measurements in the case study?

A. Reading only one location more quickly

B. Increasing the number of decimal places on the display

C. Defining measurement locations and controlling alignment and temperature

D. Discarding all results near the nominal size

Correct Answer: C. Defining measurement locations and controlling alignment and temperature

Question 10

What is the principal purpose of a decision rule in conformity assessment?

A. To define how measurement results and uncertainty are compared with specification limits

B. To increase the nominal size of every component

C. To replace calibration with visual inspection

D. To ensure that every part is exactly at nominal size

Correct Answer: A. To define how measurement results and uncertainty are compared with specification limits