ASM Metals HandBook Vol. 17 - Nondestructive Evaluation and Quality Control
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Fig. 12 Example of a CAD-generated display of inspectability (POD) as a function of pos
ition within the cross
section of a simulated disk. The POD scale ranges from black for the lowest to white for the highest POD values.
The low POD in the fillet region is due to the combination of a coarse scan mesh and a tight fillet radius.
Fig. 13 A display similar to the one shown in Fig. 12
, except that the scan mesh has been refined and the fillet
has a larger radius of curvature. The combination of scan plan and component design modification has
significantly improved inspectability throughout the disk.
Example 1: Integration of an Ultrasonic Reliability Model with a CAD System.
Figures 12 and 13 show the result of a computer simulation of ultrasonic POD for oblate spheroidal inclusions in a
rotationally symmetric component, such as a jet engine turbine disk. The display shows the results obtained from a cross
section of the component, and the gray shades refer to the POD value, in the range from zero to unity, with black being
the lowest and white the highest POD values. In the POD simulation, the inclusions were assumed to have a preferential
orientation with their largest face parallel to the component surface, and the component was assumed to be scanned in
pulse-echo mode with a focused probe normal to the surface of the part and focused at the surface. The interior points of
the component, at which the POD values were calculated, were defined to be the nodes of an automatically generated
finite-element mesh that was imposed on the solid model of the part. This artifice allowed the built-in postprocessing
graphical interface of the CAD package to be used to display the inspectability results in a format that would be very
familiar to a designer who is experienced in the use of the package.
Figure 12 shows the result of a nominal scan plan and component design. In particular, the scan mesh was quite coarse,
causing poor detectability in the web section to the right of the cross section and near the surface of the entire component.
The fillet region, at the juncture between the web and the thicker bore area to the left of the cross section, was also
assumed to have a small radius of curvature. Below this fillet region, the POD values are quite low, which is a result of
the combination of the ultrasonic beam being focused on the surface of the part and of the focusing effect of the surface
curvature. This caused the fields in the region below the fillet to be rapidly diverging and therefore of low amplitude.
To improve the POD levels throughout the component, two questions must be considered. The first is whether the
inspection technique was optimized with respect to the design of the component, and the second is whether the design
itself is inspection limited. The first question is crucial because a simple modification of the scan plan will almost
certainly be a better solution than the change in operational characteristics of the component created by a modification of
its design. In some cases, however, both the scan plan and the design will require optimization. Figure 13 shows the result
of both options; the scan mesh was refined, which caused the enhanced POD in the near-surface and web regions, and the
fillet radius of curvature was increased, which improved the POD in the fillet region.
Example 2: Implications on Standardization.
As the design applications of reliability models become more widespread, the questions of quantitative standards will
become more important. Because the manufacturer will usually be at a remote location from the designer and may be
affiliated with a different organization, it will be necessary to communicate the inspection procedure at the time that
manufacturing procedures are specified. Absolute calibration standards will then be essential to ensure that the inspection,
including specified thresholds, is properly set up and implemented. This may require a move away from the use of
reference reflectors, such as flat-bottom holes (Ref 44, 45). Recent work in ultrasonics has shown how the measurement
model, Eq 3, can be used as the basis for such a procedure (Ref 46).
Example 3: Uses of Artificial Intelligence in Optimization.
An important part of the consideration of inspectability in CAD procedures is optimization of the inspection and/or
design. This was done intuitively by a highly trained operator in Example 1. However, in the future, it may be desirable to
eliminate the operator through the use of artificial intelligence techniques, such as expert systems. Although this has not
yet been accomplished, a step in that direction has been the use of the ultrasonic measurement model in the development
of an expert system to differentiate cracklike flaws from volumetric flaws (Ref 47).
References cited in this section
8. D.O.
Thompson and T.A. Gray, The Role of NDE in Global Strategies for Materials Synthesis and
Manufacturing, Proceedings of the 1988 Fall Meeting, Materials Research Society, in press
44.
B.R. Tittmann and D.O. Thompson, Approach to a Self-Consistent Calibrat
ion Procedure of an Ultrasonic
System, Mater. Eval., Vol 35, 1977, p 96-102
45.
B.R. Tittmann, D.O. Thompson, and R.B. Thompson, Standards for Quantitative Nondestructive
Evaluation, in Nondestructive Testing Standards--A Review, M. Berger, Ed., STP 624,
American Society for
Testing and Materials, 1977, p 295-311
46.
D.D. Bennink and A.L. Pate, Investigation of Scatter in Ultrasonic Responses Caused by Variability in
Transducer and Material Properties, in Review of Progress in Quantitative Nondestructive Evaluation,
Vol
7A, D.O. Thompson and D.E. Chimenti, Ed., Plenum Press, 1988, p 621-628
47.
S.W. Nugen, K.E. Christensen, L.-S.Koo, and L.W. Schmerr, FLEX-
An Expert System for Flaw
Classification and Sizing, in Review of Progress in Quantitative Nondestructive Evaluation,
Vol 7A, D.O.
Thompson and D.E. Chimenti, Ed., Plenum Press, 1988, p 445-451
Models for Predicting NDE Reliability
J.N. Gray, T.A. Gray, N. Nakagawa, and R.B. Thompson, Center for NDE, Iowa State University
References
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Techniques, Philos. Trans. R. Soc. (London) A, Vol 320, 1986, p 329-340
3. R.B. Thompson and H.N.G. Wadley, The Use of Elastic Wave-
Material Structure Interaction Theories in
NDE Modeling, CRC Crit. Rev. Solid State Mater. Sci., in press
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Quantitative Prediction of Ultrasonic Defect Detection and Sizing, Nucl. Energy, Vol 22, 1983, p 319-333
5. R.B. Thompson, D.O. Thompson, H.M. Burte, and D.E. Chimenti, Use of Field-
Flaw Interaction Theories
to Quantify and Improve Inspection Reliability, in
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NDE in Global Strategies for Materials Synthesis and
Manufacturing, Proceedings of the 1988 Fall Meeting, Materials Research Society, in press
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B.A. Auld, General Electromechanical Reciprocity Relations Applied to the Calculation of Elastic Wave
Scattering Coefficients, Wave Motion, Vol 1, 1979, p 3
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Solid Interfaces to Unbounded Medium Scattering Amplitudes, J. Acoust. Soc. Am., Vol 74, 1983, p 1279
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R.B. Thompson and T.A. Gray, Analytical Diffraction Corrections to Ultrasonic Scattering Measurements,
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Chimenti, Ed., Plenum Press, 1983, p 567
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R.B. Thompson, T.A. Gray, J.H. Rose, V.G. Kogan, and E.F. Lopes, The Radiation of Elliptical and
Bicylindrically Focused Piston Transducers, J. Acoust. Soc. Am., Vol 82, 1987, p 1818
14.
B.P. Newberry and R.B. Thompson, A Paraxial Theory for the Propagation of Ultrasonic Beams in
Anisotropic Solids, J. Acoust. Soc. Am., to be published
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Media Ultrasonic Inspection, in Review of Progress in Quantitative Nondestructive Evaluation,
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Isotropically Elastic Solid, J. Appl. Phys., Vol 27, 1956, p 1086
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J.L. Opsal and W.M. Visscher, Theory of Elastic Wave Scattering: Applications of the Method of Optimal
Truncation, J. Appl. Phys., Vol 58, 1985, p 1102
18. J.-S. Chen and L.W. Schmerr, Jr., The Scattering Response of Voids--
A Second Order Asymptotic Theory,
in Review of Progress in Quantitative NDE,
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1988, p 139
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Laguerre/Hermite Formulation for the Nearfield of an
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24. M. Burrows, "A Theory of Eddy Current Flaw Detection," Ph.D. thesis, University of Michigan, 1964
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26. A.H. Kahn, R. Spal, and A. Feldman, Eddy-
Current Losses Due to a Surface Crack in a Conducting
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27. W.D. Dover, F.D.W. Charlesworth, K.A. Taylor, R. Collins, and D.H. Michael, in
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Crack Length and Shape during Fatigue and Fracture, C.J. Beevers, Ed., EMAS, 1980
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29. T.G. Kincaid, A Theory of Eddy Current NDE for Cracks in Nonmagnetic Materials, in
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Progress in Quantitative NDE, Vol 1, D.O. Thompson and D.E. Chimenti, Ed., Plenum Press, 1982
30. A.J. Bahr, System Analysis of Eddy-Current Measurements, in Review of Progress in Quantitative NDE,
Vol 1, D.O. Thompson and D.E. Chimenti, Ed., Plenum Press, 1982; A.J. Bahr and D.W. Cooley, Analysis
and Design of Eddy-Current Systems, in Review of Progress in Quantitative NDE,
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1983; J.R. Martinez and A.J. Bahr, Statistical Detection
Model, in Review of Progress in Quantitative NDE,
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31. B.A. Auld, F.G. Muennemann, and D.K. Winslow, J. Nondestr. Eval., Vol 2, 1982,
p 1; B.A. Auld, F.G.
Muennemann, and M. Riaziat, Quantitative Modeling of Flaw Responses in Eddy Current Testing, in
Research Techniques in Nondestructive Testing, Vol 7, R.S. Sharpe, Ed., Academic Press, 1984
32. R.E. Beissner, Boundary Element Model of Eddy Current Flaw Detection in Three Dimensions,
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Phys., Vol 60, 1986, p 352-360; Analytical Green's Dyads for an Electrically Conducting Half-Space,
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34. R.E. Beissner, K.A. Bartels, and J.L. Fisher, Prediction of the Probability of Ed
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38. J.N. Gray, F. Inanc, and B.E. Shull, Three Dimensional Modeling of Projection Radiography, in
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39. D.E. Rundquist, in Research Techniques in Nondestructive Testing,
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40. C.M. Lee, L. Kissell, R.H. Pratt, and H.K. Tseng, Phys, Rev., Vol A13 (No. 5), 1976, p 1714-1727
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44. B.R. Tittmann and D.O. Thompson, Approach to a Self-
Consistent Calibration Procedure of an Ultrasonic
System, Mater. Eval., Vol 35, 1977, p 96-102
45.
B.R. Tittmann, D.O. Thompson, and R.B. Thompson, Standards for Quantitative Nondestructive
Evaluation, in Nondestructive Testing Standards--A Review,
M. Berger, Ed., STP 624, American Society
for Testing and Materials, 1977, p 295-311
46.
D.D. Bennink and A.L. Pate, Investigation of Scatter in Ultrasonic Responses Caused by Variability in
Transducer and Material Properties, in Review of Progress in Quantitative Nondestructive Evaluation,
Vol
7A, D.O. Thompson and D.E. Chimenti, Ed., Plenum Press, 1988, p 621-628
47. S.W. Nugen, K.E. Christensen, L.-S.Koo, and L.W. Schmerr, FLEX-
An Expert System for Flaw
Classification and Sizing, in Review of Progress in Quantitative Nondestructive Evaluation,
Vol 7A, D.O.
Thompson and D.E. Chimenti, Ed., Plenum Press, 1988, p 445-451
Statistical Quality Design and Control
Richard E. DeVor, University of Illinois, Urbana-Champaign; Tsong-how Chang, University of Wisconsin, Milwaukee
Introduction
A MAJOR REVOLUTION in the industrial sector has been taking place in America during the 1980s as manufacturers
strive to regain the competitive position they once held in the world marketplace. One element of this revolution has
centered around a renewed emphasis on quality, with an approach aimed at preventing defective materials from being
manufactured through improved process monitoring and diagnosis and at designing quality into the product from the very
beginning. The concepts and methods of Deming and others have had a profound impact on the way quality is viewed
from the manufacturing/process perspective. The simple but powerful statistical methods for process control developed by
Shewhart some time ago have been successfully revived and applied on a very broad basis. In the engineering design
arena, the methods of Taguchi, referred to as off-line quality control, have been successfully used for more than 30 years
to provide a sound basis for improved product/process design. From the total system point of view, the concept of
company-wide quality control, which has been practiced in Japan for some time, is now receiving considerable attention.
In particular, recent emphasis has been placed on quality function deployment as a means to transmit customer needs
through the organization both vertically and horizontally.
The work of Shewhart in the 1920s led to a sound approach to the scrutiny of process variation and the diagnosis and
removal of process faults. However, the statistical approach to the sampling of process output prior to shipping to
determine the extent to which it conformed to specifications dominated the quality field from the 1930s through the
1970s. Unfortunately, it has only recently been recognized that this product control approach to quality control
contributes little to the enhancement of competitive position. The recognition that quality and productivity can move
together in the right direction only when the process is evaluated, finding the root cause of process faults and taking
action to remove them, is today reshaping the meaning and intent of quality control.
The dramatic change in the meaning and application of quality control as a discipline has both a philosophical and an
analytical side. These two aspects of the problem must be understood together. This article will present some fundamental
elements of statistical thinking and methods for quality design and control. Commonly used techniques employing control
charts and the design of experiments are discussed with illustrations.
Acknowledgement
This article was adapted from R.E. DeVor and T-H. Chang, Statistical Quality Design and Control: Contemporary
Concepts and Methods, Macmillan.
Statistical Quality Design and Control
Richard E. DeVor, University of Illinois, Urbana-Champaign; Tsong-how Chang, University of Wisconsin, Milwaukee
Quality and Productivity Fundamentals
Dr. W. Edwards Deming is the man largely responsible for bringing statistical thinking and methods for quality
improvement to Japan after World War II. An eminent statistician in America during the 1930s and 1940s, Deming was
one of the men in the forefront of the statistical quality control scene during World War II. After the war, Deming's
philosophies and teachings fell on the deaf ears of American management, and the quality effort fires that burned so
brightly during the war years slowly went out. However, the Japanese became aware of Deming's work and invited him to
Japan, where he met with and caught the attention of top management.
When Deming first traveled to Japan in the late 1940s, he found a climate that was quite conducive to the promotion of
his concepts and methods. On the one hand, Japan appeared to have a solid base of statistical expertise, although its
energies had been directed primarily toward mathematical theory and the application of that theory in nonmanufacturing
environments such as agriculture. On the other hand, Deming found an industrial leadership base in Japan very eager to
listen to what he had to say. With the lessons learned from his experience in attempting to promote quality improvement
in America, Deming's first order of business when he arrived in Japan was to conduct a series of top management training
seminars in which he laid out what needed to be done to place quality improvement on an institutional basis within any
organization. The obligations and responsibilities of management that he spelled out in these seminars came to be known
as his Fourteen Points for management.
Perhaps it is the combination of upper management perspective and a firmly rooted background in mathematical statistics
that has enabled Deming to sustain his efforts in a leadership position over more than 50 years. He has been able to tell
management what they ought to do and then to provide the rigorous analytical tools and methods needed to carry out his
directions. His teachings are heavily oriented toward the use of statistical thinking and methods to identify opportunities
for quality and productivity improvement. Deming has developed a road map for management to follow to enhance
competitive position over the long run. This road map, referred to as his Fourteen Points (management's obligations), is
summarized below. It should be noted that in the spirit of his Fourteen Points, Deming continues to this day to refine and
improve these tenets. As a result they themselves are continually changing. An excellent discussion of Deming's Fourteen
Points is provided in Ref 1. Deming's Fourteen Points are listed below:
• Create constancy of purpose for the improvement of product or service
• Adopt the new philosophy of process control and variation reduction
• Cease dependence on mass inspection for quality control
• End the practice of awarding business on the basis of price
•
Improve constantly and forever the system of production and service in order to improve quality and
productivity and thus continuously decrease costs
• Institute thorough and better job-related trainings
• Institutionalize leaderships
• Drive out fears, so that everyone may work effectively for the company
• Break down barriers between departments
•
Eliminate slogans, exhortations, and targets for the workforce that ask for zero defects and new levels of
productivity
• Eliminate work standards on the factory floor
•
Remove the barriers that rob employees at all levels in the company of their right to pride of
workmanship
• Institute a vigorous program of education and self-improvement
• Put everybody in the organization to work to accomplish the transformation
The Fourteen Points are clearly the responsibility of management. They define the essential elements of the
institutionalization of quality and productivity improvement through statistical thinking and methods. Other pioneers in
quality planning and management include Dr. J.M. Juran (Ref 2) and Dr. A.V. Feigenbaum (Ref 3).
Quality and Engineering Specifications
In today's economic age, it is simply impractical to use concepts and measures of quality that do not relate the
achievement of function in the field to the engineering design process. Definitions of quality that promote improvement to
some acceptable plateau of performance will inhibit the continual pursuit of never-ending improvement and will therefore
have a weak and perhaps opposing relationship to process performance in terms of efficiency/productivity. Instead, to
improve competitive position, the definition of quality should emphasize:
• A design criterion to provide a quantitative basis to move the quality issue upstream to engi
neering
design
•
Prevention rather than containment to promote focus on the process, not the product, in a manufacturing
sense
• Continual pursuit of never-
ending improvement to be strongly tied to, and therefore promote, the issue
of productivity
• Consumer
versus producer orientation to quantify/measure the loss imparted to the customer as a result
of poor quality rather than the loss imparted to the producer
The traditional definitions of quality often fall short in terms of their ability to articulate quality in a way that can foster
improvement in competitive position. In particular, the association of quality with conformance to the engineering
specification puts the measurement of quality on an attribute basis and provides little more than a shipping criterion when
it is essential that quality be articulated in a manner that enables it to be used as a design criterion. The view of quality as
conformance to specifications promotes the product control approach to quality control and therefore stands as a
significant inhibitor to the adoption of a process control approach to manufacturing and the integration of quality and the
design process.
Figure 1 illustrates the traditional interpretation of the engineering specification. Figure 1(a) and 1(b), two representations
of a process as a statistical distribution of measurements are shown relative to a certain bilateral specification. Although
the bell-shaped process distribution in Fig. 1(a) might be preferred to the more loaf-shaped process distribution in Fig.
1(b), there generally would not be much distinction between the two cases in terms of quality; that is, in both cases,
virtually all the processes/parts are conforming to the specifications.
Fig. 1 Graphical depiction of three traditional interpretations of engineering specifications.
(a) Desirable. (b)
Acceptable. (c) Nominal
When one begins to consider the dots labeled A, B, and C as representing three different manufactured parts in Fig. 1(c),
part A is generally interpreted as unacceptable because it is outside the specifications, while parts B and C are considered
acceptable because they are within the specifications. The crucial point in this interpretation is the fact that a distinction is
generally not made between parts B and C so far as quality is concerned. In fact, it is unlikely that there is very much
difference between parts A and B in terms of functional performance, while part C will likely perform considerably better
than either A or B.
Loss Function Concept
The methods of Taguchi have provided a whole new perspective on the way the engineering design process is viewed and
have provided further support to the methods of design of experiments for quality design and improvement (Ref 4, 5). The
design of experiments as a discipline has a rich and extensive history that finds its origin in the work of Sir Ronald Fisher
during the first quarter of the 20th century (Ref 6). From an industrial point of view, the work of Dr. G.E.P. Box and his
coworkers has left an indelible mark on the design of experiments in particular and the theory and practice of industrial
statistics in general (Ref 7, 8).
The Taguchi approach to quality engineering has a number of significant strengths. In particular, Taguchi has placed a
great deal of emphasis on the importance of minimizing variation as the primary means of improving quality. The
concepts of designing products such that the performance of each is insensitive to environmental conditions and making
this happen at the design stage through the use of design of experiments have been cornerstones of the Taguchi
methodology for quality engineering.
Taguchi suggests that it is important to think of quality in terms of the loss imparted to society during product use as a
result of functional variation and harmful effects. Harmful effects refer to the side effects that are realized during the use
of the product and are unrelated to product function. Functional variation refers specifically to the deviation of product
performance from that intended by design, that is, from the nominal. Specific sources of functional variation will be
discussed later in this article. Taguchi uses a loss function concept to quantify quality as loss due to functional variation.
Figure 2 illustrates the idea of the loss function.
Fig. 2 Plot of quality loss versus quality characteristic to illustrate concept of loss function of quality
The loss function concept as a way to measure quality clearly suggests that the goal of design and manufacturing is to
develop products and processes that perform on target with smallest variation. It places tremendous importance on the
reduction of variation to achieve the most consistently performing products and processes. To drive performance toward
this overall objective, more must be learned about the way in which the important parameters of the product/process
influence performance. Over the years, the methods of design of experiments have been proved to be an effective way to
do this.
Figure 3 provides an interpretation of the loss function concept when overlaid on the traditional engineering specification
definition of quality. In this way, no loss would be considered as long as the quality characteristic in question lies within
the lower and upper specification. Outside of the specifications, the product is considered to be unacceptable, and a
constant loss would therefore be realized. This loss would likely be measured in terms of scrap cost or rework cost. The
following case study suggests that this interpretation is illogical.