Production technology Ch36

Kalpakjian • SchmidManufacturing Engineering and Technology © 2001 Prentice-Hall Page 36-1

CHAPTER 36

Quality Assurance, Testing, andInspection


Deming’s 14 Points

TABLE 36.11. Create constancy of purpose toward improvement of product and service.2. Adopt the new philosophy.3. Cease dependence on mass inspection to achieve quality.4. End the practice of awarding business on the basis of price tag.5. Improve constantly and forever the system of production and service, to

improve quality and productivity, and thus constantly decrease cost.6. Institute training on the job.7. Institute leadership (as opposed to supervision).8. Drive out fear so that everyone can work effectively.9. Break down barriers between departments.10. Eliminate slogans, exhortations and targets for zero defects and new levels of

productivity11. Eliminate quotas and management by numbers, numerical goals. Substitute

leadership.12. Remove barriers that rob the hourly worker of pride of workmanship.13. Institute a vigorous program of education and self-improvement.14. Put everybody in the company to work to accomplish the transformation

Kalpakjian • SchmidManufacturing Engineering and Technology © 2001 Prentice-Hall 6-3

Robust Design

Figure 36.1 A simple example of robust design. (a) Location of two mounting holes on a sheet-metalbracket, where the deviation of the top surface of the bracket from being perfectly horizontal is ±α. (b)New location holes, whereby the deviation of the top surface of the bracket from being perfectlyhorizontal is reduced to± α/2.


Taguchi Loss Function

Figure 36.2 (a) Objective functionvalue distribution of color densityfor television sets. (b) Taguchi lossfunction, showing the averagereplacement cost per unit to correctquality problems. Source: After G.Taguchi.


Frequency and Normal Distribution Curves

Figure 36.3 (a) A histogram of the number of shafts measured and their respective diameters. This type ofcurve is called frequency distribution. (b) A Normal distribution curve indicating areas within each range ofstandard deviation. Note: the greater the range, the higher the percentage of parts that fall within it.


Frequency Distribution Curve

Figure 36.4 Frequency distributioncurve, showing lower and upperspecification limits.


Statistical Quality Control

Figure 36.5 Control charts used instatistical quality control. The processshown is in statistical control becauseall points fall within the lower and uppercontrol limits. In this illustration samplesize is five and the number of samples is15.


Constants for Control Charts

TABLE 36.2Sample size A2 D4 D3 d2

2345678910121520

1.8801.0230.7290.5770.4830.4190.3730.3370.3080.2660.2230.180

3.2672.5752.2822.1152.0041.9241.8641.8161.7771.7161.6521.586

00000

0.0780.1360.1840.2230.2840.3480.414

1.1281.6932.0592.3262.5342.7042.8472.9703.0783.2583.4723.735


Control Charts

Figure 36.6 Controlcharts. (a) Processbegins to become outof control because ofsuch factors as toolwear (drift). The toolis changed and theprocess is then instatistical control. (b)Process parameters arenot set properly; thusall parts are around theupper control limit(shift in mean). (c)Process becomes outof control because offactors such as achange in theproperties of theincoming material(shift in mean).


Digital Gages with Microprocessors

Figure 36.7 Schematicillustration showing integrationof digital gages withmicroprocessor for real-timedata acquisition and SPC/SPQcapabilities. Note the exampleson the CRT displays, such asfrequency distribution (see Fig.36.3) and control charts (seeFig. 36.4). Source: MitutoyoCorp.


Data for Standard Deviation Calculation

TABLE 36.3

Sample number x1 x2 x3 x4 x5 x R12345678910

4.464.454.384.424.424.444.394.454.444.42

4.404.434.484.444.454.454.414.414.464.43

4.444.474.424.534.434.444.424.434.304.37

4.464.394.424.494.444.394.464.414.384.47

4.434.404.354.354.414.404.474.504.494.49

4.4384.4284.4104.4464.4304.4244.4304.4404.4144.436

0.060.080.130.180.040.060.080.090.190.12


Acceptance Sampling

Figure 36.8 A typical operating-characteristics curve used inacceptance sampling. The higher thepercentage of defective parts, the lowerthe probability of acceptance by theconsumer. There are several methodsof obtaining these curves.


Liquid-Penetrant and Magnetic-ParticleInspection

Figure 36.9 Sequence of operations for liquid-penetrant inspection to detect the presence of cracksand other flaws in a workpiece. Source: Metals Handbook, Desk Edition. Copyright ©1985, ASMInternational, Metals Park, Ohio. Used with permission.

Figure 36.10 Schematic illustration ofmagnetic-particle inspection of a part with adefect in it. Cracks that are in a directionparallel to the magnetic field, such as in A,would not be detected, whereas the othersshown would. Cracks F, G, and H are theeasiest to detect. Source: Metals Handbook,Desk Edition. Copyright ©1985, ASMInternational, Metals Park, Ohio. Used withpermission.


Radiographic Inspection

Figure 36.11 Three methods of radiographic inspection: (a) conventional radiography, (b)digital radiography, and (c) computed tomography. Source: Courtesy of AdvancedMaterials and Processes, November 1990. ASM International


Eddy-Current Inspection

Figure 36.12 Changes in eddy-currentflow caused by a defect in a workpiece.Source: Metals Handbook, Desk Edition.Copyright ©1985, ASM International,Metals Park, Ohio. Used withpermission.


Holography

Figure 36.13 Schematic illustration of the basic optical system used in holographyelements in radiography, for detecting flaws in workpieces. Source: Metals Handbook,Desk Edition. Copyright ©1985, ASM International, Metals Park, Ohio. Used withpermission.

Production technology Ch36

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