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Section 36 2 Product Quality I02l

This chapter identifies and describes the various methods that are commonly used toinspect manufactured products.

Product quality always has been one of the most important aspects ofmanufacturing operations. In view of a global competitive market, continuousimprovement in quality is a major priority, particularly for large corporations inindustrialized countries. In Japan, the single term kaizen is used to signify never-ending improvement.

The prevention of defects in products and online inspection of parts are majorgoals in all manufacturing activities. Again, quality must be built into tt product andnot merely considered after the product already has been made. Thus, close cooper-ation and communication among design and manufacturing engineers and direct in-volvement and encouragement of company management are vital.

Major advances in quality engineering and productivity have been made overthe years, largely because of the efforts of quality experts such as WE. Deming,G. Taguchi, and ].M. juran. The importance of the quality, reliability, and safety ofproducts in a global economy is now internationally recognized by the establish-ment of various ISO and QSO standards and nationally by the Malcolm BaldrigeNational Quality Award in the United States.

36.2 Product QualityWe all have used terms such as poor quality or high quality to describe a partic-ular product or the products of a particular company. What is quality? Although wemay recognize it when we see or use a product, quality, unlike most technical terms, isdifficult to define precisely. Simply and generally, quality may be defined as tt products#tness for use.

Several aspects of quality that generally are identified are performance, dura-bility, reliability, robustness, availability, cost, and serviceability, as well as aestheticsand perceived quality. Thus, quality is a broad-based characteristic or property,and its factors consist not only of well-defined technical considerations, but also ofsubjective opinions.

For example, consider the following: (a) The handle on a kitchen utensil isinstalled crookedly, or the handle discolors or cracks during its use, (b) a weighingscale functions erratically, (c) a plastic toy breaks easily, (d) a vacuum cleaner re-quires frequent repairs, (e) the stem of a screwdriver bends, and (f) a machine toolcannot maintain the dimensional tolerances of the workpiece because of lack ofstiffness or poor construction. These examples all lead us to believe that the productis of low quality. The general perception is that a high-quality product is one thatperforms its functions reliably over a long time without breaking down or requiringrepairs. Some examples of this type of product are good-quality kitchen utensils,refrigerators, washing machines, tools, bicycles, and automobiles.

Note that, in describing good- or poor-quality products, this book has statedneither the intended lifetimes of those products nor any of their technical specifica-tions. Design and manufacturing engineers have the joint responsibility of selectingand specifying materials for the components of the products to be made. For exam-ple, in selecting the type of metal for a screwdriver stem, we can specify materialsthat have high strength and high resistance to wear and corrosion and then processthem with the use of appropriate manufacturing techniques, including heat treat-ments and coatings.

It is important to note, however, that materials possessing better propertiesgenerally are more expensive and may be more difficult to process than those with

|022 Chapter 36 Quality Assurance, Testing, and Inspection

TABLE 36.1

Average Life Expectancy af Same ProductsU.S. dollar bill 18 monthsCar battery 4 yearsHair dryer 5 yearsWater heater (gas) 12 yearsVacuum cleaner 10 yearsAir-conditioning unit 15 yearsNuclear reactor 40 yearsAutomobile disk brake 65,000 kmMuffler 50,000 kmTire 65,000-100,000 km

poorer properties. The level of quality that a manufacturer chooses for its productsmay depend on the market for which the products are intended. For example, low-cost, low-quality tools have their own World market niche.

As described in Section 40.9, the total product cost depends on several variables,including the level of automation in the manufacturing plant. Thus, there are manyways for the engineer to review and modify overall product design and manufacturingprocesses to minimize a products cost without affecting its quality. Contrary to gen-eral public perception, high-quality products do not necessarily cost more, especiallyconsidering the fact that poor-quality products

' Present difficulties in assembling and maintaining components. Result in the need for in-field repairs. Have the significant built-in cost of customer dissatisfaction.

Quality standards are essentially a balance among several considerations; thisbalance is also called return on quality (ROQ) and usually includes some limit onthe expected life of the product. Typical life expectancies of some products are givenin Table 36.1 (see also Table 1.4 in the General Introduction).

36.3 Quality AssuranceQuality assurance is the total effort made by a manufacturer to ensure that its prod-ucts conform to a detailed set of specifications and standards. It can be defined as allactions necessary to ensure that quality requirements will be satisfied; quality con-trol is the set of operational techniques used to fulfill quality requirements.

These standards cover several types of parameters, such as dimensions, surfacefinish, tolerances, composition, and color, as well as mechanical, physical, and chem-ical properties and characteristics. In addition, standards usually are Written to ensureproper assembly, using interchangeable defect-free components and resulting in aproduct that performs as intended by its designers.

Quality assurance is the responsibility of everyone involved with design andmanufacture. The often-repeated statement that quality must be built into a productreflects this important concept. Although a finished product can be inspected forquality, and rejected if conditions are not met, quality cannot be inspected into afinished product.

Section 36.4 Tota

An important aspect of quality assurance is the capability to (a) analyze de-fects as they occur on the production line and (b) promptly eliminate them or reducethem to acceptable levels. In an even broader sense, quality assurance involves eval-uating the product and its customer satisfaction. The sum total of all these activitiesis referred to as total quality control and, in an even larger sense, total qualitymanagement.

It is clear that, in order to control quality, it is essential to be able to

Measure the level of quality quantitatively. Identify all of the material and process variables that can be controlled.

The quality level built in during production can then be checked by continuously in-specting the product to determine Whether it meets the specifications for dimensionaltolerances, surface finish, defects, and other characteristics.

36.4 Total Quality ManagementTotal quality management (TQM) is a system which emphasizes the concept thatquality must be designed and built into a product. It is a systems approach, in thatboth management and employees make a concerted effort to consistently manufac-ture high-quality products. Defect prevention rather than defect detection is the majorgoal here.

Leadership and teamwork in the organization are essential. They ensure thatthe goal of continuous improvement in manufacturing operations is foremost, be-cause they reduce product variability and they improve customer satisfaction. TheTQM concept also requires control of the processes, and not the parts produced, sothat process variability can be reduced and no defective parts are allowed to continuethrough the production line.

Quality Circle. The basic concept of a quality circle consists of regular meetings bygroups of employees (workers, supervisors, and managers) who discuss how toimprove and maintain product quality at all stages of the manufacturing operation.Worker involvement, responsibility, and creativity, as well as a team effort, areemphasized. Comprehensive training is provided so that the worker can become con-scious of quality and be capable of analyzing statistical data, identifying the causes ofpoor quality, and taking immediate action to correct the situation. Experience has in-dicated that quality circles are more effective in lean-manufacturing environments,as described in Section 39.6.

Quality Engineering as a Philosophy. Experts in quality control have put many ofthe quality-control concepts and methods into a larger perspective. Notable amongthese experts have been Deming, juran, and Taguchi, vvhose philosophies of qualityand product cost have had a major impact on modern manufacturing.

36.4.I Deming MethodsDuring World War II, W.E. Deming (1900-1993) and several others developed newmethods of statistical process control for Wartime-industry manufacturing plants.The methods arose from the recognition that there were variations in (a) the per-formance of machines and of people and (b) the quality and dimensions of ravv

Quality Management |023


TABLE 36.2

T T ",` -

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

and productivity and thus constantly decrease cost.6. Institute training for the requirements of a particular task, and document the requirements

for future training.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 productivity.11. Eliminate quotas and management by numbers, or 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.

materials. The efforts of these pioneers involved not only statistical methods ofanalysis, but also a new way of looking at manufacturing operations-that is, fromthe perspective of improving quality while lowering costs.

Deming recognized that manufacturing organizations are systems of manage-ment, workers, machines, and products. His basic ideas are summarized in the now-well-known 14 points, given in Table 36.2. These points are not to be seen as achecklist or menu of tasks; they are the characteristics that Deming recognized incompanies that produce high-quality goods. He placed great emphasis on communi-cation direct worker involvement and education in statistics and modern manufac-

3 9

turing technology.

36.4.2 juran MethodsA contemporary of Deming, ].M. Juran (1904-2008) emphasized the importance ofthe following ideas:

Recognizing quality at all levels of an organization, including uppermanagement.

Fostering a responsive corporate culture. Training all personnel in how to plan, control, and improve quality.

The main concern of the top management in an organization is business and man-agement, whereas those in quality control are basically concerned with technology.These different worlds have, in the past, often been at odds, and their conflicts haveled to quality problems.

Planners determine who the customers are and their needs. An organizationscustomers may be external (the end users who purchase the product or service), orthey may be internal (the different parts of an organization that rely on other seg-ments of the organization to supply them with products and services). The plannersthen develop product and process designs to respond to the customers needs. Theplans are turned over to those in charge of operations, who are then responsible forimplementing both quality control and continued improvement in quality.

Section 36.5 Taguch| Methods |025

36.5 Taguchi MethodsIn G. Taguchis (1924-) methods, high quality and low costs are achieved by combin-ing engineering and statistical techniques to optimize product design and manufactur-ing processes. Taguchi rnetlvods is now a term that refers to the approaches developedby Taguchi to manufacture high-quality products. One fundamental viewpoint putforward is the quality challenge facing manufacturers: Provide products that delightyour customers. To delight customers, manufacturers should offer products with thefollowing characteristics:

High reliability Perform the desired functions well Good appearance Inexpensive Upgradeable Available in the quantities desired when needed Robust over their intended life (see Section 36.5.1).

These product characteristics clearly are the goals of manufacturers striving to pro-vide high-quality products. Although it is very challenging to actually provide all ofthese characteristics, excellence in manufacturing is undeniably a prerequisite.

Taguchi also contributed to the approaches that are used to document quality,recognizing that any deviation from the optimum state of a product represents afinancial loss because of such factors as reduced product life, performance, andeconomy. Loss of quality is defined as the #nancial loss to society after the productis shipped. Loss of quality results in the following problems:

Poor quality leads to customer dissatisfaction. Costs are incurred in servicing and repairing defective products, especially

when such repairs have to be made in the field. The manufacturers credibility in the marketplace is diminished. The manufacturer eventually loses its share of the market.

The Taguchi methods of quality engineering emphasize the importance of thefollowing concepts:

Enhancing cross-functional team interaction: Design engineers and manufac-turing engineers communicate with each other in a common language. Theyquantify the relationships between design requirements and manufacturingprocess selection.

Implementing experimental design: The factors involved in a process or opera-tion and their interactions are studied simultaneously.

In experimental design, the effects of controllable and uncontrollable variableson the product are identified. This approach minimizes variations in product dimen-sions and properties, and ultimately brings the mean to the desired level.

The methods used for experimental design are complex. They involve the useof factorial design and orthogonal arrays, both of which reduce the number of ex-periments required. These methods also are capable of identifying the effects of vari-ables that cannot be controlled (called noise), such as changes in environmentalconditions in a plant.

The use of factorial design and orthogonal arrays results in (a) the rapid identi-fication of the controlling variables, referred to as observing niain effects, and (b) theability to determine the best method of process control. Control of these variablessometimes requires new equipment or major modifications to existing equipment.


For example, variables affecting dimensional tolerances in machining a particularcomponent can readily be identified, and whenever possible, the correct cuttingspeed, feed, cutting tool, and cutting fluids can be specified.

An important concept introduced by Taguchi is that any deviation from adesign objective constitutes a loss in quality. Consider, for example, the tolerancingstandards for a shaft, given in Fig. 35.18. On the one hand, there is a range of dimen-sions over which a part is acceptable; on the other hand, the Taguchi philosophy callsfor a minimization of deviation from the design objective. Thus, with Fig. 35.18a asan example, a shaft with a diameter of 40.03 mm normally would be consideredacceptable and thus would pass inspections. In the Taguchi approach, however, ashaft with this diameter represents a deviation from the design objective. Such devia-tions generally reduce the robustness and performance of products, especially incomplex systems.

36.5.l RobustnessAnother aspect of quality is a concept originally suggested by Taguchi that continu-ously has grown in importance and is referred to as robustness. A robust design,process, or system is one that continues to function within acceptable parameters de-spite variabilities (often unanticipated) in its environment. In other words, its outputs(such as its function and performance) have minimal sensitivity to its input variations(such as variations in environment, load, and power source). Moreover, a robustproduct or machine is insensitive to changes in tolerance over its intended life.

For example, in a robust design, a part will function sufficiently well even if theloads applied, or their directions, go beyond anticipated values. Likewise, a robustmachine or system will undergo minimal deterioration in performance even if it expe-riences variations in environmental conditions, such as temperature, humidity, airquality, and vibrations. Also, a robust machine will have no significant reduction inits performance over its life, whereas a less robust design will perform less efficientlyas time passes.

As a simple illustration of a robust design, consider a sheet-metal mountingbracket to be attached to a wall with two bolts (Fig. 36.1a). The positioning of thetwo mounting holes on the bracket will include some error due to the manufactur-ing process involved. This error will then prevent the top edge of the bracket frombeing perfectly horizontal.

A more robust design is shown in Fig. 36.1b, in which the mounting holes havebeen moved twice as far apart as in the first design. Even though the precision of holelocation remains the same and the manufacturing cost is also the same, the variabilityin the top edge of the bracket (from the horizontal) has now been reduced by one-half.However, if the bracket is subjected to vibration, the bolts may loosen over time.

_i_-+g - *ig-- 2

P-~L~*~l. ;l*--~2L~f~~*lg

(H) (b)

FIGURE 36.l A simple example of robust design. (a) Location of two mounting holes on asheet-metal bracket where the deviation keeping the top surface of the bracket from beingperfectly horizontal is ia. (b) New locations of holes; now the deviation (keeping the topsurface of the bracket from being perfectly horizontal) is reduced to ia/2.

Section 36.5 Taguchi Methods |027

An even more robust design approach would be to use an adhesive to hold the threadsin place or to use some type of fastener that would not loosen over time.

36.5.2 Taguchi Loss FunctionThe Taguchi loss function was introduced in the early 1980s because traditionalaccounting practices had no real Way of calculating losses on parts that met designspecifications. In the traditional accounting approach, a part is defective and incursa loss to the company when it exceeds its design tolerances; otherwise, there is noloss to the company.

The Taguchi loss function is a tool for comparing quality on the basis of mini-mizing variations. It calculates the increasing loss to the company when the compo-nent deviates from the design objective. This function is defined as a parabola whereone point is the cost of replacement (including shipping, scrapping, and handlingcosts) at an extreme of the tolerances, While a second point corresponds to zero lossat the design objective.

Mathematically, the loss cost can be written asLoss cost = k[(Y - T)2 + 02), (36.1)

Where Y is the mean value from manufacturing, T is the target value from design, 0' isthe standard deviation of parts from manufacturing, and le is a constant, defined as

/Q _ Replacement cost(LSL - T)2 (36.2)

Where LSL is the lower specification limit. When the lower (LSL) and upper (USL)specification limits are the same distance from the mean (i.e., the tolerances are bal-anced), either of the limits can be used in this equation.

EXAMPLE 36.I Production of Polymer Tubing

High-quality polymer tubes are being produced formedical applications in which the target wall thicknessis 2.6 mm, a USL is 3.2 mm, and an LSL is 2.0 mm(2.6 i 0.6 mm). If the units are defective, they arereplaced at a shipping-included cost of $10.00. Thecurrent process produces parts with a mean of 2.6 mmand a standard deviation of 0.2 mm. The currentvolume is 10,000 sections of tube per month.

An improvement is being considered for theextruder heating system. This improvement will cutthe variation in half, but it costs $50,000. Determinethe Taguchi loss function and the payback periodfor the investment.

Solution Lets first identify the quantities involved:USL = 3.2 mm, LSL = 2.0 mm, T = 2.6 mm, o' ==0.2 mm, and Y = 2.6 mm.

The quantity le is given by($10.00)

le = -----5(3.2 - 2.6) = $27.28.

The loss cost before the improvement is then

Loss cost = (27.78)((2.6 - 2.6)2 + 0.22]= $1.11 per unit.

After the improvement, the standard deviation is0.1 mm; thus, the loss cost is

Loss cost = (27.78)[(2.6 - 2.6)2 + 0.12)-= $0.28 per unit.

The savings are then ($1.11 _ $0.28)(10,000) =$8300 per month. Hence, the payback period for theinvestment is $50,000/( $8300/month) = 6.02 months.


CASE STUDY 36.l Manufacture of Televlslon Sets by Sony Corporation

Sony Corporation executives found a confusing situ-ation confronting them in the mid-1980s. Televisionsmanufactured in japanese production facilities soldfaster than those produced in a San Diego facility,even though they were produced from identical de-signs. There were no identifications to distinguish thetelevisions made in Japan from those made in theUnited States, so there was no apparent reason forthis discrepancy. However, investigations revealedthat the televisions produced in japan were superiorto the U.S. versions; color sharpness was better andhues were more brilliant. Since the televisions wereon display in stores, consumers could easily detectand purchase the model that had the best picture.

The difference in picture quality was obvious,but the reasons for that difference were not clear.A further point of confusion was the constant assur-ance that the San Diego facility had a total qualityprogram in place and that the plant was maintainingquality-control standards so that no defective partswere produced. The Japanese facility did not have atotal quality program, but there was an emphasis onreducing variation from part to part.

Further investigations found a typical pattern inan integrated circuit that was critical in affecting colordensity. The distribution of parts meeting the color-design objective is shown in Fig. 36 .2a; the Taguchi lossfunction for these parts is shown in Fig. 36.2b. In theSan Diego facility, where the number of defective partswas minimized (to zero in this case), a uniform distri-bution within the specification limits was achieved.

The japanese facility actually produced partsoutside of the design specification, but the standard de-viation about the mean was lower. Using the Taguchiloss-function approach (see Example 36.1) makes itclear that the San Diego facility lost about $1.33 perunit while the japanese facility lost $0.44 per unit.

Traditional quality viewpoints would find theuniform distribution without defects to be superior tothe distribution in which a few defects are producedbut the majority of parts are closer to the design targetvalues. However, consumers can readily detect whichproduct is superior, and the marketplace proves thatminimizing deviations is a worthwhile quality goal.

Source: After D.M. Byrne and G. Taguchi.

I

m I

5I'/J I

E IJapanese San DIegoI 3-

E 'plant plant 3- Q'~'aIItY Average costE j 7, loss -----

Q 8 : function3Z

LSL Target USL LSL Target USLColor density Color density

(H) Ib)

FIGURE 36.2 (a) Objective-function value distribution of color density for television sets. (b) Taguchi lossfunction, showing the average replacement cost per unit to correct quality problems. Source: After G. Taguchi.

EXAMPLE 36.2 Increasing Quality without Increasing the Cost ofa ProductA manufacturer of clay tiles noticed that excessivescrap was being produced because of temperaturevariations in the kiln used to fire the tiles, thusadversely affecting the companys profits. The first

solution the manufacturer considered was purchasingnew kilns with better temperature controls. However,this solution would require a major capital invest-ment. A study was then undertaken to determine

whether modifications could be made in the composi-tion of the clay so that it would be less sensitive totemperature fluctuations during firing.

On the basis of factorial experiment design inwhich the factors involved in a process and their in-teractions are studied simultaneously, it was found

Section 36.6 The ISO and QS Standards |029

that increasing the lime content of the clay made thetiles less sensitive to temperature variations duringfiring. This modification (which was also the low-cost alternative) was implemented, reducing scrapsubstantially and improving tile quality.

36.6 The ISO and QS StandardsWith increasing international trade and global competition, customers worldwideincreasingly are demanding high-quality products and services at lovv prices and arelooking for suppliers that can respond to this demand consistently and reliably. Thistrend has, in turn, created the need for international conformity and consensusregarding the establishment of methods for quality control, reliability, and safety ofproducts. In addition to these considerations, equally important concerns regardingthe environment and quality of life also are being addressed. This section describesthe standards relevant to product quality and environmental issues.

36.6.I The ISO 9000 StandardFirst published in 1987 and then revised in 1994, the ISO 9000 standard (QualityManagement and Quality Assurance Standards) is a deliberately generic series ofquality system-management standards. The ISO 9000 standard has permanently in-fluenced the manner in which manufacturing companies conduct business in Worldtrade and has become the World standard for quality.

The ISO 9000 series includes the following standards:

ISO 9001-Quality systems: Model for quality assurance in design/dei/elop-ment, production, installation, and servicing.

ISO 9002-Quality systems: Model for quality assurance in production andinstallation.

ISO 9003-Quality systems: Model for quality assurance in final inspectionand testing.

ISO 9004-Quality management and quality system elements: Guidelines.Companies voluntarily register for these standards and are issued certificates.Registration may be sought generally for ISO 9001 or 9002, and some companieshave registration up to ISO 9003. The 9004 standard is simply a guideline and not amodel or a basis for registration. For certification, a companys plants are visitedand audited by accredited and independent third-party teams to certify that the stan-dards 20 key elements are in place and are functioning properly.

Depending on the extent to which a company fails to meet the requirements ofthe standard, registration may or may not be recommended at that time. The auditteam does not advise or consult with the company on how to fix discrepancies, butmerely describes the nature of the noncompliance. Periodic audits are required tomaintain certification. The certification process can take from six months to a year ormore and can cost tens of thousands of dollars. The cost depends on the companyssize, number of plants, and product line.

The ISO 9000 standard is not a product certification, but a quality process cer-tification. Companies establish their own criteria and practices for quality. However,the documented quality system must be in compliance with the ISO 9000 standard.Thus, a company cannot Write into the system any criterion that opposes the intent ofthe standard.


Registration symbolizes a companys commitment to conform to consistentpractices, as specified by the companys own quality system (such as quality in design,development, production, installation, and servicing), including proper documenta-tion of such practices. In this way, customers (including government agencies) areassured that the supplier of the product or service (which may or may not be withinthe same country) is following specified practices. In fact, manufacturing companiesare themselves assured of such practices regarding their own suppliers that have ISO9000 registration; thus, suppliers also must be registered.

36.6.2 The QS 9000 StandardJointly developed by Chrysler, Ford, and General Motors, the QS 9000 standard wasfirst published in August of 1994. Prior to the development of QS 9000, each of theseautomotive companies had its own standard for quality system requirements. Tier Isuppliers have been required to obtain third-party registration to QS 9000 before thedates established by each of the Big Three companies. Very often, QS 9000 has beendescribed as an ISO 9000 chassis with a lot of extras. This is a good description,given that all of the ISO 9000 clauses serve as the foundation of QS 9000. However,the little extras are substantial.

The February 1995 edition of QS 9000 has three sections. Section I contains all20 of the ISO 9001 clauses, but almost every clause has additional requirements for QS9000. Section II has three sections: Production Part Approval Process, ContinuousImprovement, and Manufacturing Capabilities. Section III is entitled Customer-Specific Requirements and contains separate sections for Chrysler, General Motors,Ford, and truck manufacturers, respectively. Existing QS 9000 registrations are beingupgraded continuously to comply with new editions of QS 9000.

36.6.3 The ISO |4000 StandardISO 14000 is a family of standards first published in September of 1996 and per-taining to international environmental management systems (EMS). It concerns theway an organizations activities affect the environment throughout the life of itsproducts (see also Section I.6 in the General Introduction). These activities (a) maybe internal or external to the organization, (b) range from production to ultimatedisposal of the product after its useful life, and (c) include effects on the environ-ment, such as pollution, waste generation and disposal, noise, depletion of naturalresources, and energy use.

Companies in most countries have rapidly been obtaining certification for thisstandard. The ISO 14000 family of standards has several sections: Guidelines forEnvironmental Auditing, Environmental Assessment, Environmental Labelsand Declarations, and Environmental Management. ISO 14001, Environ-mental Management System Requirements, consists of sections titled GeneralRequirements, Environmental Policy, Planning, Implementation and Operation,Checking and Corrective Action, and Management Review.

36.7 Statistical Methods of Quality ControlBecause of the numerous variables involved in manufacturing processes and opera-tions, the implementation of statistical methods of quality control is essential. The fol-lowing list describes some of the commonly observed variables in manufacturing:

Cutting tools, dies, and molds are subject to wear; thus, part dimensions andsurface characteristics vary over time.

Section 36.7 Statistical Methods of Quality Control 03

Machinery performs differently depending on its quality, age, condition, andmaintenance; thus, older machines tend to chatter and vibrate, are difficult toadjust, and do not maintain tolerances as well as new machines.

The effectiveness of metalworking fluids declines as they degrade; thus, tooland die life, surface finish and surface integrity of the workpiece, and forcesand energy requirements are affected.

Environmental conditions, such as temperature, humidity, and air quality inthe plant, may change from one hour to the next, affecting the performance ofmachines and workers.

Different shipments, at different times, of raw materials to a plant may havesignificantly different dimensions, properties, and surface characteristics.

Operator attention may vary during the day, from machine to machine orfrom operator to operator.

Those events which occur randomly-that is, without any particular trend orpattern-are called chance variations or special causes. Those events which can betraced to specific causes are called assignable variations or common causes.

Although the existence of variability in production operations has been recog-nized for centuries, it was Eli Whitney (1765-1825) who first understood its full sig-nificance when he found that interchangeable parts were indispensable to the massproduction of firearms. Modern statistical concepts relevant to manufacturing engi-neering were first developed in the early 1900s, notably through the work ofWA. Shewhart (1891-1967).

36.7.I Statistical Quality ControlTo understand statistical quality control (SQC), the following commonly used termsmust first be defined:

Sample size: The number of parts to be inspected in a sample. The propertiesof the parts in the sample are studied to gain information about the wholepopulation.

Random sampling: Taking a sample from a population or lot in which eachitem has an equal chance of being included in the sample. Thus, when takingsamples from a large bin, the inspector should not take only those that happento be within reach.

Population: The total number of individual parts of the same design fromwhich samples are taken; also called the universe.

Lot size: The size of a subset of the population. One or more lots can be con-sidered subsets of the population and may be considered as representative ofthe population.

The sample is inspected for several characteristics and features, such as toler-ances, surface finish, and defects, with the instruments and techniques described inChapter 35 and in Sections 36.10 and 36.11. These characteristics fall into two cat-egories: those which are measured quantitatively (method of variables) and thosewhich are measured qualitatively (method of attributes).

I. The method of variables is the quantitative measurement of the parts charac-teristics, such as dimensions, tolerances, surface finish, and physical or mechan-ical properties. The measurements are made for each of the units in the groupunder consideration, and the results are compared against specifications.

2. The method of attributes involves observing the presence or absence ofqualitative characteristics (such as external or internal defects in machined,

Frequencyofoccurrence

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fl 5'N

'Ul'

rn>-1

U3

OCfl

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(flUT

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where xi is the measured value for each part.Note from the numerator in Eq. (36.5) that, as the curve widens, the standard

deviation becomes greater. Note also that 0' has the same units as xi. Since we knowthe number of turned parts that fall within each group, we can calculate the percent-age of the total population represented by each group. Thus, Fig. 36.3b shows that,in the measurement of shaft diameters,

99.73% of the population falls within the range i30, 95.46% within d;2o', and 68.26% within i102

It can be seen that only 0.27% fall outside the i3r range. This means thatthere are 2700 defective parts per million produced. In modern manufacturing, thatis an unacceptable rate, in view of the observation that, at this level of defects, nomodern computer would function reliably. However, note that these quantities areonly valid for distributions that are normal, as shown in Fig. 36.3, and that are notskewed.

36.1.2 Six SigmaSix sigma is a set of statistical tools based on the well-known total quality managementprinciples of continually measuring the quality of products and services. Although sixsigma indicates 3.4 defective parts per million, it includes considerations such as un-derstanding process capabilities (Section 36.8.2), delivering defect-free products, andthus ensuring customer satisfaction. This approach consists of a clear focus on defin-ing the quality problems, measuring relevant quantities, and analyzing, controlling,and improving processes and operations.

As mentioned in Section 36.7.1, three sigma in manufacturing would result in0.27% (or 2700 parts per million) defective parts, an unacceptable rate in modernmanufacturing. Also, in the service industries, 270 million incorrect credit-cardtransactions would be recorded each year in the United States alone. It has furtherbeen estimated that companies operating at three- to four-sigma levels lose about10 to 15% of their total revenue due to defects. Extensive efforts continue to bemade to eliminate virtually all defects in products, processes, and services, resultingin savings estimated to be in billions of dollars. Because of its major impact on busi-ness, six sigma is now widely recognized as a good management philosophy.

36.8 Statistical Process ControlIf the number of arts that do not meet set standards i.e., the number of defectivePparts) increases during a production run, we must be able to determine the cause(incoming materials, machine controls, degradation of metalworking fluids,


10

operator boredom, or other factors) and take appropriate action. Although thisstatement at first appears to be self-evident, it was only in the early 1950s that asystematic statistical approach was developed to guide operators in manufacturingplants.

The statistical approach advises the operator to take certain measures andactions and tells the operator when to take them, in order to avoid producingfurther defective parts. Known as statistical process control (SPC), this techniqueconsists of various elements:

CD c I:

516; 1% ag Control charts and control limitsi 8 _ _Q L .Q Ca abilities of the articular manufacturin process3 Q1 ,: (D ,: P p e 6 g 3 g 3 Characteristics of the machinery involved.E $ 3 2 5*5 4 2 36.8.l E and R Charts (Shewhart Control Charts)U'

1% O The frequency distribution curve in Fig. 36.3b shows a range of_

_

12_95 13_OO 1 3_05 shaft diameters being produced that may fall beyond the designDiameter of shafts (mm) tolerance range. The same bell-shaped curve is shown in Fig. 36.4,

which now includes the specified tolerances for the diameter of theturned shafts.FIGURE 36.4 Frequency distribution curve show-

ing lower and upper specification limits.

#4304E1303T;/13.02$130151300E1299@1298@1297Q1296< 0

.Q'o

A 0.12EE 0.10E 0.08

_ 0.063 0 O45 0.02,I

0

Average of 5 samplesAverage of next 5 samples

Control charts graphically represent the variations ofa process over time. They consist of data plotted duringproduction. Typically, there are two plots. The quantity Y

(Fig. 36.5a) is the average for each subset ofsamples taken and inspected-say, eachsubset consists of 5 parts. A sample size of

Average Of next 5 Samples between 2 and 10 parts is sufficiently accu-"_ ' """""""""""" UCL? rate (although more parts are better), pro-

vided that the sample size is held constant= throughout the inspection."("e'a9e l The fre f 1' control limits for the process. The control(131 limits are set on these charts according to

statistical-control formulas designed to keepactual production within acceptable levelsFIGURE 36.5 Control charts used in statistical quality control. The

process shown is in good statistical control because all points fall withinthe lower and upper control limits. In this illustration, the sample size is5 and the number of samples is 15.

of variation. One common approach is tomake sure that all parts are within threestandard deviations of the mean (3:30)

Section 36.8 Statistical Process Control |035TABLE 36.3

Constants for Contra! ChartsSample size A2 D4 D3 dz2 1.880 3.267 0 1.1283 1.023 2.575 0 1.6934 0.729 2.282 0 2.0595 0.577 2.115 0 2.3266 0.483 2.004 0 2.5347 0.419 1.924 0.078 2.7048 0.373 1.864 0.136 2.8479 0.337 1.816 0.184 2.970

10 0.308 1.777 0.223 3.07812 0.266 1.716 0.284 3.25815 0.223 1.652 0.348 3.47220 0.180 1.586 0.414 3.735

The standard deviation also can be expressed as a function of range. Thus, for Y,Upper control limit (UCl) = E + 30 = T + AZR (36.6)

andLower control limit (LCLQ) = E - 30 = T - AZR, (36.7)

where A2 isobtained from Table 36.3 and R is the average of R values. The quanti-ties E and R are estimated from the measurements taken.

These control limits are calculated on the basis of the past production capabil-ity of the equipment itself; they are not associated with either design tolerance spec-ifications or dimensions. They indicate the limits within which a certain percentageof measured values normally are expected to fall because of the inherent variationsof the process itself and upon which the limits are based.

The major goal of statistical process control is to improve the manufacturingprocess with the aid of control charts so as to eliminate assignable causes. The con-trol chart continually indicates progress in this area.

The second control chart (Fig. 36.5b) shows the range, R, in each subset ofsamples. The solid horizontal line represents the average of R values in the lot,denoted as R, and is a measure of the variability of the samples. The upper andlower control limits for R are obtained from the equations

UCLR = D4R (36.8)and

LCLR = D3R, (36.9)where the constants D4 and D3 take on the values given in Table 36.3. The tablealso includes the constant dz, which is used to estimate the standard deviation of theprocess distribution shown in Fig. 36.4 from the equation

R0' - (36.10)

When the curve of a control chart is like the one shown in Fig. 36.5a, we saythat the process is in good statistical control. In other words,

There is no discernible trend in the pattern of the curve The points (measured values) are random with time The points do not exceed the control limits.


Tool Changed

diameterY(mm)

------------------ ----------- UCL;

Y

Average

------------------------------- LCL,7Time->

(H)

diameterY(mm)

---- --- - ----- ---- -- UCL;

Average

------------------------------- LCLYTime->

(D)

diameter,Y(mm)

-------------------- -- - ---UCL;

Q9Averaeaeeegz

gaze--=~

emo-0'Ur/JOnom

"o%3T:=u

7-+=:-s';T>"`>-="*'1>@

;~r>~.;o">-i

,-`Q,~_rw5=/>o

Section 36.8 Statistical Process Control |037LSL USL/_

&*

4... _(a) Unstable (b) Stable

FIGURE 36.1 Illustration of processes that are (a) unstable or out of control and (b) stable orin control. Note in part (b) that all distributions have lower standard deviations than those ofthe distributions in part (a) and have means closer to the desired value. Source: After K. Crow.

Various indicators (indices) are used to determine process capability, describing therelationship between the variability of a process and the spread of lower and upperspecification limits. Since a manufacturing process typically involves materials,machinery, and operators, each factor can be analyzed individually to identify aproblem when process capabilities do not meet specification limits. Among thefactors to be considered are variations in machine performance, operator skills, andincoming raw materials.

LSL USL

EXAMPLE 36.3 Calculation of Control Limits and Standard Deviation

The data given in Table 36.4 show length measure-ments (mm) taken on a machined workpiece. Thesample size is 5, and the number of samples is 10;thus, the total number of parts measured is 50. The

Determine the upper and lowercontrol limits and thestandard deviation for the population of machined partsSolution We first calculate the average of averages, x

quantity E is the average of five measurements in kt ;__L1l_;Lf1___: 112 51 mmeach sample. 10 '

TABLE 36.4Sample number x1 x2 x3 x4 x5 Q R

1 113.3 111.8 112.8 113.3 112.5 112.74 1.52 113.0 112.5 113.5 111.5 111.8 112.46 2.03 111.3 113.8 112.3 112.3 110.5 112.09 3.34 112.3 112.8 115.2 114.0 110.5 112.94 4.65 112.3 113.0 112.5 112.8 112.0 112.52 1.06 112.8 113.0 112.8 111.5 111.8 112.38 1.57 111.5 112.0 112.3 113.3 113.5 112.52 2.08 113.0 112.0 112.5 112.0 114.3 112.76 2.39 112.8 113.3 109.2 111.3 114.0 112.12 4.8

10 112.3 112.5 111.0 113.5 114.0 112.60 3.0


Then we calculate the average of the R values:

- 10 - _ mm1? - Z-QQ - 2 so

Since the sample size is 5, the following constantscan be determined from Table 363: A2 = 0.577,D4 = 2.115, and D3 = O. The control limits nowcan be calculated from Eqs. (36.4) through (36.7).Thus, for averages,

UCL; = 112.51 + (0.577)(2.60) = 114.01 mmand

LCLQ =- 112.51 - (0.577)(2.60) = 111.01 mm

For ranges,

UCLR = (2.115)(2.60) = 5.50 mmand

LCLR= (O)(2.60) = 0 mm

From Eq. (36.10), we can now estimate the standarddeviation or for the population for a value of.iz = 2326:

2.60 _at - 2"f6 - 1.18 mm

CASE STUDY 36.2 Dimensional Control of Plastic Parts in Saturn Automobiles

A typical Saturn automobile has some 38 differentinjection-molded interior plastic parts (polycarbon-ate, polypropylene, and ABS), such as door panels,air-inlet ducts, consoles, and trim. All of these partsmust conform to tight dimensional tolerances so thatthey fit and snap properly during assembly withoutunsightly gaps or buckles. However, the dimensionsof these plastic parts change with temperature andhumidity, and because of their flexibility, the partsalso tend to bend and curl.

For this reason, measurement and inspectionof plastic parts, (including the use of coordinate-measuring machines (CMMs; see Section 35.5.1) canbe difficult. Although traditional gages also are usedfor monitoring process parameters in making these

parts, a superior inspection system has been devel-oped whereby feedback from statistical process con-trol is received from a direct computer-controlledCMM so that the parts are molded properly.

The system compensates for the flexibility ofthe parts, allows automatic measurement of variouspart features, and makes measurements of the moldat periodic intervals. The data are analyzed on a reg-ular basis, and when necessary, corrective actions aretaken and changes are made in materials, processing,or mold design, so that the parts being molded willmaintain good dimensional stability.

Source: Courtesy of Saturn Corp. and ManufacturingEngineering.

36.8.3 Acceptance Sampling and ControlAcceptance sampling consists of taking only a few random samples from a lot andinspecting them to judge whether the entire lot is acceptable or whether it should berejected or reworked. Developed in the 19205 and used extensively during WorldWar II for military hardware (MIL STD 105), this statistical technique is used widelyand has become valuable. Acceptance sampling is particularly useful for inspectinghigh-production-rate parts when 100% inspection would be too costly. However,there are certain critical devices, such as pacemakers, prosthetic devices, and compo-nents of the space shuttle, that must be subjected to 100% inspection.

A number of acceptance sampling plans have been prepared for both militaryand national standards on the basis of an acceptable, predetermined, and limitingpercentage of nonconforming parts in the sample. If this percentage is exceeded, theentire lot is rejected, or it is reworked if economically feasible. Note that the actualnumber of samples (but not the percentages of the lot that are in the sample) can besignificant in acceptance sampling.

Section 36.9 Reliability of Products and Processes |039

The greater the number of samples taken from a lot, the greater is thechance that the sample will contain nonconforming parts, and the lower isthe probability of the lots acceptance. Probability is defined as the relativeoccurrence of an event. The probability of acceptance is obtained fromvarious operating characteristics curves, one example of which is shown inFig. 36.8.

The acceptance quality level (AQL) is commonly defined as the level atwhich there is a 95% acceptance probability for the lot. This percentage in-dicates to the manufacturer that 5% of the parts in the lot may be rejectedby the consumer (producers risk). Likewise, the consumer knows that 95%of the parts are acceptable (consumers risk).

The manufacturer can salvage those lots which do not meet the de-sired quality standards through a secondary rectifying inspection. In thismethod, a 100% inspection is made of the rejected lot, and the defectiveparts are removed. The process is time consuming and costly, and is an in-centive for the manufacturer to control the production process better.

Acceptance sampling requires less time and fewer inspections than doother sampling methods. Consequently, inspection of the parts can be moredetailed. Automated inspection techniques have been developed so that 100%inspection of all parts is possible and inspection can also be economical.

1.0G.)

8_~ 0.4.Q ' 'I'""' '(rg

.Q 0.2O l i

D.O

0 2 4 6 8 10Defective parts (%)

FIGURE 36.8 A typical operating-characteristics curve used in acceptancesampling. The higher the percentage ofdefective parts, the lower is the proba-bility of acceptance by the consumer.

36.9 Reliability of Products and ProcessesAll products eventually fail in some manner or other: Automobile tires become wornand the treads become smooth, electric motors burn out, water heaters begin toleak, dies and cutting tools wear out, and machinery stops functioning properly.Product reliability may be defined as the probability that a product will perform itsintended function in a given environment for a specified period while in normal useby the customer and without failure.

The more critical the application of a particular product, the higher its reliabil-ity must be. Thus, the reliability of an aircraft jet engine, a medical instrument, or anelevator cable must be much higher than that of a kitchen faucet or a mechanicalpencil. From the topics described in this chapter, it can be seen that, as the quality ofeach component of a product increases, so, too, does the reliability of the wholeproduct.

For an ordinary steel chain, the reliability of each link in the chain is critical.Similarly, the reliability of each gear in a gear train for a machine or an automobileis critical. This condition is known as series reliability. By contrast, for a steel cableconsisting of many individual wires, the reliability of each individual wire is notas critical because the cable consists of many wires. This condition is known asparallel reliability. The parallel reliability concept is important in the design ofbackup systems, which permit a product to continue functioning in the eventthat one of its components fails. Electrical or hydraulic systems in an aircraft, forexample, typically are backed up by mechanical systems. Such systems are calledredundant systems.

Predicting reliability is an important science and involves complex mathemati-cal relationships and calculations. The importance of predicting the reliability of thecritical components of civilian or military aircraft is obvious. The reliability of anautomated and computer-controlled high-speed production line with all of its com-plex mechanical and electronic components is also important, as its failure can re-sult in major economic losses to the manufacturer.


Process reliability may be defined as the capability of a particular manufactur-ing process to operate predictably and smoothly over time. Thus, it is implicit thatthere will be no deterioration in performance, which otherwise would require down-time on machines, interrupt production, and result in economic loss.

36.10 Nondestructive TestingNondestructive testing (NDT) is carried out in such a manner that product integrityand surface texture remain unchanged. Nondestructive-testing techniques generallyrequire considerable operator skill, and interpreting test results accurately may bedifficult because the observations can be subjective. However, the use of computergraphics and other enhancement techniques have significantly reduced the likeli-hood of human error. Current systems have various capabilities for data acquisitionand for qualitative and quantitative inspection and analysis.

Listed here are the basic principles of major nondestructive-testing techniques.Liquid Penetrants. In this technique, fluids are applied to the surfaces of the partand allowed to penetrate into cracks, seams, and pores (Fig. 36.9). By capillary action,the penetrant can seep into cracks as small as 0.1 ,um in width. Two common types ofliquids used for this test are (a) fluorescent penetrants, with various sensitivities andwhich fluoresce under ultraviolet light, and (b) visible penetrants, using dyes (usuallyred) that appear as bright outlines on the workpiece surface.

This method can be used to detect a variety of surface defects. The equipmentis simple and easy to use, can be portable, and is less costly to operate than that ofother methods. However, the method can detect only defects that are open to thesurface or are external.

Magnetic-particle Inspection. This technique consists of placing fine ferromag-netic particles on the surface of the part. The particles can be applied either dry or ina liquid carrier, such as water or oil. When the part is magnetized with a magneticfield, a discontinuity (defect) on the surface causes the particles to gather visiblyaround the defect (Fig. 36.1O).

The defect then becomes a magnet due to flux leakages where magnetic-fieldlines are interrupted by the defect. This in turn creates a small-scale N-S pole ateither side of the defect as field lines exit the surface. The particles generally take theshape and size of the defect. Subsurface defects also can be detected by this method,

Surface of Liquid Developing Discontinuityworkpiece penetrant agent revealed

=f-

p I1 Cleaning and 2. Application of 3. Water-wash removal 4. Application of 5. Inspection

drying of surface liquid penetrant of liquid penetrant developing agentto surface from surface but not

the defect

FIGURE 36.9 Sequence of operations for liquid-penetrant inspection to detect the presenceof cracks and other flaws in a workpiece. Source: ASM International.

Sectio

provided that they are not deep. The ferromagnetic particles may becolored with pigments for better visibility on metal surfaces.

The magnetic fields can be generated with either direct current aalternating current, and yokes, bars, and coils. Subsurface defects can bedetected best with direct current. The magnetic-particle method can alsobe used on pure ferromagnetic materials, but the parts have to be demag-netized and cleaned after inspection. The equipment may be portable, orit may be stationary.

Ultrasonic Inspection. In this technique, an ultrasonic beam travelsthrough the part. An internal defect (such as a crack) interrupts thebeam and reflects back a portion of the ultrasonic energy. The amplitudeof the energy reflected and the time required for its return indicate thepresence and location of any flaws in the workpiece.

The ultrasonic waves are generated by transducers (called searchunits or probes), available in various types and shapes. Transducers op-erate on the principle of piezoelectricity (see Section 3.7) using materialssuch as quartz, lithium sulfate, or various ceramics. Most inspections arecarried out at a frequency range from 1 to 25 MHz. Couplants are usedto transmit the ultrasonic waves from the transducer to the test piece;typical couplants are water, oil, glycerin, and grease.

n 36.10 Nondestructive Testing |04|DiscontinuityA B C D E F G

s V A '

eeeee stet

Magnetic Magnetizing Workpiece Hfield current

FIGURE 36.10 Schematic illustration ofmagnetic-particle inspection of a partwith a defect in it. Cracks that are in adirection parallel to the magnetic field(such as discontinuity A) would not be de-tected, whereas the others shown would.Discontinuities F, G, and H are the easiestto detect. Source: ASM International.

The ultrasonic-inspection method has high penetrating power and sensitivity.It can be used from various directions to inspect flaws in large parts, such as railroadwheels, pressure vessels, and die blocks. The method requires experienced personnelto properly conduct the inspection and to correctly interpret the results.

Acoustic Methods. The acoustic-emission technique detects signals (high-frequencystress waves) generated by the workpiece itself during plastic deformation, crack initi-ation and propagation, phase transformation, and abrupt reorientation of grainboundaries. Bubble formation during the boiling of a liquid and friction and wear ofsliding interfaces are other sources of acoustic signals (see also Section 21.5.4).

Acoustic-emission inspection is usually performed by elastically stressing thepart or structure, such as bending a beam, applying torque to a shaft, or internallypressurizing a vessel. Sensors typically consisting of piezoelectric ceramic elementsdetect acoustic emissions. This method is particularly effective for continuous sur-veillance of load-bearing structures.

The acoustic-impact technique consists of tapping the surface of an object, lis-tening to the signals produced, and analyzing them to detect discontinuities andflaws. The principle is basically the same as that employed when one taps walls,desktops, or countertops in various locations with a finger or a hammer and listensto the sound emitted. Vitrified grinding wheels (Section 262) are tested in a similarmanner (ring test) to detect cracks in the wheel that may not be visible to the nakedeye. The acoustic-impact technique is easy to perform and can be instrumented andautomated. However, the results depend on the geometry and mass of the part, so areference standard is necessary for identifying flaws.

Radiography. Radiograp/oy uses X-ray inspection to detect such internal flaws ascracks and porosity. The technique detects differences in density within a part. Forexample, on an X-ray film, the metal surrounding a defect is typically denser and,hence, shows up as lighter than, the flaws. This effect is similar to the way bones andteeth show up lighter than the rest of the body on X-ray films. The source of radia-tion is typically an X-ray tube, and a visible, permanent image is made on a filmor radiographic paper (Fig. 36.11a). Fluoroscopes also are used to produce X-ray

|042 Chapter 36 Quality Assurance, Testing. and Inspection

Film . Lmear detector array

'mage p Workpiece on i

G turntable ""

Image$2 Qc Workpiece processor 5; Source colllmator ~f~;;~fj=f;f=(H) (D)

f "==~.

eeeeea % 'mage- _ 4 \\ ~-~~-~

ea.. ' rocessor ;a--;TT1,,.,4_

p

(C)

FIGURE 36.|I Three methods of radiographic inspection: (a) conventional radiography,(b) digital radiography, and (c) computed tomography. Source: ASM International.

images very quickly, and fluoroscopy is a real-time radiography technique thatshows events as they are occurring. Radiography requires expensive equipment andproper interpretation of results, and can be a radiation hazard. Three radiographictechniques are as follows:

In digital radiography, the film is replaced by a linear array of detectors(Fig. 36.11b). The X-ray beam is collimated into a fan beam (compareFigs. 36.11a and b), and the workpiece is moved vertically. The detectors digi-tally sample the radiation, and the data are stored in computer memory. Themonitor then displays the data as a two-dimensional image of the workpiece.

Computed tomography is based on the same system as described for digitalradiography, except that the workpiece is rotated along a vertical axis as it isbeing moved vertically (Fig. 36.11c) and the monitor produces X-ray imagesof thin cross sections of the workpiece. The translation and rotation of theworkpiece provide several angles from which to view the object precisely.

Computer-assisted tomography (CAT scan) is based on the same principle andis used widely in medical practice and diagnosis.

Eddy-current Inspection. This method is based on the principle of electro-magnetic induction. The part is placed in or adjacent to an electric coil throughwhich alternating current (exciting current) flows at frequencies ranging from 60 Hzto 6 MHZ. The current causes eddy currents to flow in the part. Defects in the partimpede and change the direction of the eddy currents (Fig. 3612) and cause changesin the electromagnetic field. These changes affect the exciting coil (inspection coil),the voltage of which is monitored to determine the presence of flaws.

Inspection coils can be made in various sizes and shapes to suit the geometryof the part being inspected. Parts must be conductive electrically, and flaw depths

Pipe inspection coil Pipe Inspection coilB 4 B -

_Direction of A, ' g. Crackpipe travel < i2c A I f`~A/

Eddy-current s

~ flow

Pipe lneyection CfaCi< section /-\-A section B-Bcol

FIGURE 36.I2 Changes in eddy-current flow caused by a defect in a workpiece. Source: ASMInternational.

Reference-beamSpatial filter Reference-beamReference-beam

mirror#1 /i m'"0f#2Reference beam i

,if ,E ui Variable beam Object-beam 7 *splitter spatial filter

0blf=Cf beam Photographi plate(in holder)

FIGURE 36.I3 Schematic illustration of the basic optical system used in holography elementsin radiography for detecting flaws in workpieces. Source: ASM International.

detected usually are limited to 13 mm. The technique requires the use of a standardreference sample to set the sensitivity of the tester.

Thermal Inspection. Thermal inspection involves using contact- or noncontact-type heat-sensing devices that detect temperature changes. Defects in the workpiece(such as cracks, debonded regions in laminated structures, and poor joints) cause achange in temperature distribution. In t/vermograp/nc inspection, materials such asheat-sensitive paints and papers, liquid crystals, and other coatings are applied tothe workpiece surface. Any changes in their color or appearance indicate defects.The most common method of noncontact-thermographic inspection uses infrareddetectors (usually infrared scanning microscopes and cameras), which have a highresponse time and sensitivities of 1C. Therrnometric inspection utilizes devices suchas thermocouples, radiometers, and pyrometers, and sometimes meltable materials,such as wax-like crayons.

Holography. The holography technique creates a three-dimensional image of thepart by utilizing an optical system (Fig. 3613). Generally used on simple shapes andhighly polished surfaces, this technique records the image on a photographic film.

The use of holography has been extended to holographic interferometryfor the inspection of parts with various shapes and surface features. In responseto double- and multiple-exposure techniques while the part is being subjected to

Section 36.10 Nondestructive Testing |043

|044 Chapter 36 Quality Assurance, Testin, and Inspection

external forces or time-dependent variations, changes in the images reveal defectsin the part.

In acoustic holography, information on internal defects is obtained directlyfrom the image of the interior of the part. In liquid-surface acoustical hologra-phy, the workpiece and two ultrasonic transducers (one for the object beamand the other for the reference beam) are immersed in a water-filled tank. Theholographic image is then obtained from the ripples in the tank.

In scanning acoustical holography, only one transducer is used and the holo-gram is produced by electronic-phase detection. In addition to being more sen-sitive, the equipment usually is portable and can accommodate very largeworkpieces by using a water column instead of a tank.

36.1 I Destructive TestingAs the name suggests, the part tested via destructive-testing methods no longermaintains its integrity, original shape, or surface characteristics. The mechanical testmethods described in Chapter 2 are all destructive, in that a sample or specimen hasto be removed from the product in order to test it. Examples of other destructivetests are the speed testing of grinding wheels to determine their bursting speed andthe high-pressure testing of pressure vessels to determine their bursting pressure.

Hardness tests that leave relatively large indentations (Figs. 2.13 and 2.14)also may be regarded as destructive testing. However, microhardness tests may beregarded as nondestructive because of the very small permanent indentations pro-duced. This distinction is based on the assumption that the material is not notchsensitive (see Section 2.9). Generally, most glasses, highly heat treated metals, andceramics are notch sensitive. Consequently, a small indentation produced by theindenter can reduce their strength and toughness significantly.

36.l2 Automated InspectionTraditionally, individual parts and assemblies of parts have been manufactured inbatches, sent to inspection in quality-control rooms (postprocess inspection) and, ifapproved, placed into inventory. If the parts do not pass the quality inspection, theyare either scrapped or kept and used on the basis of having a certain acceptabledeviation from the standard.

In contrast, automated inspection uses a variety of sensor systems that monitorthe relevant parameters daring the manufacturing operation (online inspection).Using the measurements obtained, the process automatically corrects itself to pro-duce acceptable parts. Thus, further inspection of the part at another location in theplant is unnecessary. Parts also may be inspected immediately after they are produced(in-process inspection).

The development of accurate sensors and advanced computer-control systemshas enabled automated inspection to be integrated into manufacturing operations(Chapters 37 and 38). Such a system ensures that no part is moved from one manufac-turing process to another (e.g., a turning operation followed by cylindrical grinding),unless the part is made correctly and meets the standards in the first operation.

Automated inspection is flexible and responsive to product design changes.Furthermore, because of automated equipment, less operator skill is required, pro-ductivity is increased, and parts have higher quality, reliability, and dimensionalaccuracy.

Sensors for Automated Inspection. Continued advances in sensor technology, de-scribed in Section 37.7, have made online or real-time monitoring of manufacturingprocesses feasible. Directly or indirectly, and with the use of various probes, sensorscan detect dimensions, surface roughness, temperature, force, power, vibration, toolwear, and the presence of external or internal defects.

Sensors may operate on the principles of strain gages, inductance, capacitance,ultrasonics, acoustics, pneumatics, infrared radiation, optics, lasers, or various elec-tronic gages. Sensors may be tactile (touching) or nontaetile. They are linked to mi-croprocessors and computers for graphic data display (see also programmable logiccontrollers, Section 37.2.6). This capability allows the rapid online adjustment ofany processing parameter, thus resulting in the production of parts that consistentlyare within specified standards of dimensional tolerance and quality. For example,such systems already are standard equipment on many metal-cutting machine toolsand grinding machines described in Part IV of this book,

SUMMARY Quality must be built into products. Quality assurance concerns various aspects

of production, such as design, manufacturing, assembly, and especially inspec-tion, at each step of production for conformance to specifications.

Statistical quality control and process control are indispensable in modern manu-facturing. They are particularly important in the production of interchangeableparts and in the reduction of manufacturing costs.

Although all quality-control approaches have their limits of applicability, the im-plementation of total quality management, the ISO and QSO 9000 standards,and the ISO 14000 standard are among the most significant developments inquality control in manufacturing.

Several nondestructive and destructive testing techniques (each of which has itsown applications, advantages, and limitations) are available for inspection ofcompleted parts and products.

The traditional approach of inspecting the part or product after it is manufac-tured has been replaced largely by online and 100% inspection of all parts andproducts being manufactured.

KEY TERMSAcceptance quality levelAcceptance samplingAssignable variationsAutomated inspectionChance variationsCommon causeConsumers riskContinuous improvementControl chartsControl limitsDefect prevention

Deming methodsDestructive testingDispersionDistributionEnvironmental management

systemsExperimental designF actorial designFrequency distributionGrand averageISO standards

_Iuran methodsKaizenLot sizeLower control limitMethod of attributesMethod of variablesNondestructive testingNormal distribution curvePopulationProbabilityProcess capability

Key Terms |045

Process reliabilityProduct reliabilityProducers riskQualityQuality assuranceQuality circleQS standardsRandom samplingRangeReliabilityReturn on quality


Robustness Special causeSample size Specification limitsSensors Standard deviation

Statistical processcontrol

Shewhart control chartsSix sigma

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REVIEW QUESTIONS

Statistical quality Total quality controlcontrol Total quality management

Statistics Upper control limitTaguchi loss function VariabilityTaguchi methods

juran, ].M., and Godfrey, A.B. (eds.), _]urans QualityHandbook, Sth ed., McGraw-Hill, 2000.

Kales, P., Reliability: For Technology, Engineering, andManagement, Prentice Hall, 1997.

Kear, EW., Statistical Process Control in ManufacturingPractice, Marcel Dekker, 1997.

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Montgomery, D.C., Introduction to Statistical QualityControl, 6th ed., Wiley, 2008.

Park, S., Robust Design and Analysis for Quality Engineering,Chapman 86 Hall, 1997.

Quensenberry, C.P., SPC Methods for Quality Improvement,Wiley, 1997.

Raj, B., jaykumar, T., and Thavasimuthu, M. (eds.), PracticalNon-Destructive Testing, 2nd ed., ASM International,2002.P.]., Taguchi Techniques for Quality Engineering,

2nd ed., McGraw-Hill, 1996.Ryan, T.P., Modern Experimental Design, Wiley, 2007.Smith, G.M., Statistical Process Control and Quality

Improvement, Sth ed., Prentice Hall, 2004.Taguchi, G., Introduction to Quality Engineering, UNIPUB/

Kraus International, 1986.1-, Taguchi on Robust Technology Development: BringingQuality Engineering Upstream, ASME Press, 1993.

Tozawa, B., and Bodek, N., The Idea Generator: Quick andEasy Kaizen, PCS Press, 2001.

Ross,

36.1. Define the terms sample size, random sampling,population, and lot size.36.2. What are chance variations?36.3. Explain the difference between method of variablesand method of attributes.36.4. Define standard deviation. Why is it important inmanufacturing?36.5. Describe what is meant by statistical process control.36.6. Explain why control charts are developed. How arethey used?

36.7. What do control limits indicate?36.8. Define process capability. How is it used?36.9. What is acceptance sampling? Why was it developed?36.l0. Explain the difference between series and parallelreliability?36.| I. What is meant by six sigma quality?36.|2. Explain the difference between (a) probability andreliability and (b) robustness and reliability?

36.l8. Which of the nondestructive inspection techniques |]36.25. What is a Taguchi loss function? What is its

|]36.29. Calculate the control limits for (a) number of

QUALITATIVE PROBLEMS

Synthesis, Design, and Projects |047

36.|3. Explain why major efforts are continually beingmade to build quality into products.36.l4. Give examples of products for which 100% samplingis not possible or feasible.36.I5. What is the consequence of setting lower and upperspecifications closer to the peak of the curve in Fig. 36.4?36.|6. Identify several factors that can cause a process tobecome out of control.36.|7. Describe situations in which the need for destructivetesting techniques is unavoidable.

are suitable for nonmetallic materials? Why?36.l9. What are the advantages of automated inspection?Why has it become an important part of manufacturingengineering?

QUANTITATIVE PROBLEMS36.26. Beverage-can manufacturers try to achieve failurerates of less than one can in ten thousand. lf this correspondsto n-sigma quality, find n.|]36.27. Assume that in Example 36.3 the number of sam-ples was 8 instead of 10. Using the top half of the data in Table36.4, recalculate the control limits and the standard deviation.Compare your observations with the results obtained by using10 samples.|}36.28. Calculate the control limits for averages and rangesfor (a) number of samples = 8 (b) E = 65, and (c) R = 6.

samples = 6, (b) T = 36.5, and (C) UCLR = 5.75.|]36.30. In an inspection with a sample size of 12 and asample number of 40, it was found that the average rangewas 14 and the average of averages was 80. Calculate thecontrol limits for averages and for ranges.

36.20. Why is reliability important in manufacturing engi-neering? Give several examples.36.2l. Give examples of the acoustic-impact inspectiontechnique other than those given in the chapter.36.22. Explain why GO and NOT GO gages (see Section35.4.4) are incompatible with the Taguchi philosophy.36.23. Describe your thoughts regarding the contents ofTable 36.1.36.24. Search the technical literature and give examples ofrobust design in addition to that shown in Fig. 36.1.

significance?

u36.3|. Determine the control limits for the data shownin the following table:

X1 X2 X3 X4

0.57 0.61 0.50 0.550.59 0.55 0.60 0.580.55 0.50 0.55 0.510.54 0.57 0.50 0.500.58 0.58 0.60 0.560.60 0.61 0.55 0.610.58 0.55 0.61 0.53

|]36.32. The average of averages of a number of samplesof size 9 was determined to be 124. The average range was17.82 and the standard deviation was 4. The following meas-urements were taken in a sample: 121, 130, 125, 130, 119,131, 135, 121, and 128. ls the process in control?

SYNTHESIS, DESIGN, AND PROJECTS36.33. Which aspects of the quality-control concepts ofDeming, Taguchi, and ]uran would, in your opinion, be diffi-cult to implement in a typical manufacturing facility? Why?36.34. Describe your thought on whether products shouldbe designed and built for a certain expected life. Would youranswer depend on whether the products were consumer orindustrial products? Explain.

36.35. Survey the available technical literature, contact vari-ous associations, and prepare a comprehensive table concern-ing the life expectancy of various consumer products.36.36. Would it be desirable to incorporate nondestructiveinspection techniques into metalworking machinery? Give aspecific example, make a sketch of such a machine, andexplain its features.


36.37. Name several material and process variables that caninfluence product quality in metal (a) casting, (b) forming,and (c) machining.36.38. Identify the nondestructive techniques that are capa-ble of detecting internal flaws and those which detect exter-nal flaws only.36.39. Explain the difference between in-process andpostprocess inspection of manufactured parts. What trendsare there in such inspections? Explain.

36.40. Many components of products have a minimal effecton part robustness and quality. For example, the hinges in theglove compartment of an automobile do not have an impacton the oWners satisfaction, and the glove compartment isopened so infrequently that a robust design is easy to achieve.Would you advocate using Taguchi methods (such as lossfunctions) on this type of component? Explain.

PART

Manufacturingin a CompetitiveEnvironment

In a highly competitive global marketplace for consumer and industrial goods,advances in manufacturing processes, machinery, tooling, and operations are beingdriven by goals that can be summarized as follows:

Products must fully meet design and service requirements, specifications, andstandards.

Manufacturing activities must continually strive for higher levels of qualityand productivity; quality must be built into the product at each stage of designand manufacture.

Manufacturing processes and operations must have sufficient flexibility torespond rapidly to constantly changing market demands.

The most economical methods of manufacturing must be explored andimplemented.

Although numerical control of machine tools, beginning in the early 1950s, wasa key factor in setting the stage for modern manufacturing, much of the progress inmanufacturing activities stems from our ability to view these activities and operationsas a large system with often complex interactions among all of its components.In implementing a systems approach to manufacturing, We can integrate and optimizevarious functions and activities that, for a long time, had been separate and distinctentities.

As the first of the four chapters in the final part of this book, Chapter 37 intro-duces the concept of automation and its implementation, in terms of key developmentsin numerical control and, later, in computer numerical control. This introduction isfollowed by a description of the advances made in automation and controls, involvingmajor topics such as as adaptive control, industrial robots, sensor technology, materialhandling and movement, and assembly systems and hovv they are all implemented inmodern production.

Manufacturing systems and how their individual components and operations areintegrated are described in Chapter 38, along with the critical role of computers andvarious enabling technologies as an aid in such activities as design, engineering, manu-facturing, and process planning. The chapter also includes discussions on variousenabling technologies, such as adaptive control, indusrial robots, sensor technology,flexible fixturing, and assembly systems.

|049

|050 Part IX Manufacturing in a Competitive Environment

Computer-integrated manufacturing, with its Various features, such as cellularmanufacturing, flexible manufacturing systems, just-in-time production, lean manu-facturing, and artificial intelligence, are then described in Chapter 39. Included also isthe new concept of holonic manufacturing and the role and significance of communi-cation networks.

The purpose of Chapter 40 is to highlight the importance of the numerous andoften complex factors and their interactions that have a major effect on competitivemanufacturing in a global marketplace. Among the factors involved are product design,quality, and product life cycle; selection of materials and processes and their substitu-tion in economical production; process capabilities; and costs involved, including thoseof machinery, tooling, and labor.

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CHAPTER

ManufacturingProcesses

This chapter describes automation in all aspects of manufacturing processesand operations, by which parts are produced reliably, economically, and accu-rately at high production rates.

The chapter begins with a description of the types of automation and theirvarious applications.

Flexibility in manufacturing through numerical control of machines is thendiscussed, with detailed descriptions of their important features.

The chapter investigates the different control strategies that can be used, in-cluding open-loop, closed-loop, and adaptive control.

Industrial robots are then reviewed, including their capabilities and guidelinesfor applications.

A discussion of sensor technology and its important applications follows. The chapter ends with a comprehensive description of fixturing and assembly

systems in manufacturing and their design considerations.

37.1 IntroductionUntil the early 195 Os, most operations in a typical manufacturing plant were carriedout on traditional machinery, such as lathes, milling machines, drill presses, and vari-ous equipment for forming, shaping, and joining materials. Such equipment generallylacked flexibility, and it required considerable skilled labor to produce parts withacceptable dimensions and characteristics. Moreover, each time a different producthad to be manufactured, the machinery had to be retooled, fixtures had to be pre-pared or modified, and the movement of materials among various machines had to berearranged. The development of new products and of parts with complex shapes re-quired numerous trial-and-error attempts by the operator to set the proper processingparameters on the machines. Furthermore, because of human involvement, makingparts that were exactly alike was often difficult, time consuming, and costly.

These circumstances meant that processing methods generally were inefficientand that labor costs were a significant portion of the overall production cost. Thenecessity for reducing the labor share of product cost became increasingly apparent, asdid the need to improve the efficiency and flexibility of manufacturing operations.

37.l Introduction |05|37.2 Automation |05337.3 Numerical Control |06037.4 Adaptive Control |06637.5 Material Handling and

Movement |06837.6 Industrial Robots I07|37.7 Sensor Technology |07737.8 Flexible Fixturing I08I37.9 Assembly Systems |08337.l0 Design Considerations for

Fixturing, Assembly,Disassembly, andServicing |086

37.I I EconomicConsiderations |089

EXAMPLES:

37.| Historical Origin ofNumerical Control I06|

31.2 Special Applications ofSensors |080

CASE STUDY:

37.| Robotic Deburringof a Blow-moldedToboggan |076

l05l

|052 Chapter 37 Automation of Manufacturing Processes

Productivity also became a major concern. Generally defined as output peremployee per hour, productivity basically measures operating efficiency. An efficientoperation makes optimum use of all resources, such as materials, energy, capital,labor, machinery, and available technology. With rapid advances in the science andtechnology of manufacturing, the efficiency of manufacturing operations began toimprove and the percentage of total cost represented by labor began to decline.

In improving productivity, the important elements have been mechanization,automation, and control of manufacturing equipment and systems. Mechanizationcontrols a machine or process with the use of various mechanical, hydraulic, pneu-matic, or electrical devices; it reached its peak by the 1940s. In spite of the obviousbenefits of mechanized operations, the worker would still be directly involved in aparticular operation and would continually check a machines overall performance.Consider, for example, the following situations: (a) A cutting tool wears or fracturesduring a machining operation, (b) a part is overheated during heat treatment, (C) thesurface finish of a part begins to deteriorate during grinding, or (d) dimensional tol-erances and springback become too large in sheet-metal forming. In all these situa-tions, the operator must intervene and change one or more of the relevant processparameters and machine settings-a task that requires considerable experience.

The next step in improving the efficiency of manufacturing operations wasautomation, a word coined in the mid-1940s by the U.S. automobile industry toindicate the automatic handling and processing of parts in and among productionmachines. Although there is no precise definition, automation generally means themethodology and system of operating a machine or process by highly automaticmeans (from the Greek word automatos, meaning self-acting). Rapid advancesin automation and the development of several enabling technologies were then madepossible, largely through advances in control systems, with the help of increasinglypowerful and sophisticated computers and software.

This chapter follows the outline shown in Fig. 37.1. First, it reviews the historyand principles of automation and how it has helped to integrate various key opera-tions and activities in a manufacturing plant. It then introduces the concept of thecontrol of machines and systems through numerical control and adaptive controltechniques. The chapter also describes how the important activity of material han-dling and movement has been developed into various systems, particularly thoseincluding the use of industrial robots to improve handling efficiency.

.ffs\1 .s~i5 .~~,s,ss$eW~s~.~ Automation of manufacturing processes 3 -E Sensors 3

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The subject of sensor technology is then described; this is a topic that is an es-sential element in the control and optimization of machinery, processes, and sys-tems. Significant developments in flexible fixturing and assembly operations arecovered as well. These methods enable us to take full advantage of advanced manu-facturing technologies, particularly flexible manufacturing systems. The chapteralso includes a discussion of the guidelines for design, for assembly, for disassembly,and for service, with specific recommendations to improve the efficiency of each ofthese operations. The final topic of the chapter describes the economics of the equip-ment, processes, and operations covered.

31.2 AutomationAlthough there have been various definitions, automation generally is defined

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