QUALITY

A BRIEF HISTORYOF QUALITY

To impose quality on a recalcitrant manufacturing process needs blood, sweat,toil and a good size toolbox of quality methods. Brian Hundy is brave enough

to open Pandora's Box and look over the major techniques on offer.

It is unfortunate that fashion seems to play alarge part in the introduction of new ideas inindustry. Today, in the area of production andstock control, the main interest is in Just in

Time while yesterday's star, MRP, is relegated to thesecond division. Quality seems to be subject tofashion as much as any other aspect of business,but it is fortunately in vogue at the moment. Industryis now paying great attention to this with many firms,large and small, aiming for approval to BS 5750.

It is to be sincerely hoped that this currentinterest is not just a fad and that the concept ofimproved quality will survive and continue to beseen as vital to the future of any business.

It is not the intention here to review the wholefield of quality techniques and concepts that havebeen put forward over the last few decades. Thatwould take a large book. The aim is rather to lookat some of the more recent ideas put forward to seeif there is any commonality and if they can beintegrated.

Figure 1 summarises a number of differentquality concepts and their range of application in atypical manufacturing firm. Many of these can beequally well applied to the service industry but forbrevity most of the discussion will refer to manufac-turing.

Basic toolsThese are the basic techniques of quality assur-

ance & control and can be used for trouble shootingon a quality problem as well. They tend to be usedmainly by the technical experts but also by shopfloor operatives when they have been trained. Theyinclude:-

Pareto Chart • A vertical bar graph in which

the problems are categorised and the frequency ofeach plotted against the category in order. It isusually found that a very few problems account formost of the overall defect level and these can betargeted for action.

Cause and Effect Diagram - This is some-times called a 'fishbone' or Ishikawa diagram. Theeffect to be analysed is put on the right of the diagramand the likely factors are shown as branches on themain line. The general causes shown in this figureare typical for a manufacturing problem. Each ofthese is considered in turn and the factors affectingeach are entered as further branches on the line.Discussion of each of these causes will often sug-gest modifications and experiments to solve theproblem. Brainstorming with a mixed disciplineteam is a good way of developing this.

Process Flow Diagram - This technique isfrequently useful in many different functional areasin a variety of firms. People often think they knowthe route taken by a product or a piece of paper, butcan be surprised when it is actually written down.Once it is on paper it is possible to look at each stageof the process and identify possible incoming vari-ations and the likely effect of these on outgoingvariations.

Run Charts - A run chart is a plot over time ofa variable which is thought to be important. Thespread in results will give some indication as towhether the process is subject to changes or if it isconsistant over a time period. Changes in the pat-tern of the plot may suggest hypotheses about theircause, eg they may occur at shift changeover or atthe beginning of the week.

Scatter Diagram - This is a plot of two factors(usually a measure of a problem and a possiblecause) which might be related. A relationship may

be obvious to the eye and simple statistical tech-niques can be used to draw the line best fitting theresults and to show whether the apparent relation-ship is statistically significant. Often a problem maybe affected by more than one variable and the tech-nique of multiple correlation may used to investigatethis. A number of statistical packages are nowavailable for use on personal computers which arevery helpful for these types of problem.

Statistical process controlThis involves constructing control charts which

are similar to run charts, but statistically calculatedupper and lower limits are shown on the chart basedon the normal random variations in the process.Action is taken to adjust the process controls whendisturbances are noted so that the process is keptwithin the limits.

For instance the plot may show the process tobe generally under control, except at the start of theday and night shifts. This could be due to themachine cooling down when not in use and stepscould be taken to overcome this. SPC can be appliedto attributes (pass/fail, go/no go etc) as well as tonumerate values. SPC is being used increasinglyand many large firms are insisting on its use by theirsuppliers as part of their quality approval system.

Operatives and technical staff are generally mostconcerned with this technique though it is to behoped that supervisors and managers are equallyconcerned with its application.

Failure modes and effects analysisThis is first of all a tool for the design engineer

working in collaboration with the manufacturingengineer. The discipline requires the engineer toconsider every component in a design and assess

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QUALITY

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Figure 1 .Range ofappljcation ofqualitytechniques in atypicalmanufacturingorganisation.D =DirectorsM =ManagersT =Technical0 =OperativesS =Sales &MarketingD =DevelopmentM =Manufacture

Figure 2.Cause andEffect diagramfor a metalcuttingproblem.a (top); Generaldiagramshowingpossiblecauses.b (bottom);Detaileddiagram for the'Material'effect

first all its possible modes of failure (fatigue, wear,corrosion, electrical short circuit etc). Each of thesepossible failures is then considered for its likelyeffect on the product (noise, inoperability, smell,excessive effort needed, etc) along with the potentialcauses of failure (wrong material used, thinning,poor painting, assembly error, etc). Controls inmanufacture are noted and the probability of failureis estimated taking previous history of similar com-ponents into account.

A ranking of 1-10 is given to this as well as tothe severity of the effect of failure on the customer(1=not noticed;10 = Potential life and limb risk) andto the probability that the cause will be detected inmanufacture. Multiplying the three rankingstogether will give a number of between 1 and 1000.

Action has to be taken to reduce the higher numbersto an acceptable level, say 100.

An example could be a pressed steel part on acar suspension. The modes of failure could befatigue, fracture, corrosion or buckling. The result offailure could be erratic handling or loss of control.The probability of failure would be assessed for allof the potential causes of failure and there may be15 or 20 of these.

One of these may be that the thickness of thesteel sheet supplied is below that specified and thiscould lead to fatigue failure. The engineers mightgive a ranking of 4 to the probability of this failureoccuring. The severity of response to failure willprobably be ranked 10 as it could mean the car goingout of control. There are occasional quality checks

on the pressing which suggests that there is amoderate chance of the defect reaching the customer-a ranking of 5.

Thus the product of the rankings is 200(4x10x5), which suggests that corrective action isneeded. Incorporating automatic thickness checkson the strip before pressing should reduce the chan-ces of occurence to a ranking of 1. This now givesan overall figure of 50, which is acceptable.

The technique can also be applied to processesas well as products and manufacturing engineerswould take the lead here. FMEA can be a verypowerful tool if carried out conscientiously but it isvery time consuming and, because of this, can fallinto disuse after an enthusiastic start.

Quality circlesIntroduced from Japan more than 10 years ago,

after an enthusiastic reception this idea has nowrather fallen out of favour. The concept is based onthe belief that the operatives on the line probablyknow more about what can go wrong in manufacturethan anybody else.

The quality circle is a means of harnessing thisknowledge. Volunteers from a particular area in theworks form the circle and they choose a qualityproblem to investigate. They often have an inde-pendant facilitator to help them in methodology andthey will usually be trained inapplication of the basictools. It is normally recommended that no supervi-sors are involved directly in the circle and it iscommon for the team to meet outside working hours.

Implementation often involves system changeor expense requiring management involvment andexperience has shown that quality circles are onlyreally effective in companies which practise a par-ticipative style of management. Unless the team seetheir ideas adopted enthusiastically they soon stopbothering. It is also felt that sometimes teams canrun out of problems and some firms have nowmoved to productivity circles often with the involve-ment of the'foreman as team leader.

Deming's 14 pointsDr WE Deming was one of the US prophets of

quality who found a ready reception for his ideas inJapan after the war. It was only when the West wokeup to the remarkably high levels of quality achievedby that country that they began to listen to hismessage. Although a proponent of using statisticaltechniques, it is mainly the philosophy he expoundsthrough his 14 Points that is important.

One example is point 1: "Create constancy ofpurpose towards improvement of product and ser-vice, with the aim to become competitive, stay inbusiness and provide jobs". It can be seen that he isprimarily addressing management. He argues acase for continuous improvement and is no believerin the efficacy of slogans or inspection to give goodquality. He is a firm advocate of improved systemsand of effective training, especially on the job.

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Design of experimentsWhen investigating a quality problem it is com-

mon to alter just one particular variable or institutea new control in the belief that this might cure theproblem. Instinct of this sort does sometimes workbut often the solution proves more elusive. The faultmay be due to another unexplored factor or beaffected by more than one factor.

One answer is to devise a planned set of experi-ments changing all the variables which may bethought to have some effect. The numbers of experi-ments however rapidly becomes excessive if thenumber of possible variables is high. For instanceif seven possible variables were to be tested at eachof two levels then, using a statistically valid fullfactorial experimental design, 128 runs would berequired. This will show which of the variables hasan effect and also if there are interactions betweenvariables (eg temperature may have less effect on aprocess in the presence of one catalyst than another)In many industrial processes a run may consist of aperiod of production (eg a shift), with the number ofdefects per period being the dependent variable.Such experiments can be time consuming and veryexpensive.

Special fractional factorial designs have beendevised by statisticians which can reduce the num-ber of runs significantly, but this gives some loss inaccuracy. Another quality guru, Dr Taguchi, is prob-ably best known for his Design of experiments usingorthogonal arrays and he claims that these canreduce the number of experiments very consider-ably, eg from 128 to 8 in the case of seven variables.Some statisticians query the validity of his metho-dology but there is no doubt that it has provedextremely effective in helping to solve many practi-cal problems.

Taguchi methodsAlthough, as mentioned above, Dr Taguchi is

best known for his DOE methods he has developedmore general ideas that are well worthy of consider-ation. He distinguishes clearly between 'on-line'and 'off-line' quality control. On-line quality controlrefers to the checks and controls used in the manu-facturing processes to ensure that they are underproper control (eg SPC). A tolerance band of valuesof dimension or other control factor is usually setand the process must be controlled to keep withinthe band.

Often no changes will be made to the processuntil one or other of the tolerance limits is reachedand Dr Taguchi argues that this is not the best way.He believes the process should be monitored con-tinuously and when any deviation occurs from thetarget value, action should be taken to bring theprocess back on target. This will give the customera product which is more likely to be near the opti-mum quality. He has developed this concept into ageneral quality loss function which is more con-troversial.

Perhaps his greatest contribution, however, ishis concept of off-line quality control. As with manyothers he believes strongly that quality is firmly setin the design office. Quality in service is shown bythe product's performance in use, ie by the way inwhich the design meets the desired functional re-quirements. Variations in this performance can bedue to problems in manufacturing, to changes withtime in service such as wear (Taguchi calls this'inner noise') and to outside factors such as condi-tion of use, ambient factors such as temperature, linevoltage etc ('outer noise').

These outer enviromental noises cannot be con-trolled by the designer but Taguchi says that it isoften possible to develop robust designs which arenot very sensitive to such noise. He advocates theuse of designed experiments where the factors to beinvestigated would include deliberately introducednoise conditions as well as the parameters neededfor the best functional performance. The results ofsuch experiments will often indicate ways in whichthe component parameters can be selected to mini-mise the enviromental noise factors.

BS5750This standard is the same as the International

Standard 9000 and the European EN29000 and in itsmost complete form (Part 1) covers the whole systemfrom design through to supply of a product or service.The standard is written essentially to cover the supplyof material but can be (and is) interpreted to cover thesupply of a service and recently the BSI has extendedits Registered Stockist scheme to bring it within Part 2of BS5750.

It sets out to define the quality systems necess-ary for a supplier to provide material of satisfactoryquality to a purchaser and starts with a statement ofquality objectives by the company together with aquality manual which shows how these will beachieved. The specific way in which this quality isdetermined is seen as being unique to each supplier,it accepts that the resources of the firm may affectthe specific quality requirements and it is left to himto define what is required. As large firms begin toadopt systematic quality procedures they see thesignificant advantage of being able to minimiseincoming checks by encouraging their suppliers toseek approval of their quality systems to this stand-ard.

Greater use of this standard is to be applaudedand all manufacturing and service firms shouldconsider applying for registration. The effort re-quired should not be under estimated though therewards can be great. It is interesting that the mostpopular current option in the DTI Enterprise Iniativeis now quality, with registration to BS5750 as themain aim.

The only weakness is that the standard assumesthat the quality policy set by the firm's Board iscorrect and will assure that customers receive goodsof exactly the quality they need. BS5750 assures

approval of the system but does not necessarilyenquire deeply into the full quality needs of thecustomer and may not assure this fully.

Quality function deploymentThis total quality concept brings together both a

philosophy and a variety of techniques and providesperhaps the most complete methodology to date.For this reason and because it is not yet well knownit will be covered here in rather more depth.

Its prime philosophy is to translate "The Voiceof the Customer" through a series of stages (asdescribed below) into a product which effectivelymeets the customer's full needs. The product maybe a manufactured item such as a refrigerator or aservice such as banking. An essential part of QFDis that it can only be developed by a multi-disciplineteam working together at all stages.

Customer Needs - This first step is the mostimportant and also in many ways the most difficult.All design and marketing staff think they know exact-ly what the customer wants but their knowledge maybe incomplete or expressed in technical terms only.For example the customer, in addition to the normalneeds of rain and windproofing, may like his carwindow to be self wiping when opened and closed.It is essential to express the customer needs in theirown words and then convert these to technical re-quirements.

All the needs should be identified by marketresearch, customer clinics, etc and then brokendown into sub-needs which can be clearly identified,eg a customer need for low noise in a car may bebroken down into: wind noise, road noise, enginenoise, squeaks and rattles etc and perhaps some ofthese in turn into further subsets.

Translation of customer needs into de-sign specification - This can be very time con-suming as it is necessary to take each need, assubdivided, and convert it into a requirement whichcan be specified in the form of a test. QFD metho-dology requires that this be done by constructing amatrix of needs against design requirements. Asimple example is for a car seat with the expandedneeds down the left hand side and suggested designrequirements across the top (figure 3).

Correlations are shown by symbols in the ap-propiate square and it will be noted that some of thedesign requirements can correlate with more thanone need. It is also likely that some of the designpoints may not be compatible with each other. Anexample of this could be the need for the seat to holddriver and passenger in place on corners: this couldmean a design requirement of a wrap around seatdefined by the geometry but this could be in conflictwith the geometry requirement for easy entry. Tocover such conflicts a triangular matrix has to beconstructed across the top of the table to enable thecross correlation of all design points.

Any strong negative correlations have to be dis-

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cussed and a compromise reached. Other datawhich has to be entered tor a full QFD matrix tableincludes: a column for previous service complaintsagainst each need; a column showing agreedrelative importance of each need; a column whichassessess the strength of competitors' productsagainst the existing product for each need; a rowshowing the objective target value for each designaim; a row showing the likely technical difficulty inmeeting each design requirement; a row givingmeasurements on competitors products for eachtest; rows showing the number and cost of servicerepairs for each technical requirement; rows cover-ing regulatory and other control items, eg headrestraint rules and, not least, a row to show theimportance of each design requirement based on thedegree of importance to the customer of each relatedneed.

The example given here is for a physical productbut a similar matrix can be derived for a serviceactivity such as training or selling. An example ofthis could be for a company selling PCs by mailorder. The customer needs could include:- lowprices, fast delivery, reliable products, good choice,fast & user friendly response to orders, expert adviceetc. and these can be translated to service designrequirements in a similar way to the above.

Translation of design requirements intothe actual design - This next stage is to interpretthe design requirements and associated tests intothe real parts of the product or service. The itemsrated as being most important are selected andanother matrix is created where the "hows" of thetechnical requirments are now put down the left handside of the table as a column of new "whats".

The detai Is of the design in terms of the parts andthe part characteristics is then developed across thetop of the table.

The design process should involve a multi-dis-cipline team again to ensure good design for manu-facture as well as the required quality. A number oftechniques may be used during this design processto ensure full consideration of how the design re-quirements will be met.

They will probably include cause and effect di-agrams, FMEA and Taguchi's off-line quality controlusing Design of Experiments to ensure robust de-signs which are not sensitive to 'outer noise'. Othertechniques which are very helpful include the Pughconcept selection method and competitive bench-marking.

In this latter, very powerful technique, competi-tive products are obtained and disassembled, thecost of the parts and assembly are estimated and aparts list is produced for each.

A functional analysis is then carried out as invalue engineering so that the function(s) providedby each part can be evaluated.

If both the Bill of Materials and the functions areshown as interrelated trees then the cost of eachfunction and sub-function can be determined for

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Figure 3.QFD;Interrelationsbetweencustomerneeds andqualitydesignrequirementsfor a car seat

each of the competitive products as well as for theexisting product.

This will usually spark off ideas in the team, butat worst the cheapest way of meeting the functionwhich is used by a competitor can be adopted.

An example of this approach can be seen byconsidering the combination of suspension andfoam padding in the seat needed for the static anddynamic response specified to meet the customerneeds of resilience and vibration minimisation.

Competitive benchmarking shows that competi-tors do this in a variety of ways with different typesand thicknesses of foam, different combinations ofspringing and support pads etc.

The relative costs of achieving the functions andthe response to the specified tests will be assessedand new ideas will be developed. It may be foundthat one combination meets the specifications veryeasily while another, rather cheaper one, may just beadequate. Providing that the tests are satisfactorythen the cheaper solution would be chosen unlessit is felt that the more expensive solution wouldprovide a significant selling point.

This sort of analysis will be repeated until ac-ceptable designs have been achieved which met thetests specified. The essential tolerances for criticalfeatures on each part will of course be itemised.

On occasion conflicting features may be en-countered and compromise may need reappraisal ofthe initial customer needs matrix.

Selection and planning of the manufactur-ing processes - This is similar to normal processplanning and while the team approach would still beused in QFD the manufacturing engineers wouldnow take the lead role.

Again the most critical parts will be selected forexamination in the QFD process bearing in mind any

past history of sensitivity to process variation. Theprocess may already be determined or a new ormodified process may need to be developed. Oncethe process is clear then a process flow diagram willbe drawn up and each step in the flow consideredfor the critical parameters which could affect itsability to meet the specified tolerances.

The capability of the process will thus be verifiedand if necessary optimised to minimise variation(perhaps using Taguchi methods). The critical pro-cess parameters will be identified so that the pro-duction planning can be carried out to specify theprocess controls, SPC requirements, maintenanceschedules and all other on-line quality controls.

Experience has shown that Quality Function De-ployment is a very valuable way of achieving highquality standards. The necessary heavy load of timeand resources has unfortunately tended to mitigateagainst its more extensive use, but there are signsof it being used more by some of our more forwardlooking firms.

ConclusionsIt can be seen from this review of quality meth-

ods and philosophies that there is a strong connec-tion between the various points and that some of themore general ideas covered in the later part drawheavily on the more specific topics covered earlier.In particular QFD is a very wide ranging approachand any company using such an approach in con-junction with BS5750 will beableto assure a qualitywhich should well satisfy their customers andshould improve market share and profits. EQ

Brian Hundy was Professor of Manufacturing Man-agement at Cranfield Institute of Technology. He isnow an Independent Consultant.

MANUFACTURING ENGINEER SEPTEMBER 1991