Quality Function Deployment: Taking Quality Upstream

Ronald M. Fortuna

s Statistical Process Control (SPC) Evolution of Quality Control Activities Ian important tool for improving quality and productivity? Yes. Will ~ SPC allow American manufacturers t Design Improvement to meet the quality and cost chal­ Gl lenges of the future? No, not by it­ E self. As observed by Dr. Kaoru Ishikawa, we are seeing quality ac­ ~ Process Control CI. tivities evolve into a new generation. E The first two generations, inspection - and manufacturing process control, ~ are gradually giving way to a third ii ~ Inspection - product and process design im­ G'--- _ provements (Fig. 1). Two emerging 1920 1940 1960 1980 methodologies are at the forefront of this movement: Quality Function De­ Fig. 1. ployment and Taguchi methods. SPC is a preventive measure, quality improvements made in the but only to a point. It addresses only design stages. Quality Function Deployment the variation introduced by the pro­ Quality Function Deployment and Taguchi methods are duction process itself. That is, SPC and Taguchi methods are aimed at aimed at solving quality involves fixing what is wrong and solving quality problems at a much problems at a much earlier attempting to reduce variation after earlier stage than SPC - improving stage than SPC - improving release for production. Prevention product and process design before product and process design manufacture. As shown in Fig. 2, and reduction of variation should before manufacture. begin during the design of the prod­ you can protect against environmen­ uct and the production process. tal variables and product deteriora­ Control charts in Japan are now tion only at the product design In its broadest meaning, QFD is one of the "Seven Old Tools" (along stage. Product and process design a philosophy of planning and devel­ with Pareto analysis, cause-and­ optimization also can significantly re­ opment. Customer requirements and effect diagrams, data stratification, duce manufacturing variations. The desires are deployed vertically and check sheets, histograms, and scat­ net effect is a reduction of variation horizontally throughout the organiza­ ter diagrams). Mastery of these in product quality and performance tion. Thinking of an organization as tools, and the statistical thinking that as well as reduced manufacturing a bolt of cloth, both the vertical and accompanies them, greatly enhanc­ cost. horizontal weave must be equal to es the effectiveness of Quality Func­ Tracking the Voice of the ensure strength. American compa­ tion Deployment and Taguchi meth­ Customer: QFD nies traditionally have had strong ods. As Dr. Ishikawa has stated, Quality Function Deployment, or vertical structure but weak horizontal "Unless a person is trained to use QFD, is now used by many leading communication. QFD provides that these simple and elementary tools, Japanese and American companies. horizontal weave. More than just a he cannot expect to master the First used by Mitsubishi's Kobe function of the quality department, more difficult methods. In the case Shipyard beginning in 1972, QFD QFD is a potent planning system for of Japan, the fact that top manage­ assures that the "voice of the cus­ implementing business objectives. ment down to line workers can use tomer" is heard throughout all stag­ A fundamental goal of QFD is these seven tools is quite signifi­ es of product development. It should to eliminate startup problems and cant." These "old" tools maintain drive the effort of every function within a company.

Winter 1987 11 Product Sources of Variation Development Stages Environmental Product Manufacturing 1:.------,'\1 Product design LU u::J ic:5l II Process design •• LQJ Manufacturing o o Countermeasures possible • • Source: R. N. Kackar, Journal of Quality • Countermeasures impossible Technology, Vol. 17, No.4, Ocl. 1985.

Fig. 2. Produci development stages at which countermeasures against various sources of variation can be built into the product. early product revisions. Quality as­ • Determine design target quality form a set of final product control surance thus starts with the gather­ levels characteristics. Fig. 3 shows a sim­ ing of market information and re­ • Determine critical areas where en­ plified example of a product plan­ search and development. It moves gineering resources are needed to ning matrix used as the starting through quality planning, quality de­ gain a competitive advantage point, translating customer require­ sign, and production preparations, • Identify design conflicts ments to design reqUirements. Com­ and includes production, purchasing, petitive comparisons are integral to sales, and service. All business • Assign responsibilities QFD at every stage. They help to functions are tied together horizon­ • Link internal control points to the ensure that marketing strategies or tally. Responsibility for producing a needs of the external customer sales points don't become diluted or quality item is extended (deployed) • Determine critical product compo· altered in the development process. beyond manufacturing and quality nent and process parameters The design requirements (coun­ control. A mechanism is put in place • Develop instructions for operating terpart characteristics) determined to accomplish it. personnel. initially in the planning matrix are The meaning of "quality" ex­ Of course, every organization transferred to subsequent charts to pands beyond "fitness for use" or has some means of eventually in­ help define part characteristics. Part "conformance to specifications." It corporating customers' presumed characteristics, in turn, are carried includes the issues of cost and time­ requirements into a final product. In on to establish the appropriate man­ liness. Contrast it with traditional this sense, QFD does not represent ufacturing operations, and then de­ methods of development and pro­ a totally new idea. tailed production reqUirements. duction, where the executive's or However, through QFD, compa­ In simplest terms, successively engineer's voice drives the process nies do it in a very disciplined, struc­ apply the Pareto principle and post-introduction problem solv­ tured manner. Usually a series of - elaborate the details at one stage, ing is relied upon to fix whatever the charts or matrices is used to then select the most important items customer doesn't like. achieve specific product objectives for the next stage. Therefore, QFD by translating customer require­ not only tells where to concentrate engineering effort, but, just as im­ QFD is not an engineering ments into design and production parameters. QFD is not an engi­ portantly, where not to invest time system per se, but rather a neering system per se, but rather a and money. It also promotes "simul­ documentation and documentation and communication taneous engineering;" design, proc­ communication system. system. ess, and manufacturing engineers The point of departure for QFD work as a team to speed the proc­ is the voice of the customer. One of ess and resolve conflicts. In a narrower sense, QFD is an the most important tasks is to trans­ As a relatively new concept, es­ approach to engineering design late the customers' requirements, pecially in the U.S., QFD is evolving which employs a collection of tools expressed in their own words, into rapidly. In fact, the name "QFD" is to systematically: detailed technical language and tar­ not universal. (Bell Labs, for exam· get values, termed "Counterpart Characteristics." They eventually

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"""""?'~.~W'\' pie, calls it "Matrix Product Plan­ customer survey of competitors' ma­ the use of QFD by its suppliers. ning.") More importantly, companies chines further revealed that im­ Budd Company, Kelsey-Hayes and have customized QFD application. provement in sewing starts would Sheller-Globe have completed case This adaptation is desirable because provide a significant competitive ad­ studies. Non-automotive users in­ QFD's acceptance and usefulness vantage. Then QFD targeted key clude such diverse companies as are enhanced by incorporating exist­ design characteristics such as bed Omark Industries, Digital Equipment, ing terminology and engineering ini­ cross section and holding height for and Proctor & Gamble. tiatives. intensive engineering effort. Applications in the United "Potential Rewards Are Great" The new sewing machines ma­ States thus far have generally been This process seems rather com­ terially improved their customers' modest in scope and impact. Never­ plicated, but the potential rewards quality and productivity. Sales theless, success stories are emerg­ are great. Many U.S. companies are leaped tremendously despite a long ing. Several automotive suppliers re­ convinced that it is worth the extra term decline in the sewing machine port greatly improved customer effort in planning, execution, and top market. Tokyo Juki is now No. 1 in satisfaction with such products as management involvement. Japanese the world. coolant level sensors and glove companies using QFD have While many Japanese compa­ boxes. QFD helped them to identify achieved many benefits including: nies, including all Toyota suppliers, design shortcomings early in the are using QFD, the first U.S. case process. • Fewer engineering changes studies emerged only in early 1986. Tie-in to Taguchl • Shortened design cycles However, interest is snowballing. All One reason QFD is so powerful • Beller designs/performance of the Big Three domestic auto mak­ is that it ranks critical items to help • Lower start-up costs ers have begun training and applica­ determine where quality technology • Reduced warranty claims tions. Ford is strongly encouraging • Retention of engineering knowl­ edge Product Planning Matrix • Customer satisfaction • Competitive advantage. Counterpart Characteristics

The magnitude of these benefits ! Product Customer is large. Toyota and NGK, for exam­ Voice Design .2 Competi- pie, report that their design cycle of the Require- 'iii tive has been reduced by one third. ments a: Customer Gl Analysis Toyota start-up costs on one product ~ l) Gl <: line were reduced by 61 percent E .. ot: <:-"'In V over a seven-year period covering _0 =1:: PA Market Ina. Qi '0 II ; four start-ups. Aisin Warner claims Quality 0_" E (/)Q. LlLJ that both their number of engineer­ Requirements ing changes and their design cycle P=Poor have been halved. Komatsu MEC, a H C- A=Acceptable manufacturer of heavy equipment, V=Very Good used QFD to introduce eleven new • Strong products within a 2 'I.!-year develop­ Relationship ment cycle, five of them simultane­ ! . ! ously. These products obtained sub­ o Medium ! ! stantial gains in market share. Relationship ! QFD has also successfully been applied to "mature" products. For D Weak example, Tokyo Juki Kogyo Compa­ Relationship I ny used QFD to help redesign its

line of sewing machines. They I Technical ! began by taking extraordinary pains Difficulty I to collect and comprehend informa­ ! tion from the market, including de­ Characteristic tailed observations, discussions with Target machine operators and evaluations Values I I of complaint reports. One key "cus­ 5 , Technical , tomer demand" was ease of han­ 4 dling cloth at the start of a sewing Competitive 3- Benchmark 2 I operation. Technical analysis and a Good Evaluation , I

Fig. 3.

Winter 1987 13 and engineering effort should be ap­ Continuous Loss Function plied. Also, QFD often identifies conflicting design requirements. In these instances, Taguchi methods are providing some remarkable re­ Poor Poor sults. While Taguchi methods are often an integral part of QFD, they are also used extensively outside of Fair Fair the QFD framework. Less than one hundred QFD case studies have Good Good been documented in the United States, but there have been over Best 6000 Taguchi applications, and that number is growing rapidly. Dr. Genichi Taguchi, a highly Target acclaimed Japanese engineer and Value of the characteristic - the winner of four Deming Prizes, began developing these methods Fig. 4. The loss function quantifies potential savings by reducing variation around the during the 1950s. His most impor­ target value. tant contribution has been the com­ time deviates, early or late, from the weld strength) and to "smaller is bination of engineering and statisti­ published schedule. We can assign better" (such as fuel consumption, cal methods to achieve rapid no arbitrary limits to distinguish CO content of exhaust gas). prQduct and process design optimi­ zones of total satisfaction (no loss) Using the loss function, all qual­ zation. Taguchi's methods form a from total dissatisfaction. Assume ity improvements are measured in comprehensive, integrated quality our standard on the "late" side is terms of cost savings. Cost and engineering system, including a "no greater than 30 minutes." A de­ quality improvement become one number of special techniques. How­ layed passenger certainly sees no and the same. Quality projects may ever, Taguchi's approach is here black-and-white difference between be undertaken even though no out­ distilled to three areas: a delay of 29.5 minutes and 30.5 of-spec material is being produced. 1. Quality evaluation minutes, and therefore our "spec" is Conversely, you may reject an im­ 2. Cost-effective quality improve­ a useless measure of customer sat­ provement project in favor of others ment isfaction. even when some out-of-spec materi­ 3. Cost-effective quality mainte­ As a product example, consider al is being produced. This view of nance. the color density of a picture tube. It quality greatly promotes the inces­ is unreasonable to assume that cus­ sant devotion to reducing variation Quality Evaluation tomers are equally satisfied with all and continuous improvement which Taguchi defines and evaluates levels of density within a given accounts for Japan's rise as a global quality by his "loss function." Loss specification interval, only to be­ quality and cost leader. refers to costs incurred or profits come totally unsatisfied when the Cost-Effective Quality foregone relative to baseline perfor­ density reaches some discrete point. mance. The underlying principle is Improvement Suppose that two plants producing that quality loss is proportional to The "how to" of improvement the same picture tube shipped units consists of three steps applied to the deviation from a target value (or with the same average density and ideal performance level) over the life both the product design and produc­ all were within specifications. Both tion processes: of a product. Therefore, conform­ plants' customers should be equally 1. System design - a non-statistical ance to arbitrary specification limits satisfied, right? The Sony Corpora­ is an irrelevant measure of quality tion found out differently. Customer process of surveying and select­ (Fig. 4). The loss function quantifies satisfaction was higher and warranty ing appropriate design technology potential savings by reducing varia­ claims were lower for units produced and concepts to produce a proto­ tion around the target value. in its Japanese plant than those pro­ type design that possesses the Taguchi's loss function contra­ duced in its American plant. The dif­ functions required by the product plan dicts the notion that everything with· ference was deviation from target in specs is equally good and that value. Average density was the 2. Parameter design-experimental everything outside of specs is same, but dispersion in density val­ design methods to find the opti­ equally bad. A simple illustration is ues was much greater for the mal levels of the individual sys­ variation around a scheduled flight American-produced units. tem parameters which were de­ departure time. Customer dissatis­ The above examples are cases termined during the system faction (and potential loss) will grow where "nominal is best." The loss design at an increasing rate as departure function also applies to "larger is better" situations (such as tread life,

14 Target 3. Tolerance design - experimental of experiments (combinations). Tra­ though it is well-suited to operations design methods, used only after ditional techniques, checking the ef­ such as metal stamping. parameter design, to set the tol­ fects of only four factors, each at erances of the parameters, if three different settings, demand 81 necessary. According to Taguchi, combinations. A corresponding ... parameter design can "narrow tolerances should be the Taguchi experiment uses only nine improve a product's field weapon of last resort to be used combinations. This difference grows performance so that it is less only when parameter design exponentially as more factors are subject to environmental gives insufficient results." added to the analysis. Using variables and deterioration. Taguchi refers to them collec­ Taguchi methods, a small number of confirmation experiments are usually tively as "off-line quality control." Of Perspectives On Taguchi the three, U.S. companies have ap­ performed to check initial experi­ Of course, Taguchi is not with­ plied parameter design most exten­ mental conclusions. out critics. Some charge that certain sively. The premise behind parame­ Companies have applied methods are statistically incorrect or ter design is strikingly simple - that Taguchi parameter experimentation inefficient, and sometimes give the it is much easier and less costly to to the controllable factors in an ex­ wrong (not "the best") answers. The design a product insensitive to man­ isting production process without argument may represent the differ­ ufacturing variables than to control modifying the product design itself. ence between, say, a 50 percent im­ all of those variables. Similarly, pa­ Ford Body and Assembly Division provement in two months versus a rameter design can improve a prod­ improved door fits under existing 90 percent improvement in two uct's field performance so that it is production constraints in one of its years. In reality, with a complex less subject to environmental varia­ plants. They had only four factors product or process, the full conven­ bles and deterioration. The objective with which to work (such as latch tional experimental protocol is al­ is a "r.obust" design. plate location), yet they managed to most never performed and seat-of­ As an example of parameter improve on three of five targeted the-pants judgments suffice. design, Taguchi often cites the case quality characteristics, with no capi­ While the arguments over his of the Ina Tile Company in Ina tal investment or design changes. 1953. statistical procedures have merit, knew that uneven temperature distri­ ITT used Taguchi methods to Taguchi has made statistical experi­ bution in the tunnel kiln was an as­ increase the weld-splice strength in mental design usable by a wide signable cause of size variation in wire harness assemblies until it ex· range of non-statisticians, so his the fired liIes. Rather than attempt ceeded the core strength of the methods are having a great impact to control the kiln temperature, wire. Not only did they save on American manufacturing. ITT, for which would have been expensive, $300,000 per year by discontinuing example, used Taguchi methods in they performed a design experi­ a destructive pull test, ITT also re­ over 2000 cases and reported cost ment. The experiment studied the duced field failures and discarded savings of $35 million. Other cases effects of varying seven factors in­ proposals for costly alternative proc­ of six- and seven-figure cost savings volved in the liIe mixture. They esses such as ultrasonic welding. abound. A recent two-day Detroit found that changing the lime content Cost-Effective Quality conference on Taguchi methods and from one percent to five percent re­ Maintenance QFD drew a full house of 250 peo­ duced tile size variation by a factor Even when product and process ple and many more were turned of ten, obviating the need for expen­ design are completely optimized, away. sive temperature controls. tools wear, people make mistakes, More telling is Akashi Fuku­ For parameter design, Taguchi and materials vary. To maintain hara's analysis of the sources of modified the conventional statistical quality during production, Taguchi quality improvement at Toyota from methods of experimental design. has developed "on-line quality con­ 1977 to 1985. Fukuhara is vice The basic strategy is straightfor­ trol." It relies on several formulas to president of the Central Japan Qual­ ward: cost-effectively minimize losses due ity Association and the retired man­ • Identify which factors are control­ to piece-to-piece variation: scrap, ager of product assurance at Toyota lable and which are "noise" (not adjustment, inspection, and Autobody. He attributed fully 50 per­ controllable or very expensive to manufacturing-related performance cent to Taguchi's parameter design. control) variation. The basic principle is to SPC was little more than a footnote • Find the levels for controllable weigh the cost (loss) of reducing in his analysis. He believes that factors such that highest perfor­ variation around the target against many other Japanese firms would mance is achieved in spite of the the loss due to the variation itself. give a similar breakdown. And per­ noise. This form of quality control does not haps Taguchi's conceptual frame­ The power of Taguchi methods involve any charts but rather a sys­ work for quality improvement is is ability to greatly improve design tematic method of checking and ad­ even more important than his statis­ or production processes in a short justing. On-line quality control is tical techniques. time, using a relatively small number poorly understood in the United States and not practiced, even

Winter 1987 15 Relationships Among QFD, Taguchi Methods, and JITJTQC Operating Principles 1------, Customer QFD (Voice of the customer) II • Market quality Product 1------, requirements planning I Taguchi methods matrix· I I (Loss function con- E • Product (Market quality re- I I III conceptlng quirements) to cept/reduction of ! ,------, (design requirements) I I variation) tii I JIT/TQC principles I I (elimination of waste) Product I .. I design C I Off·line QC GI • Design .SPC I I E engineering (Design requirements) I a. • Fallsafing I 10 I A.. System design o • Quality at the I (part characteristics) i source/immedi~ I B. Parameter ate feedback I Process design • Process planning & enaineering • Standardization I (Part characteristics) c. ToleranCtl u _---'~.I ~ • Setup reduction I..I... to (manufacturing design "Cl • Employee in· II operations) volvement • Manufacturing l I Production • Educationltrainlng I planning On-line QC; • Assembly • Mfg. cells/group I I reduction of piece­ (Manufacturing oper- to-piece variation • Saleslservice technology I I ations) 10 (detailed pro- I • Preventive ....J-__~ duction procedures) I I L mai~e.:'nce -l L -l L -l Customer .. Product planning matrix is shown in Fig. 3.

F/g. 5. The vOice of the customer IJegms with tne product planning matrix and continues through succeeding sets of matrices (product design, process planning, and production pianning). The total number ofmatrices in a complete product development stream can be very large.

Conclusion Recommended Reading QFD is an appropriate mecha­ Barker, Thomas B. nism to integrate the principles and "Quality Engineering by Design: Taguchi's Philosophy," Quality Prog­ methods of world-class manufactur· ing_ As shown in Fig. 5, the voice of ress, December, 1986, pp. 32-42. the customer selectively guides the Jessup, Peter T application of efforts to eliminate "The Value of Continuing Improvement," Proceedings of the International waste and foster continuous im­ Communications Conference, "ICC 15", Institute of Eiectrical and Electronics provement using Taguchi methods Engineers, June, 1985. as well as JITfTQC operating princi­ ples. Kackar, Raghu N. "Off-Line Quality Control, Parameter, Design and the Taguchi Method, Journal of Quality Technology, Vol. 17, No.4, October, 1985, pp. 176-188. Author: Ronald M. Fortuna is a manager in Kogure, Masao and Akao, Yoji Ernst & Whinney's Manufacturing Ex­ "Quality Function Deployment and CWQC in Japan," Quality Progress, cellence practice. He has held a num­ ber of line and staff positions in manu· October, 1983, pp. 25-29. facturing and quality control. His recent activities include education and support Ryan, Nancy E. for TOC efforts of many companies in­ "Tapping into Taguchi," Manufacturing Engineering, May 1987. clude SPC, training, and implementa­ tion assistance. Fortuna is a Certified Sullivan, Lawrence P. Quality Engineer. He earned a B.S. de· "Quality Function Deployment," Quality Progress, June, 1986, pp. 39-50. gree and an M.B.A. degree in production/operations management Sullivan, Lawrence P. from the University of Michigan. "The Power of Taguchi Methods," Target, Summer, 1987. Taguchi, Genichi Introduction to Quality Engineering, Asian Productivity Organization, Tokyo, 1986. 0

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