SPC Made Easier, Simpler, More Statistically Powerful Keki R. Bhote n the search for world class quali­ when they realized that SPC in pro­ come fashionable. They are good Ity, there must be synergy between duction was too little and too late. for employee morale, and they are management, customers, suppliers, Paradoxically, the U.S. rediscovered good for small-increment problem and employees. Organization, sys­ SPC at the same time that the Japa­ solving. However, their hunches tems, and training of the right kind nese were discarding it. (SPC was often lead to blind alleys, consuming are essential catalysts. A blueprint widely used in the U.S. during World needless cost and time. Frequency of improvement in these general War II, but then the baby was distributions and process capability areas is beyond the scope of this thrown out with the bathwater, in a studies indicate the existence of var­ article. Instead, it concentrates on revolt against the mysteries of the iation, but like control charts, pro­ easy, simple, cost effective, and sta­ world of statistics.) vide few clues as to the origin of the tistically powerful tools that can im­ problem. Engineering judgment and "If Japan Can, Why Can't We" prove product quality, not by an varying one cause at a time can What re-ushered the SPC age inconsequential 10 percent, 50 sometimes help, but the longevity of in America was the airing of the percent, or even 100 percent, but by chronic problems bears witness to NBC White Paper-"If Japan Can, factors of 10:1 and 100:1 in a short their futility. Lastly, there is some­ Why Can't We." It gave the Ameri­ period of time. If quality is the cen­ times a child-like faith that comput­ can public at-large its first glimpse of terpiece for a company's resur­ ers can solve quality problems, but the reasons behind Japan's suc­ gence, these statistical tools are the used with ineffective methods they cess: Quality, in general, and SPC piece de resistance, within quality. only process meaningless data fast­ in particular. Deming was rescued er! The Traditional, Ineffective Quality from the U.S. quality wilderness and SPC Tools for the Japsnese Line Tools elevated to a prophet within his own Workers It is common knowledge that country. Major companies scurried The Japanese, as indicated ear­ Japan drew even with the U.S. in to jump on the SPC bandwagon. lier, have abandoned SPC tools for quality progress by the mid 1960s Unfortunately, SPC has become more powerful techniques, with two and has gone on to command an synonymous with control charts. exceptions. First, they still trot out ever-widening lead. What is less Control charts are complex, costly, control charts as show-and-tell for well-known are the quality tools and almost useless in their ability to visiting American firemen, so that used by the two countries. The U.S. their advanced methods would not persevered in the traditional tools of ... Control charts are receive much scrutiny! Secondly, inspection and sorting, detection complex, costly, and almost they have trained their entire direct and correction, fire fighting, exhorta­ labor work force in elementary SPC tion, and the crutch of sampling useless in their ability to solve tools, so that they can tackle small­ plans, at least until 1980. These quality problems. step quality problems through quali­ tools consume costs but add little ty circles, Kaizen (improvement) value. solve quality problems. The most groups, and employee suggestions.' Conventional SPC Tools- Too charitable rationale for their exis­ These elementary tools consist Little, Too Late tence is as a maintenance tool, to of: The Japanese, on the other be used only after a process is • P.D.C.A. (The Plan- Do- Check­ hand, abandoned these ineffective brought under control with more Action Circle) allegedly taught by tools and adopted statistical process powerful diagnostic techniques. Deming, but recently claimed as a control (SPC) in the 1950s, under Problem Solving-U.S. Style. Japanese innovation the coaching of Dr. W. Edwards Along with control charts, the • Data collection and analysis Deming. They rode the crest of the U.S. began to use other less-than­ SPC wave until the mid 1970s, effective problem-solving tools. Brainstorming, quality circles, and Kepner-Tragoe methods have be- 12 Target ..~ ~.........•............•...•.•.•.......•~~.~~~~~-"'""""""'."""'"'"~".""'."'."".""'.","""""""" Design of Experiments Characteristic Classical Taguchi Shainin Technique Fractional factorials, Orthogonal arrays Multi-vari, vari~ble search, full EVOP, etc. factorials Effectiveness Moderate Low to moderate Extremely powerful (20 percent to 200 percent (20 percent to 100 percent (100 percent to 500 percent improvement) improvement) improvement) Retrogression possible Retrogression likely No retrogression Cost High High Low Many experiments Many Few experiments experiments Complexity Moderate High Low Full ANOVA required Inner and outer array multipli­ Experiments can be under­ cation, SIN, Anova stood by line operators Statistical Validity Low Poor High Higher order interaction No randomization Every variable tested with all effects confounded with main Even second order interaction levels of every other variable effects effects confounded with main Excellent separation and To a lesser extent, even effects qualification of main interac­ second order interaction SIN concept good tion effects effects confounded Applicability Requires hardware Primary use as a substitute for Requires hardware Monte Carlo analysis Main use in production Can be used as early as prototype and engineering run stage Ease of Moderate Difficult Easy Implementation Engineering and statistical Engineers not likely to use Even line workers can knowledge required technique conduct experiments Fig. 1. Three approaches to the design of experiments are compared. • Check-sheets, histograms, and These and allied techniques are jective is to disoover key variables in frequency distributions to measure often grouped together and called product and process design, drasti­ variation the "seven tools of QC" that every cally reduce the variations they • Pareto charts to separate the vital Japanese worker leams and uses. cause, and opan up the tolerancas few causes of defects from the The aggregate benefit is very pow­ on the lesser variables to reduce trivial many erful, but unfortunately it is these oosts. These experiments are oon­ ducted before the start of produc­ • Cause-and-effect diagrams to list elementary SPC tools that U.S. pro­ tion. Hundreds of Japanese oompa­ all possible causes of a problem fessionals are embracing in their un­ nies oonduct thousands of these and group them by families equal drive to catch up with Japan. Meanwhile, Japanese professionals designed experiments each year to • CEDAC (Cause-and-Effect Dia­ - in engineering, manufacturing, make designs "more robust." The grams with the Addition of Cards) and qual~y-have graduated to discipline is a variant of the classical - a refinement of cause and ef­ more sophisticated and powerful design of experiments fathered by fect diagrams to keep them cur­ tools. Sir Ronald Fisher of Britain 70 years rent and more meaningful to the ago. The principal Japanese expo­ Japan's Secret Weapon worker nent is Dr. Genichi Taguchi, who The central thrust and secret • Control charts. adapted the classical methods into a weapon of Japanese quality is de­ sign of expariments (DOE). The ob- t> Fall 1987 13 system called the "Orthogonal portantly, the only way to reduce CPK = (1 - K) Cp Array." and eventually eliminate all scrap, (Where K is an absolute value, with­ In the U.S., by contrast, DOE rework, analyzing, etc., is to get a out regard to its sign) was practically unheard of, except product parameter at, or very close (Design Center, D, need not be at for a small band of academics and to, its design center. This is the only the mid-point of the specification missionary statisticians. A belated way to get to zero defects and 100 width.) movement, started in the early percent yields. Once this is done, When the process average, 1980s, imported Taguchi's methods production becomes a "breeze" x, and the design center, D, coincide, wholesale. without the necessity of inspections p that add no value! K is reduced to zero, so that C and Classical vs. Taguchl vs. Shainin CPK are equal. Fig. 3 shows two ex­ DOE Measures of Variation: Cp snd CPK amples of non-centered processes. Fig. 1 lists three approaches to Before variation can be re­ Process A has a narrow spread, the design of experiments - the duced, it must be measured. Two with a respectable Cp of 2.5. But classical, Taguchi, and those taught yardsticks-Cp and CPK-have be­ because it is skewed toward one by Dorian Shainin, less famous than come standard terminologies in re­ end of the specification Iim~s, ~s CPK Deming or Juran, but a giant of an cent years. Process capability, Cp, is is reduced to 1.0. By contrl;lSl, Proc­ authority and a consummate prob­ defined as specification width divid­ ess B has a wider spread and a lem solver. The classical tools start ed by process width. It is a measure poorer Cp of 1.67. Yet, it is more with fraction factorials and end with of spread. Fig. 2 depicts six frequen­ toward the design center and, there­ evolutionary optimization (EVOP). cy distributions comparing the speci­ fore, has a higher CPK of 1.33. The Taguchi's methods use orthogonal fication width (40 - 20 = 20) to the objective, again, is to aim for high arrays (inner and outer), analysis of process width. Process A in Fig. 2 Cp.'s of 5, 10, 15, and 20 without variance, and signal-to-noise. The has a Cp of 0.8. This is a process adding recurring costs. Shainin experiments start with multi­ out of control, with reject tails at Measuring Variation - The Easy vari charts, followed by variables both ends.