36855351 tqm statistical tools

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TQM Tools

Here follows a brief description of the basic set of Total Quality Management tools. They

are:

y Pareto Principle y Scatter Plots

y Control Charts

y Flow Charts

y Cause and Effect , Fishbone, Ishikawa Diagram

y Histogram or Bar Graph

y Check Lists

y Check Sheets

Pareto Principle

The Pareto principle suggests that most effects come from relatively few causes. In

quantitative terms: 80% of the problems come from 20% of the causes (machines, raw

materials, operators etc.); 80% of the wealth is owned by 20% of the people etc. Therefore

effort aimed at the right 20% can solve 80% of the problems. Double (back to back)

Pareto charts can be used to compare 'before and after' situations. General use, to decide

where to apply initial effort for maximum effect.

Return to TQM Tools index

Scatter Plots



A scatter plot is effectively a line graph with no line - i.e. the point intersections between

the two data sets are plotted but no attempt is made to physically draw a line. The Y axis

is conventionally used for the characteristic whose behaviour we would like to predict.

Use, to define the area of relationship between two variables.

Warning: There may appear to be a relationship on the plot when in reality there is none,

or both variables actually relate independently to a third variable.


Control Charts



Control charts are a method of Statistical Process Control, SPC. (Control system for production processes). They enable the control of distribution of variation rather than

attempting to control each individual variation. Upper and lower control and tolerance

limits are calculated for a process and sampled measures are regularly plotted about a

central line between the two sets of limits. The plotted line corresponds to the

stability/trend of the process. Action can be taken based on trend rather than on individual

variation. This prevents over-correction/compensation for random variation, which would

lead to many rejects.


Flow Charts



Pictures, symbols or text coupled with lines, arrows on lines show direction of flow.

Enables modelling of processes; problems/opportunities and decision points etc. Develops

a common understanding of a process by those involved. No particular standardisation of

symbology, so communication to a different audience may require considerable time and

explanation.


Cause and Eff ect , Fishbone, Ishikawa Diagram

The cause-and-effect diagram is a method for analysing process dispersion. The diagram's purpose is to relate causes and effects. Three basic types: Dispersion analysis, Processclassification and cause enumeration. Effect = problem to be resolved, opportunity to be

grasped, result to be achieved. Excellent for capturing team brainstorming output and for filling in from the 'wide picture'. Helps organise and relate factors, providing a sequential

view. Deals with time direction but not quantity. Can become very complex. Can bedifficult to identify or demonstrate interrelationships.




Histogram or Bar Graph

A Histogram is a graphic summary of variation in a set of data. It enables us to see

patterns that are difficult to see in a simple table of numbers. Can be analysed to drawconclusions about the data set.

A histogram is a graph in which the continuous variable is clustered into categories and

the value of each cluster is plotted to give a series of bars as above. The above examplereveals the skewed distribution of a set of product measurements that remain nevertheless

within specified limits. Without using some form of graphic this kind of problem can bedifficult to analyse, recognise or identify.


Check Sheets

A Check Sheet is a data recording form that has been designed to readily interpret results

from the form itself. It needs to be designed for the specific data it is to gather. Used for

the collection of quantitative or qualitative repetitive data. Adaptable to different data

gathering situations. Minimal interpretation of results required. Easy and quick to use. No

control for various forms of bias - exclusion, interaction, perception, operational, non-

response, estimation.


Check ListsA Checklist contains items that are important or relevant to a specific issue or situation.Checklists are used under operational conditions to ensure that all important steps or

actions have been taken. Their primary purpose is for guiding operations, not for

collecting data. Generally used to check that all aspects of a situation have been taken into

account before action or decision making. Simple, effective.



TOOLS OF TOTAL QUALITY MANAGEMENTSujata Mitra

Implementing TQM in the hospital

posed certain challenges. It meant convincing

people that Quality was not extra work, it was

an integral part of work and the way to work.People had to be motivated to achieve µgobeyond-

service¶ Quality. The approach was toencourage people to be creative and find

solutions to their own problems.Which brings us to the next stumbling

block. Would all the individual efforts combineto give a significant thrust to the Quality

movement or would they remain isolated

islands of improvement? There was need to

align and prioritise the individual goals with

the organisational goals, conversely, the

organisational goals had to cascade down toindividual goals. S pecialised training in IVF

technique could be an individual need, but if

the organisational goal was to reduce average

hospital stay, laparoscopic training would be

given priority.

Prioritisation and alignment was done

through the Balanced Scorecard concept.

1. BALACED SCORECARD

This is a set of measurements and

targets that are used to prioritise and quantify

goals (Ref.Chow,et.al,1998). A hospital may

have identified cost competitiveness as its goal.How is this communicated to all the working

units? In the scorecard, an overall target for

cost saving is set which is then broken into

specific targets for different areas like power

consumption, rightsizing, revenue generationetc. Each department sets its own target in

these specific areas and plans to achieve itthrough improvement projects, value

engineering etc. Ultimately, two and two maynot just be four, but even five due to this

synergistic working.

The scorecard is like a progress report.It is a ready reckoner for planning as well asassessing progress vis.a.vis the targets (Ref.

Fig. 2, µAn introduction to TBEM model¶).II. QUALITY IMPROVEMENT

PROJECT

A quality improvement project is taken

up preferably by a cross-functional team to

tackle chronic, recurrent problems which



impact upon customer satisfaction (Ref. TotalQuality Handbook, Tata Steel). Most of these

problems are either not obvious or have beenswept under the carpet. The job of the team

lies in correctly identifying the problem,

analysing it and coming up with a solution that is

acceptable to all. If it is a problem that cutsacross different work areas, a cross functional

team ensures that benefits are shared by all.

A number of patient complaints related

to long waiting time in the out-patient

department. One of the hospital goals

therefore, was to reduce average waiting time in

OPD to less than 30 minutes. The Cardiology

department took up the challenge and included

this as their departmental goal. A QIP team

was formed. After data collection and brainstorming for all possible causes, the main

reason identified for the increased waiting timewas too many patients arriving at the same

time. The analogy of congestive cardiac failurewas drawn- increase in preload (number of

patients) leading to pump failure (doctorsunable to cope with the sudden rush). The

solution was again drawn from the analogyreduce

the preload! An appointment system

was put in place, with segregated time slots

for different patient categories. The solution

appealed to both, doctors and patients, and the

pump efficiency increased to 90% patients seen

within 30 minutes! (Ref.Bharat et.al, 1999). This

solution has been emulated by other clinical

departments too so that today the average

waiting time in OPDs is less than 15 minutes

and more than 95% patients are dealt with in

less than half hour of their arrival.

III. VALUE ENGINEERING PROJECT

Cost effectiveness is the need of the hour

for any organisation. A value engineering

project helps to achieve this6

strategic goal. It aims at µValue added service¶.

It implies reducing wastage, not spending.Teams use creativity and innovation to come

up with alternatives that may be cheaper,eliminate wastage or add value to existing

services (Ref. Jaganathan, 1998).A classic example is the value

engineering done in the Nursery to reducewastage of nappies. Irrespective of baby size



or need, bulky, full size nappies were provided toall babies, which, besides wastage, were quite

uncomfortable for the little customers. Nursesand doctors brainstormed to find out what the

ideal nappy size should be. The existing nappies

were reduced to a quarter, wastage was

eliminated and the babies smiled!IV. QUALITY CIR CLE

A Quality Circle is a small group of

employees from the same work area whovoluntarily meet regularly to identify, analyse

and resolve work related problems (Ref.Hutchins, µIn pursuit of Quality¶ 1990) This not

only improves the performance of anyorganisation, it also motivates and enriches the

work life of employees. The philosophy behindQuality Circles is building people.

A Quality Circle tackles small, work

related problems through teamwork.Statistical tools are used to analyse problems,

members arrive at a solution by consensus and

implement it themselves. This leads to

empowerment at the grass root level.

TMH has 57 active Quality Circles in

diverse work areas like the Hospital laundry

and kitchen, Steward section, Nursing section

etc.

Unlike the QIP and VE teams, a Quality

Circle is permanent.

The quality circle of the hospital kitchenwas worried about the complaints regarding

the quality of food. The chappatis in particular,were singled out for criticism. The fluffy, soft

chappatis leaving the kitchen became cold andhard by the time they reached the patients. The

defect lay in the distribution system. A simple,7

but innovative solution was rearranging the

food on the trolleys. The chappatis were now

wrapped in a cloth and placed directly on top

of the steaming µdal¶container.

Patient satisfaction on hospital servicesis greatly influenced by mundane matters like

food. If professional expertise is not backedwith concern in areas like hospitality, patient

dissatisfaction is bound to linger. Withsuccessful quality circles taking care of such

µpinpricks¶, the hospital administration can resteasy.

V. INTEGRATION OF



IMPROVEMENT INITIATIVES

How do these improvement initiatives

contribute to improving the overall

performance of the hospital? As described, all

targets cascade from the scorecard. The

integration of improvement projects with the

scorecard is shown in Fig.lREFERENCES

1. Bharat.V., Mohanty.B., Das.N.K,

µWaiting time reduction in out patient

services -an analogy to heart failure

therapy.¶ Indian Journal of Occupational

and Environmental Medicine; 1999; 3,181-184

2. Chow.W.Chee, µThe balanced scorecard: A potent tool for energizing and focusing

healthcare organisation management¶- Journal of HealthcareManagement 43:3

May/June 19983. Hutchins David µIn pursuit of Quality¶

Wheeler Publishing, 19924. Jaganathan.G. µGetting more at less cost-

The value engineering way.¶ Tata McGraw

Hill, New Delhi,19925. Total Quality Handbook, Tata Steel

Batanero, C. (Ed.), Training Researchers in the Use of Statistics, 53-63.

«2001 International Association for Statistical Education and International Statistical Institute.Printed in Granada, Spain

CHIHIRO HIROTSUSTATISTICAL TRAINING OF RESEARCHERS IN TOTAL QUALITYMANAGEMENT: THE JAPANESE EXPERIENCE A training system for statistical methods in Total Quality Con trol or Total Quality Management is discussed and we suggest what and how to teach. It is stated that wehave no department of statistics in the universities in Japan and stressed that applied statistics is most efficiently taught to those who have their own problems and motivations to apply these statistical methods. It is then essential for a company tohavetheir own training systems for the TQM researchers although some extra company

training courses may also be efficiently utilised. As an example we introduce in somedetail the seminars provided by JUSE as well as in -company training systems of ToyotaMotor Corporation and Takenaka Corporation.

1. INTRODUCTIONIn this paper we consider a training system for statistical methods in TQC (TotalQuality Control) or TQM (Total Quality Management). Two important aspects of thesystem are what and how to teach. The success of quality control in Japan is due tothe



company-wide activities, which involve all the staff and departments in a companyanddo not just depend on a few experts. It is also due to the natural tendency of theJapanese to be very diligent, generally clever and willing to devote themselves to thecompany.Each company has a statistics section as a part of the QM promotion section. Ideally

a company should have a TQM promotion team involving several advisors andtrainerswho are expert in the area and can teach these statistical methods. However, someelementary courses may be more efficiently taught in Japan by an external institutionsuch as JSA (Japanese Standards Association) or JUSE (Japanese Union of Scientistsand Engineers). Such institutions are particularly useful in Japan since there is nodepartment of statistics in the universities and statistical methods are very poorlytaught.Now I describe five courses to learn the statistical methods that are most useful inpractice:1. Elementary statistics: Basic idea of variations in data, statistical estimation and

tests, concept of TQM, basic tools such as QC seven tools and control charts;2. Design of Experiments: One- and two-way layouts, split plot design, hierarchical

design, orthogonal array, analysis of variance (ANOVA), reliability analysis;3. Multivariate Analysis: Regression analysis, discriminant analysis, principal

component analysis, correspondence analysis, cluster analysis, contingency tables;4. Advanced: Beyond ANOVA techniques, graphical modelling, GLM, GAM, Multiple

correspondence analysis, Taguchi method;5. Applications: Problem solving by integrated use of various statistical methods.54 Training in Total Quality Management

The first three courses might be taught by some external institution, but the last twoshould be taught within the company and should be based on the researcher¶s ownproblems. It is then desirable to have convenient tailor-made software for statisticalanalysis and the database of the company¶s past achievements. It should bestressed herethat the CWQC (Company-Wide Quality Control) in Japan has been successfullydeveloped by all the people within a company, by applying statistical methods to hisor her own problem even though the methods used might be very elementary. It shouldalso be noted that a recent trend is to apply statistical approaches not only to themanufacturing processes but also to the planning, marketing and managementprocessesof the company. It is also essential to have the hierarchical education system in acompany for maintaining its statistical activities. One of the most successful

examplesin Japan is the Toyota System.Finally an annual company-wide conference is very useful to give people in thecompany an opportunity to present their statistical activities to the top managementof the company and to promote their statistical activities. A presidential award might begiven to the best achievement.2. GENERAL STATISTICAL BACKGROUND IN JAPANWe will begin by describing the general background of statistics education in Japan.



One of the most prominent characteristics is that there is no department of statisticsatJapanese universities and that statisticians are scattered around various facultiesformingvery small research teams.There was a very hot discussion on this subject a long time ago, when it was

decidedto distribute the statistics offices (called koza in Japan) over the various facultiesrequiring the study of statistics within their own field, instead of having aconcentratedstatistical department. A koza has been composed of one professor, one associateprofessor and two research associates.To give an example, at the University of Tokyo about 15 professors and associateprofessors of statistics are working in the Faculties of Economics, Engineering,Medicine, Agriculture, Education, Mathematics, and Culture. In my experience as aProfessor of the Department of Mathematical Engineering at the University of Tokyo,Itook charge of a laboratory composed of one associate professor, one research

associateand about ten doctoral and master students including a few from companies. Thereisonly one statistics laboratory among more than two hundred laboratories in theFacultyof Engineering at the University of Tokyo. It may be surprising that we have only oneprofessor and one associate professor among approximately 400 faculty members inthevery big Faculty of Engineering. We have, however, several additional statisticslaboratories in the Faculties of Economics, Medicine, Science, Agriculture, Educationand Culture and we organise an inter-faculty statistics meeting once a week andcollaborate to educate graduate students . In this sense the University of Tokyo israther favoured and I am afraid that the case will not be the same for other manyuniversities.Professional statisticians are usually brought up in the statistics laboratoriesscattered in various faculties in the universities as in the example of the University of Tokyo. The number and the range of lectures are usually not enough and studentsreadbooks themselves or in small groups, attend seminars and discuss their notes withtheir supervisors. There is no particular external consulting service for researchers in theuniversities. Of course we give advice on their request, though this is not often

neededsince, at least in the Faculty of Engineering, researchers are usually capable enoughtoChihiro Hirotsu 55

solve their statistical problems by themselves with the aid of some statisticalpackage.Therefore, we think it is important to have a weekly inter -faculty statistics seminar for graduate students. We have many opportunities to present our respectiveproblems



and ideas to our colleagues and obtain suggestions from them, and sometimes thisnaturally leads to collaborative work. Those opportunities include seminars andsymposiums.Most undergraduate students, however, take only an elementary statistics courseduring their studies except those students who belong to particular departmentswhere

there is statistics staff. They only have a poor concept of variations in data and anelementary knowledge of statistical tests and estimation. The general backgroundsof the researchers who perform the Total Quality Management in the company in Japanwill be mechanical, civil and electronical engineering, chemistry, architecture and soon.Even when I give advice to graduate students from other departments on their requeststhis is far from sufficient. It is thus essential to have the statistical training coursesoutside universities for researchers in companies who did not receive any proper statistics courses in universities.However, this is not a major defect in Japan since applied statistics can be most

efficiently taught when students have their own problems and motivations. In myexperience, for example, it is much more difficult to teach the idea of multiplecomparisons procedure to students in a classroom than to explain those ideas toresearchers in pharmaceutical companies who are dealing with various types of multiplicity problems in their ordinary research work, such as multiple endpoints,subgroup analyses and interim analyses.It is therefore possible for a researcher to learn statistics methods after he or she hasbeen involved in some department of a company and has realised the problems tobesolved there. We also note that the Deming Prize Application has been useful inJapanto motivate people in companies to learn statistics (see the special issue: TheDemingPrize edited by Okuno, 1990-1991).F ig.1 The F our Phases of R & D ActivitiesPlanning and Exploratory PhaseScientific and Explanatory PhasePragmatic and Confirmatory Phase After-market Research PhaseFeedbackOne thing I should stress here is that a researcher in a company should not be anindividual data analyst, but should relate his or her research to preceding andsucceeding

works. Any research and development (R&D) activity has four steps of exploration,explanation, confirmation and after-market research, and thus the informationobtainedby the after-market research should give feedback promptly to the first step of planning,56 Training in Total Quality Management

as it is shown in Figure1.In each phase the type of data might be different and even with the same data theapproach to the data and the decision based on the data might be different (Hirotsu,



1992). An example of this could be the difference between Phase II and Phase III of clinical trials in the stream of new drug development, which are sometimes referredtoas explanatory and pragmatic phases. To perform his or her role appropriately, it istherefore essential for a researcher to be aware of the stage he or she is in thestream of

R & D. This implies the necessity of an in-company training course at least in thefinalstage of education of applied statistics, and also suggests a need for a generalmanager to supervise the whole process of R & D.Now under the circumstances of Japan and the characteristics of applied statistics,the need of some extensive training system for people to perform TQM in companiesisobvious.3. TQM EDUCATION COURSES HELD OUTSIDE COMPANIESIn Japan we have many TQM education courses outside companies. Typical andextensive examples are the courses provided by JUSE and JSA (see Ishikawa, 1969

andMizuno & Kume, 1978). There have been, however, several changes since thesepapersand the current status of JUSE is described in some detail below. A variety of systems of education courses exist, such as post-oriented,divisionoriented,theme-oriented, methodology-oriented courses, statistical software courses anda correspondence course. There are also various levels from elementary toadvanced,which include also rather philosophical seminars to introduce the concept of TQM aswell as more technical statistical seminars. Since it is important to maintain thetrainingsystem successfully in a company, top management of the company should beaware of the relevance of applying statistics fully in the R & D activities. It should also benotedthat there are courses provided not only for the manufacturing processes but also for theplanning, marketing and management processes.3.1. POST ORIENTED COURSES1. Top Management Course (intensive, 9 hrs.×4 days): Introducing the managingdirector to management and TQM for the promotion of company -wide qualitymanagement activities.

2. Executive Management Course (intensive, 9 hrs.×4 days): Introducing the generalmanager to planning and implementing TQM.3. Senior Management Course (6 hrs.×3 days): Introductory course for senior

managers to the basic principles of TQM and TQC.4. Middle Management Course (6 hrs.×9 days): Practical course for middlemanagersto promote TQM in their respective departments.5. Chief Basic Course (6 hrs.×6 days): Role of chief staff in the ordinary qualitycontrol activities.



Chihiro Hirotsu 57

3.2. DIVISION ORIENTED COURSES1. TQM Instructor courses (6 hrs.×6 days): Methods of introduction and promotion of

TQM for TQM instructors with basic knowledge of TQM and TQC.2. Procurement Department Course (6 hrs.×4 days): Purchasing and logistics service

control for value engineering and cost reduction.

3. Elementary Course for Sales Department (6 hrs.×4 days): Concept of TQM andQA(Quality Assurance) in sales department.4. Advanced Course for Sales Department (6 hrs.×8 days): Roles of salesdepartmentfor TQM and the current method of QA for customer satisfaction.5. QC Seminar for Good Manufacturing Practice (6 hrs.×3 days): Necessaryknowledge of GMP (Good Manufacturing Practice) to promote TQM and QA inmanufacturing and selling foods and drugs.3.3. THEME ORIENTED COURSES1. Policy and Planning Seminar (6 hrs.×3 days): Method and organisation for determining the management, quality and quality control policies of the company

and for transmitting them throughout all the company sectors.2. Introductory Course for TQM (6 hrs.×3 days): Basic concept of TQM, quality andcontrol; Method of problem solving and approaching a project.3. Cost Down Seminar (6 hrs.×6 days): Basic concept, promotion and method of costdown in manufacturing planning and purchase departments.4. QC Story Seminar for Achieving a Management Project : An approach andknowhowfor innovating the business based on the company top management policy.5. Introductory Course for Product Liability (6 hrs. ×3 days): Current status of the law

and system for product liability; Experiences and measures to solve t he productliability problems.6. Advanced Course for Product Safety: A. Product Safety Technology Course (6 hrs.×2 days): Guidelines of productliability for engineers in planning, design, research and development, qualityassurance and quality control.B. Product Safety Co-ordinator Course (6 hrs.×2 days): Roles of the product safetyco-ordinator in product safety; Designing the product safety review system andthe document safety system.7. R & D Management Seminar: Management of research and development; Methodof new product development, market research and new product planning.58 Training in Total Quality Management

3.4. METHODOLOGY ORIENTED COURSES (ELEMENTARY)1. QC Seminar Basic Course (6 hrs.×30 days): Seminar of quality control concepts

andtheory and application of statistics for engineers and staff with at least 3 yearsbusiness experience; Lectures, practice with personal computer and QC games for basics statistics methods, statistical test and estimation, design of experiments,regression analysis, reliability engineering, sensory test, feeling evaluation and soon.2. QC Seminar Elementary Course (6 hrs.×8 days): Basic concept of quality controland elementary statistics methods including QC seven tools, collecting andsummarising data, test and estimation, analysis of variance and correlation and



regression analyses.3. QC New Seven tools (6 hrs.×3 days): Affinity chart method, relation chart method,

system chart method, arrow diagram method, process decision program chart(PDPC), matrix chart and matrix data analysis.4. Seminar for Computer Application for Problem Solving (6 hrs.×2 days): Problemsolving, decision making and information system.

5. Quality F unction Deployment (QF D) Seminar 5.1. QF D Practice Course (6 hrs.×2 days): Practice of QFD application, makingtwo-way tables and problem solving.5.2. QF D Introductory Course (6 hrs.×4 days): Outline and utility of QFD.6. Strategy Planning Seminar for Policy Management (6 hrs.×2 days): Framework of planning strategy, environmental analysis, product analysis, market analysis,allocating resources, analysis of strategy factors; case studies.7. Product Planning Seven Tools7.1. Introductory Course (6 hrs.×4 days): Seven tools for producing hit product;Group interview, questionnaires, positioning analysis, imaginary method, jointanalysis, product planning based on marketing; case studies.7.2. Quick Course (6 hrs.×1 days): Outline of seven tools for product planning.

3.5. METHODOLOGY ORIENTED COURSE (ADVANCED)1. Design of Experiment Seminar (1) (7 hrs.×8 days): Role experimental design,

meanand variance, test and estimation, 1-way layout, 2-way layout, split plot design,orthogonal array, theory of ANOVA, correlation analysis, simple regressionanalysis.2. Design of Experiment Seminar (2) (7 hrs.×12 days, 4 days per a month): Multi-waylayout, advanced orthogonal array, non orthogonal experiment, sequentialexperiment, mixed experiment, random effects model, optimisation of multiple -endvariables, Taguchi method, multiple regression analysis, analysis of proportions.3. Multivariate Analysis (1) (7.5 hrs.×4 days): Introduction to multivariate analysis,principal component analysis, variable selection in regression analysis, logisticChihiro Hirotsu 59

regression analysis.4. Multivariate Analysis (2) (7.5 hrs.×4 days): Latent structure analysis of categoricaldata, graphical modelling, canonical correlation analysis, covariance structureanalysis integrating regression analysis and factor analysis, data mining.5. Statistical Methods for Clinical Trials Seminar (1) (6 hrs.×7 days): Introduction toclinical trials, planning, designing, elementary statistical methods includingnonparametricmethod and cross-over design.6. Statistical Method for Clinical Trials Seminar (2) (6 hrs.×24 days, 2 days per month): Introduction to statistical inference, regression analysis, ANOVA, analysis

of categorical data, analysis of survival data, dose-response analysis, sample sizedetermination, meta-analysis, statistical guideline fo r regulation.7. Data Management in Clinical Trials Seminar (camping system, 6 hrs.×5 days):Outline of data management in clinical trial.3.6. STATISTICAL ANALYSIS SOFTWARE SEMINARS BASED ONJUSE-QCAS OR JUSE-MA1. QC Practice Seminar (6 hrs.×3 days): Process analysis, problem solving, QCseventools, and regression analysis.



2. Design of Experiment Seminar (6 hrs.×3 days): Factorial experiments, orthogonalarray, QC game.3. Multivariate Analysis Seminar (6 hrs.×3 days): Principal component analysis,multiple regression analysis, and correspondence analysis.4. Reliability Analysis Seminar (6 hrs.×2 days): Analysis of reliability data and fielddata.

5. Seminar for Questionnaire Planning and Its Analysis by Personal Computer (6hrs.×2 days): Application of multivariate analysis to the analysis of questionnaires.3.7. CORRESPONDENCE COURSE (6 MONTHS)This course is based on two textbooks, one for methods and the other for practice of quality control.Similarly the Japanese Standards Association (JSA) provides some standardcourses,in particular, ISO 9000 and ISO 14000 seminars.4. IN-COMPANY TQM EDUCATION AND TRAINING Although these external seminars provide a very good opportunity for TQMeducation and training the internal education of people in a comp any is even moreimportant for practising these methods and techniques in their ordinary activities.

Most companies, if not all, arrange education and training courses in TQM for their 60 Training in Total Quality Management

employees. Ideally for in-company education a company should be equipped with:1. A hierarchical education system;2. Tutors with various achievement levels;3. Taylor-made software for statistical analysis;4. Database of company¶s past projects and case studies;5. Annual company-wide conference for statistical activities.In this section we describe two characteristic cases of in -company education system.4.1. THE CASE OF TAKENAKA CORPORATIONThe Takenaka Corporation was the winner of the first Deming Prize in theconstruction sector and should be regarded as the leader of the sector. Its educationschedule has been introduced by Jido (1990 -91), from which we reproduce his Table3.2(Table 1 here).We can see from Table 1 that the Takenaka Corporation is giving in -companyseminars by in-company instructors and extra professionals for its employees tolearnthe TQC (TQM) concepts and statistical methods as well as using extra seminarsprovided by JUSE and JSA. It should be noted that a hierarchical system is taken sothatsenior instructors who have finished an advanced course can teach the elementarycourse. It is essential for the staff and foremen to learn statistical methods based on

their own problems. A more recent example of this approach is seen at the Toyota Motor Corporation.4.2 CASE OF TOYOTA MOTOR CORPORATION According to the highly stable condition of manufacturing processes in Japan arecent tendency of TQM is changing from statistical approaches to a morephilosophical(or conceptual) approach with slogans such as customer¶ s satisfaction, market in(rather



than product out), source control and so on. It is, however, obvious that thephilosophyof TQM can only be carried out with the scientific approach. Furthermore the recentdevelopment of statistical methods has enabled us to handle new types of problemsanddata coming out of off-line as well as on-line processes. It is therefore very

inappropriate to adhere to the classical SQC (Statistical Quality Control) approachand itis strongly recommended to go beyond it. Under these circumstances Toyota¶sapproachis remarkable in that it is convinced of the necessity of the new scientific SQCmethodand it is practising it. We will briefly introduce the system here and refer to Amasakaand Osaki (1999) as well as to Amasaka et al. (1999) for details.First, Toyota has developed its own methodology called µSQC Technical Methods¶integrating statistical methods such as Seven New Tools and other basic SQCmethods,multivariate analysis and design of experiments with engineering techn ology, which

canbe used efficiently and appropriately at each step of problem solving in the course of research, development, manufacturing and marketing. This is carried out byassessing aone shot analysed with a ready made statistical method. They call it mountainclimbingfor problem solving by use of µSQC Technical Methods¶.To support the efficient utilisation of the µSQC Technical Methods¶ the integratedSQC network TTIS (Toyota SQC Technical Intelligence System) has also beendeveloped. It is composed of TSIS (Toyota SQC Intelligence System), TPOS (ToyotaTQM Promotional SQC Original Soft), TSML (Toyota SQC Manual Library) and TIRSChihiro Hirotsu 61

(Toyota Information Retrieval System).Table 1. QC Education Schedule in Takenaka Corporation (Table 3.2 of Jido, 1990-1991)HIERARCHY PURPOSE IMPLEMENTATION PROCEDURESeminar Follow-upDirectors To acquire knowledge toevaluate TQC activities astop managementDirector SpecialCourse (JUSE)To enhanceknowledge through

attending PresidentDiagnoses &Consultations.General managers To acquire fundamentalknowledge and concept of TQC, as ³upper´ middlemanagement.Executive Course(JUSE)Senior managers



ManagersTo acquire principalknowledge and basicstatistical methods of TQCas middle management.Manager Course(JUSE & JSA)In-house TQCManager Seminar (5days)To hold BranchGeneral Manager¶sQC Diagnoses andConsultationTo participate invarious QCDiagnoses andConsultations.To present the

outcome of TQCactivities at in-housegatherings andconventions.QC Specialists To acquire the TQC concept,statistical methods and other professional knowledgebecoming QC promoter inhis department.Various outsideseminars (JUSE &JSA)Engineers To acquire the TQC concept

and statistical methods.In-house TQC BasicCourse (B) 15 days Administrators To acquire the TQC conceptand basic statistical methods.In-house TQC BasicCourse (A) 10 daysStaff members To acquire the TQC conceptand often-used QCtechniquesIn-house TQCElementary Course 3days

To present QCactivities at variousgatherings andconventions.Clerical workers To acquire the TQC conceptand knowledge required for QC circle activitiesSeminars and lecturesconducted by in-houseinstructors



QC circle gatheringsand conventions.New recruits To acquire basic TQCconceptIn-house TQCOrientation Course 1dayJUSE: Union of Japanese Scientist & Engineers, JSA: Japanese Standards Association

TPOS is the friendly tailor-made software of Toyota and it is composed of TPOSPM(Multivariate Analysis), TPOS-PS (General SQC Methods), TPOS-PO (design of experiment), TPOS-PK (sensitivity analysis) and TPOS-PR (reliability analysis).Multivariate analysis, for example, contains discriminant analysis, multiple regressionanalysis (1), (2) and principal component analysis. One can refer to varioussuccessfulapplications in real business through TSIS and also find past successful examples of problem solving in Toyota by TIRS. To sum up TTIS is, as stated in Amasaka andOsaki(1999), the intelligent system for SQC applications consisting of four main systems

synthesised to grow while supplementing one another. TTIS has been very efficientlyused in in-company education and training of SQC in Toyota.62 Training in Total Quality Management

Toyota also employs the hierarchical system of education and training. It is intended,in addition to educate beginners, to train the in -company SQC special staff andadvisorswho can act as SQC promotion leaders of workshops of 200 departments and alsoto beengaged in the SQC seminars as trainers.Now the Toyota education system is planned and implemented in six ranks:Beginner (100%), business (100%), intermediate (60%), lower advanced (15%),upper

advanced (5%) SQC classes and SQC special advisor class (2%). The ratios of participants to the total of twelve thousand employees are given in the parenthesessothat 100% of employees are, for example, expected to attend the beginners andbusinessclasses.The beginners and business classes are designed to cover the daily works while atthe two middle class courses participants will learn and practice the new SQCmethods.The two highest classes are aimed at training the trainers and leaders of respectiveworkshops and for extra professional purposes advanced lectures are also gi ven.Qualifications for SQC special staff and SQC special advisors are determined and

therespective titles are given to successful candidates. According to Amasaka andOsaki(1999) eight hundred special staff and advisors who have successfully completed t hesixsteps are now actively engaged in their respective works.Three courses for the beginner personnel are prepared in more detail: technician,sales and clerical courses. Typical curricula of the technician course (3 days, 21hrs.),



which are composed of twelve lectures, are given in Amasaka and Osaki. It shouldbenoted that in the second lecture they learn how to integrate various statisticalmethods tosolve real problems using the Toyota Technical Methods. The TPOS is fully utilisedthroughout the twelve lectures so that each trainee can take the TPOS back to his or

her own workshop for practical use.5. TQM SYMPOSIUMS AND CONFERENCESJUSE and JSA have been promoting many conferences and symposiums on varioustopics and at a variety of levels. It is important to attend those meetings to presenttheir own activities and to learn of achievement by others. An annual Conference onScienceSQC is being held within the Toyota Group inviting top management and externalprofessionals to attend and it is a very good incentive for employees to present their achievement to the heads of the company.Of course the Annual Conference and Symposium of the Japanese Association of

Quality Control are also giving a very good opportunity for researchers of TQM topresent their achievements as well as to learn from others.6. CONCLUDING REMARKS As stressed in the text the most important thing for training researchers in thecompany is that trainees themselves have their own motivations. Then it is essentialtoteach statistical methods based on the real problems they are confronted with. Whenthey have their own motivations and related data, it is very easy to teach themstatisticalideas. It does not depend on the particular field where they are working. It inevitabl ysuggests to them not to work alone when analysing their data, but to be aware of thephase of R & D activities he or she is, and to include manufacturing, marketing andafter market research.Chihiro Hirotsu 63

I also suggested that statistics training is most efficiently done by in-companytrainers with some appropriate software and database of the company¶s pastachievements. Then an in-company hierarchical education system of special SQCadvisors and staff is essential for discovering skills and also f or maintaining thesystemitself. However, if the in-company education system is not matured enough thecoursesoutside the company may also be efficiently utilised.In Japan, JUSE, JSA and other Institutions are providing a sufficient variety of

courses, philosophical as well as technical, for TQM training. Researchers can alsoconsult with the experts in the universities. Those experts have usually someconnectionwith JUSE or JSA and they can introduce appropriate tutors for the companies. Itshouldbe noted that even the most prominent companies such as Toyota Motor Corporationand Takenaka Corporation are utilising the courses of JUSE introduced in § 3.REFERENCES



Amasaka, K., & Osaki, S. (1999). The promotion of the new statistical quality control inte rnaleducation at Toyota Motor: A proposal of µscience statistical quality control¶ for improvingthe principle of total quality management . European Journal of Engineering Education, 24,259-276. Amasaka, K., Kosugi, K, & Maki, K. (1999). A proposal of th e new SQC internal educationfor management (in Japanese). Quality, Journal of the Japanese Society for Quality Control , 29,292-299.Hirotsu, C. (1992). QC technology (in Japanese). Quality, Journal of the Japanese Society for Quality Control , 22, 238-258.Ishikawa, K. (1969). Education and training of quality control in Japanese industry. Reportsof Statistical Application and Research, JUSE 16, 85-104.Jido, J. (1990-1991). TQC in Takenaka Corporation. Reports of Statistical Application and Research, JUSE 37, 29-44.Mizuno, S., & Kume, M. (1978). Developments of education and training in quality control.Reports of Statistical Application and Research, JUSE 25, 78-102.Okuno, T. (Ed.) (1990-1991). Special issue: The Deming Prize. Reports of Statistical

Application and Research, JUSE 37.Chihiro HirotsuF aculty of Science & Technology, Meisei University 2-1-1 Hodokubo, Hino-City, Tokyo 191-8506, JapanE-mail: [email protected]

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