qp0606thiraviam

7/30/2019 qp0606thiraviam

1/5

Simple Tools for

Complex SystemsbyAmar Raja Thiraviam

40 I JUNE 2006 I www.asq.org

oot cause analysis and corrective action

tracking are vital elements of any qualityimprovement initiative. These tasksbecome even more critical in an organization withcomplex processes, simply because of the largenumber of opportunities for failure involved.

In such instances, it is common to look for com-plex solutions to solve the complex problem. Often,all it takes are simple tools like Pareto analyses and

process mapping to reduce the defects of a com-

plex manufacturing process.First, it is important to define the word com-plex. What is complex to one person may be sim-ple to another. Our definition of a complex processis one with a large number of opportunities for fail-ure.1 In our high-tech manufacturing environment,which produces electromechanical devices, eachunit has more than 1,500 opportunities for failure.

Of course, the tools explained here can workeffectively on any process.

Six Sigma Based Process Maps

The first tool we used in our case was processmapping. In our Six Sigma based technique, thefirst step was to understand, identify and define allopportunities for failure in a given manufacturingprocess. We mapped processes from incominginspection through shipping, as shown in Figure 1.

We knew the root cause of any quality problemcan fall into one of three categories: part, process ortool.2 We classified all opportunities into one of thethree categories and assigned each a code. Noticethe process map also indicates whether the processis value added or nonvalue added and whether the

part is electrical, mechanical or software. Such clas-sifications are common in any complex manufac-

R

QUALITY IMPROVEMENT

In 50 WordsOr Less

Simple tools such as process maps and Pareto

charts can help correct nonconformances in

complex systems.

A team in a high-tech manufacturing setting used

such tools to achieve significant improvement.


2/5

turing process and are helpful

in analyzing these problems.The system also is designed sofrequent revisions made to theproduct do not affect the track-ing and analysis of the rootcause data.

In Figure 1, value added andnonvalue added processes are differentiated bycolor as are electrical, mechanical and softwareparts. Activities like testing (N2) and rework (N4)are labeled as nonvalue added. In a lean manufac-turing organization, these types of activities are

either eliminated or kept at a minimum.

Root Cause Coding

The next step was to accurately code the rootcause of all nonconformances so theycould be analyzed effectively. In this case,we found the existing root cause codingsystem was too generic and usually point-ed to the obvious effect and not the rootcause. As these effects tended to manifestthemselves in different ways, this in turncaused the number of cause (effect) codes

to continually increase.The Six Sigma based process maps helped

create an effective replacement to the original causecode system. Several elements of the process mapwere integrated to form the cause code for eachissue. The heading of each process map had a name

and code. In the case of Figure 1, it is final assemblytwo1.2.3. All parts, process steps and tools alsohad their own codes. These two codes coupled to-gether defined a unique code for each opportunity

QUALITY PROGRESS I JUNE 2006 I 41

Tool codeFinal assembly two1.2.3

Vaule addedNonvalue addedSoftwareElectricalMechanical

Name of the assembly process

Part Code

Program oneVIII

Test the subassemblyusing the software

program.

N2

Install embeddedsoftware using

program.

4

Process code

If the shaft is oversize, turn it to spec.

N4

Cover oneE,cover twoF

Use adhesive andtorque screws

to connect both covers.

5

Torque wrenchIII

PCBA ScrewsB, C

Install PCB onto thebase using two

screws.

6

Wire bundleD

Feed wire bundlethrough the bottom

of the hub.

17

PCB = printed circuit board

The Process MapFIGURE 1

Summary of Opportunities for ErrorTABLE 1

Mechanicalopportunities

Electricalopportunities

Softwareopportunities

Total Percentage

Parts 23 0 2 25 54.3%

Process 17 0 4 21 45.7%

Total 40 0 6 46 100.0%

Percentage 87% 0% 13% 100%


3/5

for failure in the entireprocess. Hence, step six inFigure 1 (p. 41) would becoded as 1.2.3(6), in whichthe first three digits repre-sent the lower levelprocess, and the number orletter inside the parenthe-ses indicates the opportu-nity that has failed.

So, if we have a qualityproblem due to a faultyprinted circuit board (PCB)used in step six, the rootcause code would be1.2.3(A). When the screwis faulty, the code would

be 1.2.3(B). Similarly, eachincident can be investigat-ed and assigned to one ofthe unique codes in theprocess maps.

Table 1 (p. 41) shows asummary of the processmap. This gives us usefulinformation about thenature of the productionprocess and the types of components involved.

In a lot of situations, it wasnt feasible to map allthe processes. In these cases, we mapped only themanufacturing processes and not the supportingprocesses such as purchasing and planning. Wealso developed a list of other codes to categorizethe issues whose root causes were not mapped:

99.1: material shortage. 99.2: inventory management. 99.3: customer related. 99.4: other.The severity and nature of the quality problems

often vary widely, and it is always better to differ-entiate the cause by the nature and magnitude ofthe quality problem. For example, we may want todistinguish between cosmetic and functional quali-ty problems. We added special characters to theprocess map code to facilitate this. For example, ifthere is a small scratch in the PCB (Figure 1) itwould be coded as 1.2.3(E)-, whereas a functional

electrical failure in the PCB would be coded as1.2.3 (A) without any special characters.


Similarly, an incoming nonconformance in a PCBwill be coded as 1.2.3(A)!, whereas a design failurewill be coded without any special characters. Thistechnique also forces us to identify the root causeand not the blatant symptoms or effects.

Monitoring the ProgressParts per Million Levels

The three-digit assembly code (1.2.3) in the rootcause code helped identify the contribution of sev-eral lower level assembly processes to the overallprocess nonconformance level. Because the processmaps are based on opportunities for failure, it islogical to use Six Sigma metrics such as parts permillion or sigma levels. More common metrics alsocan be used.

Table 2 (shows how the process map codes arecategorized by the lower level assembly processes.This type of analysis helps us get the informationon each of the subdivisions and focus our correc-tive and preventive actions in the right areas.

QUALITY IMPROVEMENT

Pareto ChartsVital Few and Trivial ManyFIGURE 2

Count

Top root causessubassembly assembly 1 to 3July 2005

Top five causes

1.1.4 (17)Installation of bearing1.1.3 (12)Installation of harness1.1.3 (8)Shaft AB201.1.4 (E)Bearing 5001

1.1.4 (XII)Software program X

9

1

8

7

6

5

4

3

2

1.1.4 (17)0

1.1.1 (28)

Cause

1.1.3 (12) 1.1.4 (E) 1.1.4 (XII) 1.1.1 (12)1.1.3 (8) 1.1.2 (17)

Trivialmany

Vitalfew

Production line employeesEngineering team


4/5

Pareto AnalysisThe Vital FewAnd Trivial Many

Subsequently, we used another simple tool, aPareto analysis, on quality problems of each ofthe lower level assembly processes. This analysishelped the engineering team focus on the vital fewproblems against the trivial many. But it is impor-

tant to remember you need to pay attention to thetrivial many issues as well in a continuous im-provement environment.3

We achieved this with a unique approach. Theindividual production teams had monthly meet-ings in which they discussed recent quality prob-lems. The focus, though, was on the trivial manyissues that could be solved by simple techniquesthat didnt require technical expertise. Thus, engi-neering worked on one side of the Pareto analysis,solving complex technical problems, while produc-tion employees worked from the other end of the

Pareto analysis, solving simple quality problems(Figure 2). This increased involvement and created

a sense of teamwork among the employees.To further increase awareness, we published and

posted Pareto charts in production cells. This alsocreated a visual factory environment. Table 2 showsan example of a Pareto chart at an individual station.

Tracking the EffectivenessOf Corrective Actions

If root cause analysis makes or breaks a qualityimprovement project, the corrective action trackingtechnique makes it complete. Hence, it is importantto verify corrective actions and ensure they are effec-tive. We can do this just by monitoring the reoccur-rence of the same problem in subsequent periods. Inour case, the root causes were identified by a uniqueprocess map code, so finding reoccurrence was aseasy as doing a simple search in the spreadsheet ordatabase where the information was stored.

At the end of each month, the subject matter

experts documented the corrective actions takenagainst each root cause that occurred more than

QUALITY PROGRESS I JUNE 2006 I 43

Pareto Chart at Individual StationTABLE 2

Parts per million (PPM) levels by station January 2005

CategoriesNumber of

nonconformitiesTotal

opportunities/unitPPM Target PPM

Module assembly one 1.1.1 25 158 4,164 773

Module assembly two 1.1.2 0 5 0 773

Module assembly three 1.2.1 | 1.2.2 | 1.2.3 | 1.2.4 7 182 1,012 773

Module assembly four 1.2.5 | 1.2.6 | 1.2.7 4 120 877 773

Module assembly five 1.3.1 | 1.3.2 1 84 313 773

Module assembly six 1.4.1 27 93 7,640 773

Subassembly one to three 1.5.1 12 83 3,805 773Subassembly two to six 1.6.1 | 1.6.2 6 97 1,628 773

Subassembly one to three 1.4.3 47 38 32,548 773

Final assembly one 1.7.2 1 34 774 773

Final assembly two 1.7.3 0 27 0 773

Cal/cert 1.9.1 | 1.9.2 | 1.9.3 1 25 1,053 773

EQC 1.12.1 | 1.12.2 | 1.12.3 1 52 506 773

Shipping 1.11.1 | 1.11.2 0 97 0 773

Total 132 1,294 2,684 773

Units produced this month 38 Target quality problems per unit 1

Cal/cert = calibration/certification.

EQC = environmental quality control.


5/5

once that month. This information was stored in theroot cause analysis matrix (Table 3). After 60 days,these incidents were reviewed again by searchingfor reoccurrence of the same issues. Reoccurringissues are considered open items, and expansivequality plans or problem solving projects may bedeveloped to solve them.

Breakthrough Improvements

A structured method like this allows us toreview all issues and ensure they are addressed. Inthis case, the project resulted in more than 60%reduction in nonconformance levels and helped theorganization reach breakthrough improvements.

The root cause analysis matrix included rootcause, effects, actions taken, frequency and effec-tiveness. This facilitated the existing solutionsearch process and made sure the knowledgegained through root cause analysis was retained

and made available to appropriate locations.This system also provided feedback for the lean

manufacturing efforts in thecompany. We identified thenonvalue added activities andexpressed them as a fraction oftotal opportunities. This helpedus critically examine the needfor each activity, eliminatewaste and work toward leanprocesses.

It also helped create a visualfactory environment and increaseemployees awareness of qualityproblems in their own areas andother areasthus showing themthe ramifications of their actions.The process maps also providedvaluable input into design andprocess failure modes and ef-fects analysis.

This system of root causeanalysis and quality improve-ment was effective and reward-ing in the kind of complex sys-tem common in high-tech in-dustries. It has helped us meetthe increasingly tough customerrequirements and standardsdemanded in critical areas.

REFERENCES

1. Allen Sajedi, discussions with author in May 2003,

August 2003 and February 2004.

2. Joseph M. Juran and A. Blanton Godfrey,Jurans Quality

Handbook, fifth edition, McGraw-Hill Professional, 1998.

3. Kenneth Stephens, lecture at the University of Central

Florida, Quality Design and Control class, spring 2003.

AMAR RAJA THIRAVIAM is a quality engineer for Ocean

Design Inc. in Ormond Beach, FL. He earned a masters

degree in engineering from the University of Central Flor-

ida in Orlando. Thiraviam is a member of ASQ and a certi-

fied Six Sigma Black Belt.


QUALITY IMPROVEMENT

commentPlease

If you would like to comment on this article,

please post your remarks on the Quality Progress

Discussion Board at www.asq.org, or e-mail

them to [email protected].

Corrective Action Tracking MatrixTABLE 3

Root Cause Analysis MatrixSeptember 2004

Purpose: To track the effectivness of corrective actionsbased on the process map cause code analysis

Scope: Production quality problems

Cause codeNumber of

occurencesCause(s) Effect(s) Actions taken Responsibility Sign off

Assembly one Total Prodn

1.1.4(N12) 1 1

1.1.1(B)! 1 1

1.1.1(B)!- 1 1

1.1.1(A)! 1 1

1.1.3(6) 1 1

Assembly two

1.2.1(30) 1 1

1.2.1(B)! 1 1

1.2.4(10) 1 1

1.2.4(9A) 1 1

Assembly three

1.2.5(N7) 1 1

1.2.5(D)+ 4 0

1.2.7(D+) 2 01.2.6(D+) 2 0

Calibration one 0

Documents

qp0606thiraviam