Application of 6-Sigma for Service Improvement Case Study: Mala Tang

NFor Earnest Koshi

Li Ran

Shen, Yi

11.06.2008

2

Contents

Motivation, Goals and Expected Results

DefineCTQ

Process Description

MeasureActual Process with Time

Questionnaire Survey

AnalyzeCause and Effect Chart

AHP Evaluation

Pareto Chart

ImproveDesign of Experiments

Simulation

Conclusion

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Motivation, Goals and Expected Results

Tsinghua University is a large community hence, need for improvement in on campus services systems in our campus

In this research project, we adopt DMAIC methodology for the improvement service quality of the Mala Tang window at the Taoli Yuan refectory which is one of biggest on campus

By applying six sigma, we seeks to find and eliminate causes of defects and errors in this sector by focusing on outputs that are critical to students who are the customers.

There exist long queues in the refectory during the rush hours , almost 40% of time in the refectory spent in queue.

Goal is to reduce the total waiting time to 7 minutes or even less while maintaining high level of customer satisfaction

Figure 2 below indicates the CTQs: diversity, waiting time and serving time.

We expect high diversity short waiting time and serving time t

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Define - Critical to Quality

Stakeholder

Strategic focal point

KPI

Internal CTQ

Student Refectory

Satisfaction

Comfort

Cost

Efficiency

Throughput timeDelicious

Diversity

Proper spice Queueing time

Serving time

Cannot measure

CTQ+ CTQ-

CTQ-

-The queue is G/G/2

-FCFS criterion and Customers never abandon the queue

-Infinite supply of spices

-Total number of cook units in the Mala Tang window is six and 2 staffs

-Limited accommodation limited and inventory storage space

Assumptions And Constraints

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Define - Process DescriptionS

tore

Sta

ffS

tude

nts

Order

Determineprice

Pay

Operation sub process

Replenish sub

process

Enter the system

Is it my order?Wait Take & leave

Output 1

Output 2

Input 1

Input 2

15 – 30 sec Input 1 to Output 1: 6 secInput 1 to Output 2: 28 sec53 sec

Variables

-Decision variables: Include the process itself, proportion of ingredients and the layout

-Independent variables or outputs: Directly or indirectly determined by the decision variables. Include average / maximum waiting time, average / maximum queue length, cost, and some subjective factors such as satisfaction of students

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Measure – The ACTUAL Process

.

Availablecooks? Cook

Previousorder ready?

Yes

No

Put the order into queue

Return empty bowl to front

Get cooked Add spicesTake to

front

Any orders in queue?Yes

CookReturn empty bowl to front

Add staple food

Yes

Output 1

Output 2

Input 1

No

Input 2

No

3 - 48 1 - 3

0 - 1

7 - 87 - 13

1 - 23 - 5

2 - 36

3 - 481 - 36

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Measure – The ACTUAL Process (cont…)

Is any ingredientalmost used up?

Take the empty basket

Yes

No

Output

Input

Walk to store

Filling

Walk to frontPut the

full basket

1 4

4 4

40

Measurement -Video Analysis

-Actions captured by use of a camera

-Videos short secretly in order to get an authentic working conditions and without manipulation concerning motivation

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Measure – Questionnaire Survey

Fifty copies distributed and forty seven valid returned

Aim of the survey was to detect the customers’ demand towards possible service and get their ratings for the service

Result provided opinion of customers permitting us to know what matters most

The next step will be to gather a high quantity of reasons which causes that long waiting / serving time

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Dissatisfaction

4%

43%

34%

19%

No

A little

Dissatisfied

Very angry

Measure – Questionnaire Survey (cont…)

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Catagories of Suggestions

0

1

2

3

4

5

6

7

Spe

ed

Sca

le

Div

ersi

ty

Tast

e

Layo

ut

Not

chan

ge

Vol

ume

Pric

e

Num

ber o

f Sug

gest

ions

Measure – Questionnaire Survey (cont…)

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Analyze – Cause and Effect Chart

Waiting too long

People Procedure

Provisions CustomerEnvironment

Inappropriate proportionof ingredientInterfering

Poor facility layout

Low proficiency

Fatigue

Too many branches

Few cook devices

Cooking time

Long boiling time

Need manual mixture

Inappropriate positionof ingredient

No standard

Need too many judgements

Unhappy moodContinuous work

Repetitive work

Hunger and thirst

Poor motivation

Insufficient space

Inappropriate dimensionof devices

Long and frequent moving

No standard time

Not enough people

Inpredictable amount of customers in queue

Rush Hour

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Analyze – AHP Evaluation

.

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Analyze – Pareto Chart

Pareto Chart for Causes

0.341

0.20040.1422 0.1249

0.09220.0587

0.0226 0.0176

1.000

0.9007

0.8085

0.5414

0.6836

0

0.2

0.4

0.6

0.8

1

No std. Layout Pos.ofingredient

Manybranches

Prop.ofingredient

Lowspace

Fatigue Mood

Causes

Imp

ort

an

ce

Designed experiments

Simulation

14

Improve – Design of Experiments

15

Improve – Design of Experiments (cont..)

16

Improve – Design of Experiments (cont..)

Has branchNo branch

195

190

185

180FreeFi xed

3No

195

190

185

180

Branch

Mean

Sequence

Unexpected task

Mai n Ef fects Pl ot for C8Data Means

FreeFi xed 3No200

190

180

200

190

180

Branch

Sequence

Unexpect ed t ask

No branchHas branch

Branch

Fi xedFree

Sequence

I nteracti on Pl ot for C8Data Means

17

Improve – Simulation

18

Improve – Simulation (cont…)

Hf=40, Lf=2030 each

291

288

285

282hi gh varl ow var

f ront hi gh, back l owal l equal

291

288

285

282

Capaci ty

Mean

I ngr. Sel ect i on

I ngr. Pos

Mai n Ef fects Pl ot for Ti meData Means

hi gh varl ow var f ront hi gh, back l owal l equal

296

288

280296

288

280

Capaci t y

I ngr . Sel ect i on

I ngr . Pos

30 eachHf=40, Lf=20

Capaci ty

l ow varhi gh var

I ngr. Sel ecti on

I nteracti on Pl ot for Ti meData Means

Service time as output

19

Improve – Simulation (cont…)

Finished orders as output

Hf=40, Lf=2030 each

258

256

254

252

250

hi gh varl ow var

f ront hi gh, back l owal l equal

258

256

254

252

250

Capaci ty

Mean

I ngr. Sel ecti on

I ngr. Pos

Mai n Ef fects Pl ot for Fi ni shedData Means

hi gh varl ow var f ront hi gh, back l owal l equal

260

255

250

260

255

250

Capaci t y

I ngr . Sel ect i on

I ngr . Pos

30 eachHf=40, Lf=20

Capaci ty

l ow varhi gh var

I ngr. Sel ecti on

I nteracti on Pl ot for Fi ni shedData Means

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Conclusion

Six Sigma was a useful method to identify the key factors of the service process

Standardization of the tasks, especially fixed task performing order and fewer occurances of unexpected tasks can give lower service time

Fewer branches in the process makes lower service time

refectories in general can raise their throughput

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Conclusion

We did not match our defined goal, since variation on the customers’ side is still too high

service quality is improved by Six Sigma more customer requirements can be met, but not all

A revised application of Six Sigma should concentrate on customer behaviour and synchronize it with the process

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Q & A

Thank You

Q & A