Application of 6-Sigma for

Service Improvement –

Case Study: Mala Tang AQM Term Project: Final Report

Koshi, NFor Earnest

Li, Ran

Shen, Yi

June 11, 2008

2

Table of Content

Table of Content ............................................................................................... 2

Executive Summary ......................................................................................... 3

1 Overview: Project Selection ....................................................................... 4

1.1 Background Information ................................................................... 4

1.2 Problems and its Symptoms ............................................................. 4

2 Define ........................................................................................................ 6

2.1 Goals and Expected Results ............................................................ 6

2.2 Framework ....................................................................................... 6

2.3 Assumptions ..................................................................................... 8

2.4 Constraints ....................................................................................... 9

2.5 Variables .......................................................................................... 9

3 Measurement ........................................................................................... 11

3.1 Video Analysis ................................................................................ 11

3.2 Revised Process Diagram .............................................................. 11

3.3 Questionnaire ................................................................................. 13

4 Analyze .................................................................................................... 16

4.1 Cause and Effect ............................................................................ 16

4.2 Correlation & Pareto ....................................................................... 16

5 Improvement ............................................................................................ 19

5.1 Design of Experiment ..................................................................... 19

5.2 Simulation ...................................................................................... 23

6 Conclusion & Outlook .............................................................................. 28

Appendix A: Questionnaire ............................................................................ 30

Appendix B: DOE results ............................................................................... 31

3

Executive Summary

6-sigma is a powerful tool to detect errors within a process regardless

whether it is a manufacturing process or service process. We applied the

6-sigma Methodology with its roadmap DMAIC (Define – Measure – Analyze –

Improve – Control) on the serving process of the Mala Tang window of the

Taoli canteen in order to reduce the service time per customer and therefore

the waiting time.

During the define step we drew our project scope, specified our goal

concerning the improvements we want to make and made assumptions

concerning the process. A CTQ tree and a rough process diagram were drawn

to illustrate the process understanding. Constraints were set limit the range of

the task and Variables (decision and dependency) were defined to give

additional insight into the whole field of the project.

The measurement step contains a video analysis of the service process at

the canteen window and a revised and improved process diagram with times

measured for each single action. Furthermore a questionnaire was designed in

order to find out more about the average number of ingredients ordered by

students and their satisfaction with the present situation concerning waiting

time and serving time. In addition to that suggestions were collected to find out

the factors that need to be changed in order to achieve a higher customer

satisfaction.

The analyze step deals with a cause and effect diagram to find many

factors that might have an influence on the output – the long waiting time. After

a qualitative selection of the most important ones a correlation matrix helped to

find an order of the main factors and their importance.

In the Improvement stage a DOE was conducted to reveal the impact of

those factors which are considered as the most important in a process. The

following simulation on Java basis that was made using data from the

measurement phase provided additional data for another DOE to test the other

factors

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1 Overview: Project Selection

1.1 Background Information

Tsinghua University is a large community with tens of thousands of people

and the area it takes can almost compare to a town. Besides classroom,

lecture hall and laboratories for students and professors, it also has its own

supply and logistic service systems just like an isolated world. Hence there is

much space for improvement for the service systems in our campus. In this

research project, DMAIC (Define – Measure – Analyze – Improve - Control),

the implementation steps for 6-sigma Projects are followed to analyze and

improve the service quality of the Mala Tang window of the Taoli refectory.

Quality especially service quality is a crucial factor in the fast growing

modern China. 6-sigma is in the large bunch of the quality management

methods and it is very popular nowadays. 6-sigma can help to improve the

service process. The term 6-sigma is based on a statistical measure that

equals to 3.4 or fewer errors of defects per million opportunities. 6-sigma can

be described as a business improvement approach that seeks to find and

eliminate causes of defects and errors in manufacturing and services process

by focusing on outputs that are critical to customers.

6-sigma provides a blueprint for implementation of total quality system. Its

roadmap – DMAIC (Define-Measure-Analyze-Improve-Control) means: Define

the problem of the process; Measure the performance of the process; Analyze

the cause if the process, Improve the process, reduce waste; Control the

process, eliminate the occurrence of the same problem.

1.2 Problems and its Symptoms

A significant phenomenon in our campus is the long queues in the

refectory during the rush hour (i.e. after-class hours). For example, the

average time for a student from joining a queue to getting the of food in the

Mala Tang window of Taoli refectory is about 10 minutes, while the minutes for

enjoying this meal are just 15! Thus the waiting (or wasted) time takes 40% of

the whole time of a student in the refectory (Figure 1)

5

Unit: minute

15

10Eating

Waiting

Figure 1-1: Composition of time spent in Taoli refectory

6

2 Define

2.1 Goals and Expected Results

The 6-sigma team aims at reduce the total waiting time to 7 minutes or

less and remain the same level of customer satisfaction. The critical-to-quality

(CTQ) tree is shown in figure 2. There are 3 CTQs: diversity, waiting time and

serving time. And the diversity is required to be high, while the others are

required to be low.

Figure 2-1: CTQ flow down for Mala Tang serving process

2.2 Framework

Figure 3 shows the SIPOC framework of our project and the scope of

improvements

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Mala Tang

Serving Process

Input: Ingredients Output: Mala Tang

Staffs & Refectory

Customer: Students

Our project scope

Supplier: the University

(Cannot be controlled and set as constraints)

Figure 2-2: SIPOC framework

Our scope of work focuses on the Mala Tang serving process and the

related output. We do not consider the complete input and output of the

process. Within the scope is furthermore the staff of the refectory. A rough

process diagram (Figure 4) helps to illustrate the general idea of the serving

process at Taoli refectory. As one can see the „Store‟ does not lie within the red

line and is therefore not part of the project scope. We focus on the interaction

between „Students‟ and „Staff‟ which embodies the service process.

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Malatang serving process

Staff StoreStudents

Order

Order more?

Yes

Determine price

No

CookPay

Previous order

ready?

Yes

Bring to front

Wait

Is it my order?

Take

Yes

No

Yes

Replenish

No

No

Add spices & rice

Is any

ingredient

almost used

up?

Figure 2-3: Mala Tang serving process & the project scope

2.3 Assumptions

The queue of waiting for service is G/G/2, and the distribution of

inter-arrival and service time will be further studies and assigned in our

simulation. This is in accordance with the fact of the Mala Tang window of Taoli

9

refectory.

The patience of customers in the queue is unlimited and they will not leave

until they get the service. This is generally correct since the waiting people

rarely leave the queue before get the service at the Mala Tang window of Taoli

refectory.

The queue follows First-Come-First-Serve (FCFS) criterion. It is true since

the Mala Tang queue hardly has queue jumpers.

The amount of spice is infinite. It is almost true since the usage of spice is

little and it almost needs no replenishment during the process of service.

2.4 Constraints

There are some fixed parameters in the refectory which is difficult or

impossible for the 6-sigma team to change and is considered as constraints:

Total number of cook units is 6 in the Mala Tang window of Taoli refectory.

Total number of front staffs is 2 in the Mala Tang window of Taoli refectory.

Total room space of the Mala Tang window of Taoli refectory is a constraint

and cannot be modified.

Although the proportion of ingredients (vegetables, meat, and rice) can be

changed, the amount remains constant due to the limited inventory space

2.5 Variables

The variables are divided into 2 categories: decision variables, which can

be decided by the 6-sigma team, and dependency variables, or outputs, which

are directly or indirectly determined by the decision variables

2.5.1 Decision Variables

The decision variables are: the process itself, proportion of ingredients

and the layout

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2.5.2 Dependency Variables

As mentioned before in section 1.3, the dependency variables for our

evaluation are: average / maximum waiting time, average / maximum queue

length, cost, and some subjective factors such as satisfaction of students

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3 Measurement

3.1 Video Analysis

Given on the 1st version of the process diagram we made videos from the

Mala Tang serving process of the Taoli refectory. We intended to determine the

time for the single actions the cooking operator needed from the beginning of

taking the order over the cooking process till the end of the process the

handing over of the finished dish including the rice.

We shot the videos secretly in to provide an authentic working condition

and without manipulation concerning motivation or anything else which might

have affected the outcome

3.2 Revised Process Diagram

The analysis of the procedures shown in the videos made us redraw the

process diagram. From the video we could determine the times needed for

each action step during the whole service process. Our observations from the

new process diagram with process times were:

This process contains a lot of branches and therefore is has a lack of

standardizations;

Much time is spent in the region between input two and output two of the

operation sub process;

"Replenish sub process" takes almost 1 minute. Proper configuration of

the ingredients in front to reduce the frequency of replenishment, the total

efficiency will improve a lot.

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Figure 3-1: Process diagram version 2, 1/3

Figure 3-2: Process diagram version 2, 2/3

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Figure 3-3: Process diagram version 2, 3/3

3.3 Questionnaire

3.3.1 Questionnaire Design

We designed a survey distributed among random students who came to

the Taoli refectory on the May 11th 2008. Altogether we handed out 50 sheets

of questionnaires and among those 47 valid returned back to us.

The questionnaire contained the questions involving the frequency to

have Mala Tang, time, number of ingredient ordered, perception of queue

length, waiting time and satisfaction, etc. Concrete questions can be found in

Appendix A (in Chinese). The aim of this survey was to detect the customers‟

demand towards possible service improvement in Mala Tang process and their

satisfaction regarding the waiting / queering time

The questionnaire contained the listed questions. The aim of this survey

was to detect the customers‟ demand towards possible service improvement in

Mala Tang process, parameters related to customers (for modeling) and their

satisfaction regarding the waiting / queering time.

3.3.2 Statistical Results

From the questionnaire there are some conclusions:

Most people (73%) will not give up queueing even if the queue is longer

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than 2 windows, and 1/3 of the people will never give up (Figure 8). So in our

model, we added an assumption that servers are always busy.

Figure 3-4: Acceptable queue length

Another main findings from the statistical result of the survey is the fact

that in average the students are not satisfied (Figure 9) with service and

waiting time at the Mala Tang window of the Taoli canteen.

Figure 3-5: Dissatisfaction level

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Note: If we give the “dissatisfaction” levels some weight:

No 0

Little 1

Dissatisfied 3

Very Angry 9

Then we can get the average dissatisfaction level of 3.563

There are also some improvements regarding the serving time as

suggested by the customer themselves, Figure 10 gives number of the

suggestions by categories.

Figure 3-6: Customers' suggestions for further Improvements

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4 Analyze

Now we know that customers want to be served faster. This will

automatically lead to higher satisfaction level among students and will reduce

the overall queuing time for everybody.

The next step will be to gather a high quantity of reasons which causes

that long waiting / serving time.

4.1 Cause and Effect

A fishbone chart, also called „Cause and Effect‟ diagram, is helpful to brain

storming many reasons that can lead to an outcome and is the first step to

identify the key-reason and most crucial factors that have the highest influence

on the outcome.

Figure 4-1: Cause and Effect Diagram

Since it is a service process and not a manufacturing process the 5 P‟s

are uses instead of the 5 M‟s. The main outcome is „long waiting time‟ which is

caused by 5 major symptoms and each has several reasons or causes itself.

4.2 Correlation & Pareto

After the Selection of the most crucial factors from the Cause and Effect

Diagram a correlation analysis of these main causes was mode. After serious

consideration, some factors were not taken into further consideration since it is

17

not possible or hardly possible to change the factors in order to achieve

improvements. The analytic hierarchy process (AHP) method is used to

determine the weight of those causes (Figure 12), excluding some reasons

that cannot be further improved.

Figure 4-2 AHP result of weight of causes

From the weight above a Pareto-chart is drawn to illustrate the crucial

factor to concentrate on during further project process.

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Pareto Chart for Causes

0.341

0.2004

0.1422 0.12490.0922

0.05870.0226 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.of

ingredient

Many

branches

Prop.of

ingredient

Low

space

Fatigue Mood

Causes

Imp

ort

an

ce

Figure 4-3 Pareto chart for causes

The accumulated weight of the main causes shows that a total of 5 main

causes contribute over 90% of the whole amount of causes. So the 5 critical

factors or reasons for a high waiting time at Mala Tang window of Taoli

refectory are found now.

1. No standard

2. Process layout

3. Position of each single ingredient

4. Many branches in the actions and during process

5. Proportion of ingredients

The first and fourth points are more related to psychological issues and

can be further studied by design of experiments (DOE). Our efforts in

improving the process time will concentrate on these 2 main causes. The other

3 are systematic factors and can be studied by modeling and simulation.

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5 Improvement

5.1 Design of Experiment

5.1.1 Introduction

This DOE should find out about the influence of standardized patterns and

branches on the actual working or process time. The primary objective of this

design of experiment is to find the crucial factors that might change the

process time of a task.

DOE is known as a structured, organized method for determining the

relationship between factors that affect a process and the output of that

process. After the experiment we want to use the Response Surface

Methodology to find the optimum combination of factors that yields to a

minimum working time.

Our objective is to find out how much standardized actions and branches

contribute to the process time of a task (measured in seconds) and ultimately

find a fitted model to best predict the final working time

5.1.2 Methodology

Figure 5-1 DOE Scene Layout

Figure 16 shows a general overview of the scene layout on which we

conveyed our DOE.

There are 9 tasks carried out during the DOE:

1 Walk to one side of the source

2 Pick an item

3 Walk to center table

4 Put the item on the center table

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5 Walk to the other side of the source

6 Pick an item

7 Walk to center table

8 Put the item on the center table

9 Next cycle, until all books is moved to center table

In order to investigate the influence of the factors we picked from the

Pareto-chart analysis on the outcome of the DOE. The output of the DOE is

the time needed to complete all the tasks under certain working conditions.

The Factors considered in the 23 experiment is as shown in Table 1

Table 5-1 Factors of DOE

Factors Level

- +

Branch A No branch Has branch

Sequence (Std.) B Fixed order Free Order

Unexpected tasks (Std.) C No 3

Description of factor A

“-“: the person can use all books in source 1 and then use books in source 2.

“+”: the person should use one book from 1 and then in the next cycle the person

should use one book from 2, and then continue

Description of factor B

"-": the person should pick one book and then one piece of paper in a cycle

"+": the person may either pick a book or paper first in each cycle, decided by random

variable generator

Description of factor C

"-": no interruptions

"+": when finish a cycle, the person may be interrupted by other things. After which

cycle is decided by random variable generator. The total number of interruptions in one

repeat (16 cycles) is 3

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5.1.3 Results

Table 5-2 Experiment results of DOE

Factors

A + - + - + - + -

B + + - - + + - -

C + + + + - - - -

Result Mean

time 206.53 191.03 188.02 183.6 186.14 191.63 177.92 175.94

Using data from Table 2, the analyzing of factorial design and factorial

plotting in MINITAB 15 are performed. Figure 5-2, 5-3 and 5-4 are the results

Figure 5-2 General analysis results from MINITAB

Figure 5-3 Main effects plot for process time

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Figure 5-4 Interaction Plot for Process Time

Figure 5-3 shows the main effects and indicates that the sequence order

and the appearances of unexpected tasks have the main influence on the final

process time. This confirms our findings from the Pareto-Chart where we

identified those as critical factors that have the highest contribution towards a

long process time and therefore leads to high waiting time in a service process.

Figure 5-2 and figure 5-4 underlines the high importance on focusing on

the two factors „unexpected task‟ and „sequence‟ which both are requirements

that stand for a standard process diagram where each action happens

according to a given and predefined sequence.

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5.2 Simulation

Figure 5-5: Simulation Screenshot

The simulation is based on the process diagram version 2 and the results

from the questionnaire. Some information like the number of ingredients is on

the basis of the statistical result of the questionnaire and is defined as a

random value within a certain range. Each type of ingredients has a probability

to be selected. This probability will called selection probability. The simulation

was developed with JAVA and shows the complete process of the Mala Tang

window of Taoli refectory.

5.2.1 Time as Output

The simulation provided data for another DOE. We picked the values

which are randomized as new factors that influence the total serving time. The

factors are:

Factor A: Capacity of the basket

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“-“: all is set to 30

“+”: ingredients with high demand are set to 40, the others are set to 20

Factor B: Variance of Selection Probability

“-“: the variance of selecting different ingredients remains small

“+”: the variance of selecting different ingredients is high

Factor C: Ingredient Position

“-“: the probability of selecting ingredients which has a high or low distance to

each other is the same

“+”: the probability of selecting ingredients which are closer to each other is higher

Using data from simulation the different random seed, we get different

replication for our 23 factorial design. Figure 5-6, 5-7 and 5-8 are the results

Figure 5-6 General analysis results for simulation

25

Figure 5-7 Main effects plot

Figure 5-8: Interaction Plot

The plots show that the factor position has the highest contribution

towards the process time. The interaction and strong correlation of the factors

should be taken into account since synchronized their changes all result in a

higher process time.

26

However, p-value is too low, which implies that the unidentified block

factors affecting service time are too many. Hence we turned to another

indicator: number of finished orders.

5.2.2 Finished Orders as Output

Figure 5-9: Simulation DOE Results

Figure 5-10: Main Effects Plot

27

Figure 5-11: Interaction Plot

We can see that all 3 factors have strong positive correlation with number

of finished orders.

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6 Conclusion & Outlook

6-sigma was a useful method to identify the key factors of the service

process. It could have a great effect on improving the service time.

Using 6-sigma roadmap DMAIC, refectory in general can raise their

throughput and serve a higher number of customers than they do now which

means that they can greatly raise their effectiveness and efficiency.

The major conclusions we drew were:

1. Fewer branches in the process make lower service time

2. Standardization of the tasks, especially fixed task performing order and

fewer occurrences of unexpected tasks can give lower service time

3. The affection of position and proportion of ingredients is not significant

on average service time.

4. However, there is integrated optimization so that the total number of

finished orders in the given hours has a significant increase. In concrete, if

the most demand ingredients are put at front and give more resource like

capacity, total number of finished orders will increase. Moreover, the

increasing will become more significant as the demands for different

ingredients become more different.

It was not possible for us to match our defined goal. Though we think that

the reduction of time is possible, but we cannot predict the queue length and

therefore the waiting time since many factors are with the customer and the

variation is too high to promise a certain level of service speed.

Our report does not include a control stage. We thought that it is not

appropriate to use statistical control methods to see whether the service

process is working well or not. Since variation that comes from the customer

29

which has a great influence on the service time might lead to the conclusion

that the process time is too high, though all improvements were already

implemented.

Since the service quality is theoretically improved by 6-sigma more

customer requirements can be met, but not all. The service still has some

problems to deal with like the variety of customer group. The next step of

improvement would be to take the popular ingredients into account and make

re-arrangement of the ingredients according to their frequency of usage. By

this it is not guaranteed that every process will be accelerated but though the

average throughput-time will shortened and hence this will finally lead to a

smaller queuing time.

.

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Appendix A: Questionnaire

桃李园麻辣烫服务过程调查

本问卷用于 2008 年清华大学工业工程系质量管理研究生课大作业顾客情况调

查，不会用于任何商业用途及对您产生任何不良影响。谢谢您的支持。

下面是有关清华大学桃李园餐厅麻辣烫窗口服务过程的 8 个问题。请根据您自己的感觉填

写。

1. 您多长时间去桃李园吃一次麻辣烫？________________

2. 您一般是几点去吃？

中午

11:00 - 11:30

晚上

17:00 – 17:30

11:30 - 12:00 17:30 – 18:00

12:00 - 12:30 18:00 – 18:30

12:30 – 13:00 18:30 – 19:00

3. 您一般会点几个菜？________________

4. 在看到队伍大概多长的时候您会放弃排队？

A. 多长都要排

B. 队尾排到旁边第 3 个窗口

C. 队尾排到旁边第 2 个窗口

D. 队尾排到旁边的窗口

E. 只有很少人或没人排队时才考虑去看看

5. 您吃一次麻辣烫在队伍中等待的时间一般有多久？________________

6. 从点好菜到拿到做好的麻辣烫一般会等多久？________________

7. 您感觉吃一次麻辣烫的等待时间长吗？

A. 没感觉

B. 短点当然更好，但现在这样也能接受

C. 非常希望等的时间可以短点

D. 时间太长了，强烈要求缩短

8. 您个人认为桃李园麻辣烫的服务有什么可改进的地方吗？

31

Appendix B: DOE results

Replication 1

Factors Result

A B C Person 1 Person 2 Person 3

Mean time Perf. Seq. Time / s Perf. Seq. Time / s Perf. Seq. Time / s

+ + + 8 219.4 12 215.8 17 209.8 206.50

- + + 6 194.5 13 172.5 24 184.3 183.50

+ - + 4 178.5 15 173.4 21 178.2 187.23

- - + 3 191.7 16 181.8 18 185.2 186.23

+ + - 5 189.8 9 176.6 20 187.4 184.60

- + - 1 195.7 14 191.8 23 203.6 197.03

+ - - 2 174.6 11 178.6 22 180.3 179.13

- - - 7 185.4 10 168.4 19 175.2 179.37

Replication 2

Factors Result

A B C Person 1 Person 2 Person 3

Mean time Perf. Seq. Time / s Perf. Seq. Time / s Perf. Seq. Time / s

+ + + 41 216.3 32 214.3 33 190.5 207.03

- + + 44 204.6 29 204.2 40 189.4 199.40

+ - + 48 191.3 30 186.2 36 194.4 190.63

- - + 46 193.3 27 186 35 177.5 185.60

+ + - 42 201.9 28 189.1 39 184.9 191.97

- + - 43 192.3 31 186.3 37 188.7 189.10

+ - - 47 186.4 25 181.2 38 179.6 182.40

- - - 45 184.6 26 171.9 34 163.8 173.43

Replication 3

Factors Result

A B C Person 1 Person 2 Person 3

Mean time Perf. Seq. Time / s Perf. Seq. Time / s Perf. Seq. Time / s

+ + + 59 209.5 65 211.5 53 197.2 206.07

- + + 62 199.2 67 187.2 55 184.2 190.20

+ - + 64 182.2 68 196.7 54 179.7 186.20

- - + 60 186.5 69 179.4 52 171 178.97

+ + - 58 188.1 70 174.5 50 183 181.87

- + - 57 186.8 66 185.7 51 193.8 188.77

+ - - 61 168.6 72 171.8 49 176.3 172.23

- - - 63 172.7 71 184.5 56 167.9 175.03