application of 6-sigma for service improvement case study: mala tang nfor earnest koshi li ran shen,...
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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
3
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
4
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
5
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
6
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
7
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
8
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
9
Dissatisfaction
4%
43%
34%
19%
No
A little
Dissatisfied
Very angry
Measure – Questionnaire Survey (cont…)
10
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…)
11
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
12
Analyze – AHP Evaluation
.
13
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
20
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
21
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
22
Q & A
Thank You
Q & A
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