This is a short slide presentation of my assignment in course of System thinking and modeling. I used Arena Simulation software as tool to discover and make improvements in dental clinic service.

1. Business Process Simulation
Project : Dental Clinic service
(Tool: Arena Simulation Software)
Mr. Sok kimseng

2. Problem Description
Dental clinic manager wants to fire a few staffs because he observed that the
resource (dentists and dental assistant) is over capacity requirement. And also, he wants
To cut expense of labor cost. However, he still want to provide the best
quality of treatment, services, and the lowest price for overall patients both
local and international. So he wants to know the effect of cutting the number
of dentist or dental assistants. The Bright Smile dental clinic:
 Personnel: three dentists (Two are active employees and One is part-time
employee), four dental assistants, one receptionist, and one secretary.
 Machine Capacity: the clinic equipped with one x-ray machine, one intraoral
radiographs unit, and one extra-oral panoramic radiographs unit for providing oral
healthcare service to patients.

3. Question and KPIs
Questions: Does it effect to patients number out or service quality
if dental clinic manager wants to fire one dental assistant and one part-time
dentist? The main objective of this project is to study staffing modification by
modifying the number of resource so that manager can determine the impact
of this modification on the performance metrics of the dental clinic in delivery
oral healthcare service by using Arena simulation software.
KPIs: We have to measure some performance metrics such as:
a. The rejected percent when dentists are not available for providing service to
the patients
b. The patient total time in system (dental clinic) for first and return patients
c. Resource Utilization (Personnel and dental chair)

4. Dental Clinic Layout
South
North
WestEast
CRE
Waiting Room
IN Treat 2
CDR
TR
CO
D&P Treat 3
Treat 1
Treat 5
Treat 6
Treat 4

5. Data Input
 Entity: Patients (First and Return Patients)
Process:
 Queue: FIFO
 Resource
Process ID Process Resource ID
Process time
(minutes)
Interarrival of patients NORM(43.7,14.1)
CRE Check-in with receiptionist RE TRIA(2,3,4)
CDR Check-in for first visit with dentist DR and DC TRIA(10,12,15)
CDR Check-in for return visit with dentist DR and DC TRIA(3,5,8)
TR Taking radiograph DA TRIA(3,4,5)
IN Oral Health Instruction DA TRIA(10,15,20)
D&P Diagnosis & Planning DR and DC TRIA(2,4,10)
Treat 1 Filling treatment DR, DA and DC TRIA(30,40,50)
Treat 2 Sealing treatment DR, DA and DC TRIA(20,30,40)
Treat 3 Cleaning treatment DR, DA and DC TRIA(20,30,40)
Treat 4 Crown treatment DR, DA and DC TRIA(45,60,70)
Treat 5 Extraction treatment DR, DA and DC TRIA(30,45,60)
Treat 6 Check-up DR, DA and DC TRIA(5,10,15)
CO Check-out for first visit RE TRIA(5,8,12)
CO Check-out for return visit RE TRIA(1,2,3)
Resource ID Resoruce Capacity
DR Dentist 3
DA Dental Assistant 4
RE Receptionist 1
DC Dental Chair 2

6. Conceptual Flow
Check-in
Meet dentist
Meet dental
assistant
Meet dentist and dental assistant to
do preventive and corrective dental
treatment
Patients
Arrive
Patients leave or
return to clinic again
based
- Dental assessment,
- Diagnosis & planning
-Take radiograph (If
needed)
- Oral health instruction

7. Conceptual Model
Patient
s
Arrival
First
Visit
Return
Visit
CDR
TR
D&R
IN
Treat 1
Treat 3
Treat 6
Treat 5
Treat 4
CO
40%
60%
30%
15%
55%
30%
15%
15%
10%
20%
NORM(43.7,14.1) First Visit: TRIA(10,12,15)
Return Visit: TRIA(3,5,8)
TRIA(3,4,5) TRIA(10,15,20)
TRIA(2,4,10)
TRIA(30,40,50)
TRIA(20,30,40)
TRIA(45,60,70)
TRIA(30,45,60)
TRIA(5,10,15)
Treat 2
TRIA(20,30,45)
CRE
TRIA(2,3,4)
10%
Patients
Leave
First Visit: TRIA(5,10,15)
Return Visit: TRIA(1,2,3)
First Visit
Time in
system
Return Visit
Time in
system
First Visit
number
Return
Visit
number
RE=1
DR=1,DC=1
DA=1
DA=1
DR=1,DC=1
DR=1,DA=1, DC=1
RE=1

8. ARENA Model

9. Run Setup Replication Percent rejected
1 26.666
2 18.75
3 23.529
4 25
5 29.411
6 29.411
7 15.374
8 6.666
9 25
10 35.294
Sample Mean 23.5101
Sample standard deviation 7.716732384
95% Confidence Interval Half Width 5.519834287
Minimum Summary output value 6.666
Maximum Summary output value 35.294
Error in the point estimate 23.47%
Desired value h 2
First approximation 57.18985953
Second approximation 76.17142639
 Simulation run time:
 Terminating
simulation
(TNOW > 600 && Total
WIP == 0)
 Number of replication
 Based on
statistical analysis,
number of replication
should be 80 times.

10. Evaluating scenarios with PAN

11. Discussion
 Percent rejected: According to box and whisker plot with error tolerance 10%, the
percent rejected of scenario 10, scenario 14, and scenario 18 are 11.12%, the same
level.

12. Discussion
 Resources: According to the table below, the scenario 18 is the best in term of
number of resource usage and resource utilization in the clinic.Resource
Utilization
DA DC DR
Scenario
10
0.44
7
0.25 0.59
7
Scenario
14
0.44
7
0.33
7
0.59
7
Scenario
18
0.44
7
0.50 0.59
7Resources DA DC DR
Scenario
10
2 4 4
Scenario
14
2 3 4
Scenario
18
2 2 4

13. Discussion
 Average total time in the clinic:
The average total time in dental clinic system is the same in scenario 10, 14, and 18.
 Total time in system for first visit patient is 75.821minutes.
 Total time in system for return visit patient is 59.621 minutes.

14. Conclusion
Regarding to the question and discussion, we conclude and recommend as
following:
 Scenario 18 is the best.
 Dental clinic manager could not fire dentist if he considers about the percent
rejected or service level.
 In contrast, the manager should hire one more dentist so that the percent
rejected will be reduced from 25.51% to 11.120% an well as the average total
time in the clinic will be reduced from 93.202 minutes to 75.821 minutes for
first visit patients and from 77.908 minutes to 59.621minutes for return visit
patients.
 On the other hand, the resource utilization of dental assistant is low (only
18.6%). we also recommend that dental assistants should be reallocated and
assigned to other tasks in case of manager doesn’t want to fire them. We
can add more tasks for them in order to use this resource efficiently.

15. Thank you!!!