Final Model 5-1

1

False

De te rm in e Ca l l Ty p e

Else

76

16

e n t i ty ty p eT e c h n i c a l Ca l l

As s i g n

Re c o rd in g De la y

Te c h n ic a l Ca l l

Ty pe

De te rm in e Pro d uc t

Else

25

34

Ca l lT y p e 1 T e c h

Pro c e s s Pro d u c t

Ca l lT y p e 2 T e c h

Pro c e s s Pro d u c t

Ca l lT y p e 3 T e c h

Pro c e s s Pro d u c t

En t i ty T y p eAs s i g n Sa l e Ca l l

Ca l lPro c e s s Sa l e

T y p eSta tu s e n ti tyAs s i g n Ord e r

s ta tu s c a l l

d e lay fo r o rd e r

re q u i re d ?

No s a le s pe rs o n Tr ue

False

Ca l l Pri o ri tySe t o rd e r Sta tu s

Sa les p e rs o n

Ca l l s ie z es

s a les p e rs o n

wi th

c o nv e rs a tio n

o rd e r s ta tus

s a les p e rs o n

re lea s e s

o rd e r s ta us c a l l s

L in e

Re lea s e Tru n kCo m p le te d Ca l l s

Re c o rde n t i ty

Di s p o s e o f c a l l

Calls Arrive

Tech Support Calls

Sales Calls

Order Status Calls

Se iz e Tru nk L in e De lay

In i tia l re c o rd in g

c re a te c a l l a rri v a l sAttem p te d Ca l l

Re c o rdTru nk L in e Av a i la b le ?

Tr ue

Ca l ls

Re c o rd Rjec te d

Ca l l sDi s p o s e Re j e c te d

0

0

0

0

0

0

0

0

0

0

Model 5-2: Enhanced Call Center Changes

• In developing models for real systems, you want to

capture the system’s behavior accurately. Although our

current model would allow us to capture real system

behavior, it's lack a lot of details.

• Let’s start with more detailed examination of call arrivals.

The call-arrival rate to this system accurately varies over

the course of the day according to non-stationary poison

process. So we collect data expressed in calls per hour

for each 30 minutes period during the opening hours of

the system.

2

1)Incoming calls’ arrival rate varies over day

– Probabilistic model – Nonstationary Poisson process

– Instead of defining a constant rate (= 1 / mean

interarrival time), we will define an Arrival Schedule

The call arrival rates are given in the following table:

3

Model 5-2: Enhanced Call Center Changes

4

Model 5-2: Enhanced Call Center

Changes

Define nonstationary arrival-

rate function in Schedule module – Arrival Schedule

Although our initial model assuming constant staffing levels

for our sales and technical support areas , the staffing level

actually varies over the day.

2)Sales-staff size varies over day

There are six people with the following staggered daily

schedules:

Number of people @ time period in minutes:

1@60,3@60,4@90,5@60,6@60,5@90,6@90,5@30,3@60

,2@60

Data in text, Schedule data module, Sales Schedule

Model 5-2: Enhanced Call Center

Changes

2)Sales-staff size varies over day

6

3) Tech-support staff are partially cross-

trained• Tech-support staff work on 8-hour day with 30 minutes

off for lunch break (lunch is not included in the 8 hours).

• There are 11 technical support employees whose work

schedule along with the product types they can handle

are shown below:

7

3)Tech-support staff are partially cross-

trained

– Resource set for each tech-support product type

• Members are those tech-support resources qualified

• Individual resources already defined – Resource data module

• Overlapping membership – some resources in multiple sets

• Sets are ordered – here, put most versatile tech-support people at bottom, to “save” them for other calls ... Preferred Order in Seize

• Will Seize from a set in model

8

9

3) Tech-support staff are partially cross-

trained

Will use Arena

Sets concept to

implement this

cross training

Sets – collect same-type items together

Set, Advanced Set data modules (Basic, Advanced Process panels, resp.)Refer to items in set by original name, or index (subscript) in set

10

3) Tech-support staff are partially cross-

trained

Define in Set that for Product 1 we have five employees

Define the schedule for each employee separately

• Define in Set that for Product 2 we have five employees

11

3) Tech-support staff are partially cross-

trained

12

3) Tech-support staff are partially cross-

trained

Define in Set that for Product 3 we have six employees

• Basically all products have the same name of save attribute which is “Tech Agent Index” because the

eleven employees have skills to perform one or more

than one type of the three products.

13

3) Tech-support staff are partially cross-

trained