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Defence Research andDevelopment Canada

Recherche et développementpour la défense Canada Canada

Training Pipeline Modelling Using the Production Management Tool

20 March 2009

Prepared by: Ms. Michelle StraverPresented by: Mr. Paul Bender

Director General Military Personnel Research & Analysis

Defence R&D Canada – CORA • R & D pour la défense Canada – CARO

Outline

• introduction

• case study

– modelling process

– sample results

• future work


What is the Production Management Tool (PMT)?

• simulation tool that can be used for:

– viewing and analyzing the current and future state of a training pipeline

– identifying existing or arising scheduling problems (i.e. bottlenecks, empty seats, etc.)

• conducting “what if?” testing by changing pipeline parameters (e.g. course capacities, number or timing of serials, streaming, intake, etc.)


What is the Production Management Tool (PMT)?

• three major components:

– Arena model

• event-driven simulation model

• generic (can be used for any CF occupation)

– database

• contains the information required by the simulation (basic scenario parameters, information on course flow, entry plans and courses, course serials, and personnel)

• after running, contains text file with output results

• includes extensive set of queries for analyzing results

– Graphical User Interface (GUI)

• used for entering data, generating charts and reports


Top-Level View of Arena Model


ANAV Test Case

• Step 1: Gather Information

• Step 2: Generate Credit Matrix

• Step 3: Clean Data

• Step 4: Set Up Scenario in GUI and Run

• Step 5: Analyze Data


Step 1: Gather Information (with SME support)

• develop training pipeline

– establish course flow from recruitment to graduation for each possible entry plan

• obtain current pipeline status

– past, current, and planned course schedules

– course history for each student

– most data can be imported from the Military Individual Training & Education (MITE) database extract

• determine whether course failure results in re-course or transfer out of occupation

• determine overall attrition rate


ANAV Training PipelineCFR

DEOCEOTP

UTPNCM

COR (pilot)

OTBOTP

AMT

Sea Surv

BSERE

BANCCP-140 N/C

CC-130 Nav

CH-124 TCO

BOTP

CP-140 ASO

ROTP RMC

SLT

(if req’d)

BOTP

IAP

COR (unrelated)

ROTP CIV

Civ Univ

IAP


Step 2: Generate Credit Matrix

• completing a course gives a specified number of credits (0 to 1) toward eligibility for other courses

• student is eligible for a course when he/she earns a total of 1.0 credits for that course

• alternatively, students can be streamed into one of a set of courses according to specified proportions


Step 3: Clean Data

• MITE Extract contains several data tables

– OP_COURSE_TBL

• general high-level details for each course

– OP_CRSE_SESSN_TBL

• details for every course serial, e.g. start/end dates, min/max capacity

– OP_TRAINING

• course/serial registration and attendance results for each student

– POPULATION

• each student’s Service Number, name, rank, hire date, occupation, entry plan


Data Cleaning Issues – Examples

• adjust serial capacity (OP_CRSE_SESSN_TBL)

– change min capacity to 1 for courses that are shared with other occupations

• update course codes and serials (OP_TRAINING)

– course will not be recognized if individual took it under earlier code

• validate/update entry plans (POPULATION)

– often unknown or named differently in MITE Extract; OT/COR is never indicated

– check each individual’s course history to infer entry plan and update if required


Step 4-1: Enter Scenario Information


Step 4-2: Enter Course Information


Step 4-3: Import or Enter Serial Data


Step 4-4: Import or Enter Population Data


Step 4-5: Run Scenario


Step 5: Analyze Data

• many types of charts and reports can be produced easily by the user at the course, serial, or person level

• time period for analysis can be selected by user so that different time segments of the simulation can be compared

• the charts shown in the following slides represent a five year period beginning on the simulation start date (14 Feb 2008)


5

6 6 6 6

4 4 4 4

2

8 8

7

8

4

9 9

8

9

8

0

1

2

3

4

5

6

7

8

9

10

08/09 09/10 10/11 11/12 12/13

Fiscal Year

Nu

mb

er

of

Ind

ivid

ua

ls

CH-124 TCO CP-140 N/C CP-140 ASO CC-130 Nav

Graduates by Fiscal Year


Demand and Attendance Ratios Relative to Capacity

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

IAP

BO

TP

SLT

RM

C

CIV

UN

IV

AM

T

SE

A S

UR

V

BS

ER

E

BA

NC

CH

-124

TC

O

CP

-140

N/C

CP

-140

AS

O

CC

-130

Nav

Rat

io w

.r.t

Cap

acity

Demand Attendace Capacity


Demand and Attendance for the BANC

0

5

10

15

20

25

30

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Serial Date

Nu

mb

er o

f In

div

idu

als

Demand Attendance Min Cap Max Cap


Person Gantt Chart

1-J

an

-07

1-J

an

-08

1-J

an

-09

1-J

an

-10

1-J

an

-11

DEO (Entry Plan)

IAP

BOTP

AMT

BSERE

SEA SURV

BANC

CC-130 Nav

Date

Wait Attend Sim. Wait Sim. Attend


Future Work

• case study for multiple related occupations

– e.g. ANAV and pilots

• probability-based recourse/transfer on fail

• add flexibility to attrition parameter

• improve handling of entry plans

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Documents

dfense canada caro step

defence rd canada cora

dfense canada caro demand

dfense canada caro graduates

course information slide

capacity slide

scenario slide

course op