Range Clearance Production Function Estimation for

Explosive Ordnance Disposal

Dr. Brice Stone, Mr. Jonathan Fast

and Mr. Gary Grimes

Metrica, Inc.

November 1999

2

Overview

• Objective

• Methodological Approach– Objective Data– Survey Data

• Survey Results

• Model Development

• Interpretation of Modeling and Analysis

3

Research Objective

Determine manpower requirementsfor EOD personnel to perform

explosives decontaminationand thermal treatment

on Air Force Weapons and Training Ranges

4

Methodological Approach

• Survey based approach

• Objective data - Form 3578

• Combined use of survey and objective data– Developing supplemental data for analysis– Verification/Validation of objective data

5

Modeling Range Cleaning

• Range cleaning as a production function

• Single equation model– Man hours– Density function

• Simultaneous system– Acres cleaned– Tonnage– Quantity of nomenclature

6

Key Data Elements

• Man hours

• Acres cleared

• Type of terrain and/or weather or seasons– Desert– Mountains– Marshy, swamps– Brush

7

Key Data Elements (Cont’d.)

• Type of clearance– 50 use day– annual– 5 year

• Year of occurrence and season

• Density of ordnance (tonnage)

8

Key Data Elements (Cont’d.)

• Types and quantity of ordnance removed– Small arms ammunition– Practice bombs– Bombs– Cluster bombs– Rockets– Missiles– Grenades

9

Survey Structure

• Paper and pencil

• Questions concerning range cleaning tasks and manpower used

• Bases surveyed

• Responses rates

10

Ranges/Bases Surveyed

BaseNumber ofResponses

Barksdale 1Cannon 1Dover 1Edwards 1Eglin 15Eielson 3Hill 7Holloman 3Kadena 2Luke 7McConnell 1Mount Home 2Nellis 63Osan 2Seymour Johnson 2Shaw 1Spangdahlem,Germany 1

Total Surveys 113

11

Size of Ranges by Base

Base Smallest Largest Average AcresBarksdale - - 672Cannon - - Not ProvidedDover - - 9,416Edwards - - 92,160Eglin 320 16,000 3,439Eielson 22,880 160,600 77,160Hill 126 14,080 5,932Holloman 5,000 17,000 59,000Kadena 10 40 25Luke 30,535 116,444 66,506McConnell - - 34,000Mount Home - - 110,000Nellis 31 1,506,622 244,400Osan - - 45Seymour Johnson 46,421 46,621 46,521Shaw - - 13,600Spangdahlem,Germany

- - 676

Across Surveys 10 1,506,622 155,688

12

Types of Clearance by Base

Base/Range50 Use

Day

Annual orPartial

Five Year Five YearBarksdale 1 1 N/ACannon 1 N/A 1Dover 1 1 1Edwards 1 N/A 1Eglin N/A 7 N/AEielson N/A 3 N/AHill 1 7 5Holloman 1 3 N/AKadena N/A 2 N/ALuke 4 7 4McConnell N/A 1 1Mount Home 1 1 N/ANellis 8 9 N/AOsan 1 1 N/ASeymourJohnson 1 1 1Shaw 1 1 1Spangdahlem, Germany 1 1 1Across Bases 23 46 16

13

Compensating for “Lost Time”

Base

ApplyGreaterEffort

with theExisting

Team

AddManpower

to theFieldedTeam

Coordinateand Extend

theScheduledNumber of

Days

Focus onCritical Areasand Defer theRemainder tothe Next Cycle

Barksdale 0 0 100 0Cannon N/A N/A 50 50Dover 100 0 50 50Edwards 0 0 0 0Eglin 30.5 27.5 26.3 22.1Eielson 70 0 13.3 16.7Hill 84.3 2.1 2.1 17.1Holloman 0 0 0 50Kadena 50 N/A N/A 50Luke 100 2.8 0 5.7McConnell 20 0 5 75Mount Home 33 33 0 33Nellis 90.9 40 0 82.6Osan N/A N/A N/A 100Seymour Johnson 0 35 0 65Shaw 25 0 50 25Spangdahlem,Germany

N/A N/A N/A N/A

Across Bases 74.6 17.2 13.7 48.6

14

Means for EOD Personnel Used, Duration of Clearance and Acres Cleared by Base

Base/Range

Number ofEOD

Personnel

Number ofAcres

Cleared

Duration(Hours) ofClearance

Barksdale 6 672 40Cannon 12 20,010 26.1Dover 5.3 3,230 280Edwards 10 35 5.3Eglin 8.6 190 76.9Eielson 14.3 2,767 1,866.7Hill 15.5 8,003 85.4Holloman 3.8 17,125 92.5Kadena 7 15 140Luke 12.9 8,101 548.5McConnell 17.5 23,440 120Mount Home 12 55,027 9Nellis 12.7 39,909 139.6Osan 6 40 8SeymourJohnson

4.5 279 29

Shaw 10.3 8,355 410Spangdahlem, Germany 5 261 118.7Across Bases 11.1 13,604 250.3

15

Acres Per Man Hour for Annual Clearances by Base

Survey(1998)

AF Form 3578(1992-1995)

BaseAcres Per ManHour – Mean

Number ofObservations

Acres Per ManHour - Mean

Number ofObservations*

Barksdale 2.80 1 1.17 1Cannon 0.04 1 0.58 2Dover N/A N/A N/A N/AEdwards N/A N/A N/A N/AEglin 0.22 5 2.20 6Eielson 1.02 3 N/A N/AHill 7.90 6 9.92 15Holloman 39.32 3 6.22 5Kadena 0.03 2 N/A N/ALuke 2.88 7 4.22 28McConnell 6.44 1 N/A N/AMount Home 55.00 1 6.36 3Nellis 22.31** 9 5.28** 7Osan 0.16 1 N/A N/ASeymourJohnson 39.13 1 N/A N/AShaw 1.67 1 2.79 2Spangdahlem,Germany 0.23 1 N/A N/AAcross Bases 11.53** 43 4.70** 85

16

Acres Per Man Hour for Five Year Clearances by Base

Survey AF Form 3578

BaseAcres Per ManHour – Mean

Number ofObservations

Acres Per ManHour - Mean

Number ofObservations*

Barksdale N/A N/A 1.01 2Cannon 53.33 1 125.00 1Dover 15.02 1 N/A N/AEdwards N/A N/A N/A N/AEglin N/A N/A N/A N/AEielson N/A N/A 0.65 1Hill 5.84 5 30.07 4Holloman N/A N/A N/A N/AKadena N/A N/A N/A N/ALuke 11.03 3 14.62 11McConnell 8.50 1 N/A N/AMount Home N/A N/A N/A N/ANellis N/A N/A 12.32 5Osan N/A N/A N/A N/ASeymourJohnson 1.67 1 2.79 2Shaw 13.91 1 7.73 1Spangdahlem,Germany 1.88 1Across Bases 11.19 14 16.04 31

17

Acres Per Man Hour for 50 Day Use Clearances by Base

Survey AF Form 3578

BaseAcres Per ManHour – Mean

Number ofObservations

Acres Per ManHour - Mean

Number ofObservations*

Barksdale 2.80 1 1.71 7Cannon 0.03 1 N/A N/ADover 0.60 1 N/A N/AEdwards 5.12 1 1.24 1Eglin N/A N/A N/A N/AEielson N/A N/A N/A N/AHill 0.12 1 0.25 4Holloman 14.83 1 N/A N/AKadena N/A N/A N/A N/ALuke 0.10** 4 0.60** 71McConnell N/A N/A N/A N/AMount Home 0.05 1 N/A N/ANellis 0.06** 6 11.72** 2Osan 3.09 1 N/A N/ASeymourJohnson 0.20 1 N/A N/AShaw 0.43 1 N/A N/ASpangdahlem,Germany 0.47 1 N/A N/AAcross Bases 1.36 21 0.93 87

18

Model Results

• Simultaneous system– Man Hours statistically significant for all three

outputs (9.5215 acres per man hour)

• Single equation (reduced form)– Man Hours statistically significant (9.4173)– Tonnage and Quantity of Ordnance statistically

significant

19

Model Results (Cont’d.)

• Other factors– Type of clearance– Tonnage– Type and quantity of ordnance

• Consistent results for man hour production regardless of approach

20

Simultaneous Equation Results for Acres Cleared

Confidence IntervalVariable Coefficient T-Statistic Lower Bound Upper Bound

Tonnage per Mh 0.0577 5.3560 0.0365 0.0789Acres Cleared perMh 9.5215 8.1980 7.2378 11.8053Quantity ofSpecific Ordnanceper Mh 1.3231 3.9860 0.6705 1.9757

21

Single Equation Results for Acres Cleared

Variable Coefficient T-value Significance LevelTonnage 23.76637 1.655 0.103Quantity

ofOrdnance

-1.60256 -2.413 0.019

ManHours

9.417378 3.466 0.001

22

Acres per Man Hour, Historical Data, AF Form 3578

0

5

10

15

20

25

1992 1993 1994 1995 1996 1997

Year

Acres/ManHr

50 Day UseAnnual5 YearAverage

23

Acres per Man Hour, AF Form 3578 Compared to Survey Data

Year/Type ofClearance 1992 1993 1994 1995 1996 1997 Average Survey

50 Day Use 0.4578 0.6694 0.6639 1.7789 0.9862 1.3417 0.9830 1.3563Annual 6.1581 3.2856 5.6732 3.5551 8.8274 16.7152 7.3691 11.53445 Year 17.7168 10.1158 5.5310 22.068 7.0047 19.6743 13.6851 11.9184Total 7.1106 2.7881 2.2349 5.8141 7.8478 10.3041 6.0166 8.8234

24

Implication of Estimated Model

• Assume 10,000 acres - annual clean

• Implies – Crew of nearly 9 people

• 7 - low• 11 - high

– Working 40 hours per week– 3 week job

25

Implication of Estimated Model (Cont’d.)

• 5 year clearance – Adds at approximately one more person– Caveat: Usually includes doubling of acres

cleared

26

Interpretation of Modeling and Analysis

• Manpower requirements for range clearances vary significantly by type of clearance, acres cleared and type of explosive ordnance cleared

• Manpower requirements for range clearances vary by base

• Decreasing trend in manpower usage for range clearances