Modeling Tools to Support Navy Manpower Requirements Analysis

Briefing to RADM Harvey

4 September 2002

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Objectives of the Briefing

• Provide background on the use of modeling and simulation to forecast manpower requirements

• Present the advantages of manpower modeling approach over traditional approaches to manpower requirements

• Present three immediately available technologies that could be incorporated

• Discuss future development of modeling and simulation to augment NMRS

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Background on Modeling and Simulation for Manpower Requirements Analysis

• Industry has used modeling and simulation to evaluate manpower needs for several decades

• DoD began developing methods for modeling human systems in the 1970s

• Army MANPRINT program adopted modeling and simulation-based tools for determining operational manpower requirements in late 1980s/early 1990s– Accredited modeling as a basis for manpower requirements

analysis during design in 1995

• Navy began research in the use of modeling for manpower analysis in the 1990s

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Background on Modeling and Simulation for Manpower Requirements Analysis

• DD 21/(X) changed the landscape of the systems engineering process with respect to manpower modeling in the DoD– Manpower was a KPP– Manpower issues had to be tied to operational

consequences– DD 21/(X) was an SBA (simulation-based acquisition)– DD 21/(X) was a revolutionary system, so old approaches

(e.g., HARDMAN) would not work

Forecasting manpower requirements accurately, tracking them to system performance requirements, and doing it on a sound engineering basis was a necessity!

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Background on Modeling and Simulation for Manpower Requirements Analysis

• The manpower modeling ideas and technology from DD 21/(X) matured during several Navy R&D efforts– ONR Manning Affordability Initiative

• Watchstander Model– SEAIT/SMART3 – Total Crew Model

• The ideas and technology became a part of the systems engineering toolkit for other programs– Coast Guard Deepwater– JCC(X)– AEGIS Open Architecture– TSI approach to modernization

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Advantages of Modeling and Simulation for Manpower Requirements Determination

• Full traceability between mission and manpower requirements– “If we man to this level, we can expect this mission performance”

• Considers and evaluates the “peaks and valleys” of the need for manpower

• Straightforward ways to trade between at-sea and in-port workload concepts

• Transparent and understandable– Ability to trace manpower-induced problems to the source, and

identify the impact of possible solutions

• A solid link to systems engineering and design• Tools are available, mature, and low cost or free• Significant validation has already been conducted

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BMHTETDC2

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Mission duration

Num

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requ

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What Many Manpower Models Assume

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What Drives Manpower and Ship Performance

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BMHT

ETDC2

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Mission duration

Num

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Advantages of Modeling and Simulation for Manpower Requirements Determination

• Full traceability between mission and manpower requirements– “If we man to this level, we can expect this mission performance”

• Considers and evaluates the “peaks and valleys” of the need for manpower

• Straightforward ways to understand at-sea and in-port workload

• Transparent and understandable– Ability to trace manpower-induced problems to the source, and

identify the impact of possible solutions

• A solid link to systems engineering and design• Tools are available, mature, and low cost or free• Significant validation has already been conducted

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Proposed Improvements• Complement existing NMRS algorithms /

calculations data• Strengthen the PSMD development process• Provide meaningful trade space analysis for the

acquisition process• Ensure:

– CONSISTENTLY • Apply Navy Manpower and personnel policies• Apply uniform parameters and allowances• Combine Watch and Workload data

– UNIFORMLY• Translate workload drivers• Optimize requirements within specified

boundaries• Determine minimum skill and quality

• Reflects:• Scenario based wartime and peacetime missions • Warfare sponsor requirements (ROC/POE)

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Objectives of Manpower Modeling

• Provide quantitative metrics in a controlled simulation to support system engineering and trade space analysis

• Support manning optimization• Existing Tools

– Watchstander Model (WSM)• Detailed watchstander operations during dynamic scenario execution

– Total Crew Model (TCM)• Detailed crew activity and fatigue data

– SMART Build 3• Detailed maintenance and skill set data

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Tenets of Optimized Manning

• Maximize Crew Performance– Identify “Best” operator to perform task

• Reduce Workload– Technology Insertion– Process Re-engineering– Capability Change– Re-allocate from sea to shore

• Reduced Workload Does not Equate Directly to Eliminated Billets

– SMD Conditional Watches– Collateral Duties– Policy Requirements

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ainten

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• Req’d Admin

• Damage Control

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Underlying Approach: Task Network Modeling

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Watchstander Model (Cognitive-level)

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Watchstander Model• Model Explanation

– Micro-level, 1 second time slices

– Simultaneous mission execution

– Team definition and workload calculation

– System model with human as the focus

• Process– Task analysis– Build Task Flows– Allocate Sailor/Auto to task– Scenario– Run simulation– Analyze results

• Analysis Metrics– Workload

• Instantaneous < 100%• 3 minute running average

< 95%• 1 Hour running average <

80%, > 20%– Goal 65%

– No lost mission critical tasks

• Previous Projects– DD 21 / (X)– AMO– DEEPWATER– FORCEnet– DCPM (DC Personnel Model)– RSA

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• Use SME and system engineer inputs• Detailed workload analysis for watchstanders.

– CIC– Engineering– Damage Control– Bridge– Food Service

• Design tool for CS engineers.• Tests multiple design variants before committing.• Evaluates mission simultaneity • Provides empirical data identifying the relationships between

track density and crew workload.

Watchstander Model

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Demo

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Total Crew Model

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Total Crew Model• Rapid trade space analysis through

optimization of relevant outcomes asking “What if…” questions– Ship capabilities (can the crew perform all evolutions?)– Evaluate impact of system design changes on crew workload– Evaluate impact of ship’s schedule on crew fatigue– Evaluate resource availability on mission success– Target limited resources for best results– Training requirements for billets– Quality of life issues

• Personal time, work hours and type of work, sleep, meals

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Total Crew Model• Model Explanation

– Macro-level, 15 minute time slices

– Simultaneous event execution– Crew workload versus Navy

staffing standards– Test crew size against mission

execution– DDG 85 baseline WQ&SB &

ship class SMD working papers

• Process– Define evolutions/events– Define priority matrix– Build task flow – Assign sailors to evolutions– Randomize special events– Run simulation– Analyze results

• Analysis Metrics– Ships schedule– Mission accomplishment– Crew activity data

• Sleep = 8 hrs/day• Personal Time = 2.5 hrs/day• Meals = 1.5 hrs/day• Work = 12 hrs/day

– 81 hours weekly

– Fatigue

• Previous Projects– DEEPWATER– DD21 / (X)– FORCEnet– DCPM

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Total Crew Model Components• Daily Routine

– Watchstanders– Maintainers– Food Service– Admin– Schedules depend on current readiness condition.

• Crew Assignments (WQ&SB)– Assignment of billets to evolutions. (Resources sheet)– Rules defining personnel requirements for evolutions. (Logic

sheet)

• Trump Matrix– Contains all possible pair wise comparisons for task priorities.

• Scenario– Normal routine and authored recurring and infrequent evolutions.– Usually > 10 days to ensure compounded fatigue is captured.

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• Modeled as series of task networks • Each crewmember belongs to a home network

• Evolutions are scheduled in the model event queue to occur at a scripted times

• Evolutions use the WQ&SB and the trump matrix to select crew members

DailyRoutine

DailyRoutine

Watch Sections 1, 2, & 3

Day Schedules

Daily Routine & Evolution Scheduling

ScriptedEvolution Schedule

ScriptedEvolution Schedule

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• Crew members are designated for each evolution• Specific rules are given for selecting from several crew

members

• Each evolution & routine schedule event is compared to each other evolution for prioritization

• A trumping evolution must trump all scheduled tasks for crew member for the duration of the evolution

Sailor Assignment & Trump Matrix

WQ&SBWQ&SBChoose most rested HCO

Choose most rested HCO

Choose most rested LSO

Choose most rested LSO

TrumpingTask

EvolutionPriority Matrix

EvolutionPriority Matrix

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Fatigue Degradation Equation

Circadian ComponentCircadian Component

Combined DegradationCombined Degradation

Linear Awake Degradation&

Parabolic Sleep Recovery

Linear Awake Degradation&

Parabolic Sleep Recovery Awake AsleepAsleep

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WorkPersonal Needs Sleep

Total Crew Model Output Examples:Fatigue & Total Hours Breakdown

Blue Gold Rotation

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OS1

OS2

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Exhausted

Normal

• Micro sleep begins ~ 9 • Micro sleep increases in duration & frequency as fatigue climbs

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– Evolution Delays/Failures

Total Crew Model Mission Data– Successful Evolutions

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TCM Validation Effort• Phase I (to be conducted onboard USS Milius)

– Navy’s current optimal manning experiment (OME) DDG

– Test actual data against model predicted data• Mission schedule• Mission effectiveness• Crew assignments• Crew fatigue

• Phase II (to be conducted a non-experimental ship)– For further validation– Control

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SMART B3 Model• Model Explanation

– PM, CM – Based on equipment usage– FM, OUS – Scheduled (can be

deferred)– Stochastic Operational

Functions/Tasks– Function Task Skill Requirements– Job (Rank/Rating) skills and abilities

• Process– Define System Parameters

(Equipment, Compartments, Maintenance Actions)

– Scenario Development (GANTT Charting feature)

• Function/Task analysis• Build Task Flows

– Allocate job/auto to tasks– Run simulation/Analyze results

• Analysis Metrics– Skill Usage (average and over

time)– Crew Requirement– Utilization (average and over time)– Operational and Directed Manhour

Requirements– Maintenance Hit Matrix– Personnel Conflicts– Crew Composition– Cost Data

• Navy Projects– Currently being integrated with

Manpower Analysis and Prediction System (MAPS)

– Navy owned

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• Operational & Maintenance manpower• Focus on skills needed to perform tasks• Requirements based

–Driven from the bottom-up

–Assigned to jobs

• Apply iterative, “what-if” analytical approach

SMART Build 3 Features

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SMART B3 Challenge

• What is the BESTBEST crew composition for a new system?– Skills– Size– Cost

• Complications– Early answers required– Fast turn-around required– Range of missions and environments

Minimize cost Minimize crew size Minimize number of different jobs Minimize workload

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Building SMART B3 – The Pieces

Ship Manpower Analysis and Ship Manpower Analysis and Requirement Tools (SMART)Requirement Tools (SMART)

Working Together

Human Human Performance Performance

ModelingModeling

Skill and Ability Skill and Ability TaxonomyTaxonomy

To Evaluate New Acquisitions and Evolving Manning

Concepts for Legacy Ships

Existing ManpowerExisting ManpowerShip Data & Ship Data &

Maintenance ModelsMaintenance Models

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SMART B3 Skill Taxonomy

• Based on taxonomy work by Edwin A. Fleishman

• 50 different skills and abilities grouped into 8 different categories

• Scales anchored with behavioral examples

CommunicationVisualAuditoryConceptual

Speed-LoadedReasoningFine MotorGross Motor

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COMET Cost Data

PMSPreventive

MaintenanceData

SMDDirected

Manpower

FMWAPFacilities

Maintenance

JASSKSA Data

MAPSWatch Station &

‘High Driver’ Man-hourRequirements

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Sample Build 3 Results• Overall skill usage

– By run & job– 8 Major Categories

• Skill usage over time– View selected skills/abilities

(1-4) for any one job

• Crew Requirement– Comparison of number

personnel used to number available

• Utilization– Total & Over Time by Job

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Model Summary• Watchstander Model

– Micro-level design tool.– Detailed workload analysis for watchstanders.– Tests multiple design variants before committing.– Provides empirical data on low level task and function performance.

• Total Crew Model– Macro-level design tool.– High-level workload and crew activity analysis for entire ship’s crew.– Considers fatigue and crew resiliency/performance.– Identifies manpower resource drivers.– Provides empirical data identifying the relationships between manpower, scenarios, and

performance.

• SMART B3– Focus on mixing the jobs that the crew does to optimize different aspects of ship manning.– Includes sophisticated maintenance modeling capability.

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Model Interactions

TCM

WSMSMART3

jobsbillets?

task performance

reallocatetasks

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Modeling & Methodology Result Influences Total Ownership Cost

Technology/ Innovation

Effect on Functions

Crew Hypothesis:# & Skill Mix

•Development $•Procurement $•Installation $•Maintenance

•Labor•Spares, etc.

Other TSIT Analysis Total Ownership Cost

RDT&E

Acquisition

Life Cycle

Operations & Support

Design and Construction

•Indirect Manpower•Other Personnel/ Infrastructure

•Personnel $•Training $

Manpower Modeling

and Associated

Analysis

•Number of Crew

•Skill Rqmt•Etc.

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Advantages of Modeling and Simulation for Manpower Requirements Determination

• Full traceability between mission and manpower requirements– “If we man to this level, we can expect this mission performance”

• Considers and evaluates the “peaks and valleys” of the need for manpower

• Straightforward ways to trade between at-sea and in-port workload concepts

• Transparent and understandable– Ability to trace manpower-induced problems to the source, and identify

the impact of possible solutions

• A solid link to systems engineering and design• Tools are available and mature• Significant validation has already been conducted