NNSA Infrastructure Initiatives

BUILDER and MDI

Jeff Underwood

Office of Infrastructure and Capital Planning

March 25, 2014

NA-OO Strategic Objectives

• Arrest the declining state of NNSA infrastructure• Build an operating model that is repeatable,

predictable, transparent, effective and efficient.• Drive NNSA towards a positive performance

culture with safe operations• Implement cutting-edge sustainable

infrastructure management practices• Manage risk and employ innovative solutions

BLUF

Ability to “see” conditions via uniform lens across all NNSA sites Ability to understand and to project risk at various funding levels Data required at enterprise level, sites can use BUILDER for

original assessments or can pass data into BUILDER from existing systems.

Enterprise level “real time” data to monitor program execution. A National Academy of Science recommended way to

communicate the condition of real property to key stakeholders, adopted by the DoD and being adopted by other agencies, including DNI, FBI, and the Smithsonian.

More efficient use of limited site resources.

BLUF

Ability to “see” conditions via uniform lens across all NNSA sites Ability to understand and to project risk at various funding levels Data required at enterprise level, sites can use BUILDER for

original assessments or can pass data into BUILDER from existing systems.

Enterprise level “real time” data to monitor program execution. A National Academy of Science recommended way to

communicate the condition of real property to key stakeholders, adopted by the DoD and being adopted by other agencies, including DNI, FBI, and the Smithsonian.

More efficient use of limited site resources.

Inventory

• Real Property Inventory

• Component Inventory

Assessment

• Condition Assessment

• Functionality Assessment

Prediction

• CI Prediction

Work Planning

• Work Generation

• Work Prioritization

Forecasting

• Course of Action (COA) Analysis

Process

Inventory

Import from FIMS and site systems. Supports tactical actions (e.g. replace roof, repair doors, replace

HVAC, etc.) Group assets for lifecycle investment management, reduces

assessment requirements Immediately supports asset performance predictions

Section

Component

System

Building Facility

(B20) Exterior Closure

(B2010) Walls

Masonry Metal Panel Curtain Wall

(B2020) Doors

(D30) Services

(D3020) Heating

Boiler(s)

Example Building Hierarchy

Capture the lifecycle rating of an asset to inform risk-based decisions

► Performance Requirements may change, butmeasurement should be constant

► Inspectors are “human sensor” and do not provide opinion/interpretation

► Models the rating given by an expert based uponengineering principles for consistency across an organization

► Assessment frequency and level-of-detail are tailored to mission risk and lifecycle condition (Knowledge Based Inspections)

► Import legacy deficiencies from existing software for IOC, round out with assessment of other systems after IOC.

Navy has recognized 75% savings over their previous assessment program.

Condition Assessment

Condition Prediction

1990 1995 2000 2005 2010 20202015Year

60

20

80

40

100

Ass

et

Co

nd

itio

n

In

de

x

Design Life = 20 yrs.

Condition @ Failure

“Real” Service Life = 17 years

Inspection 1Inspection 2

Inspection 3

Adaptive model predicts performance of each unique asset; identifies best time to invest

Construction/Installation

“Economic Sweet Spot”

0

Modernization inspection addresses issues of:► Capacity (too little or too much)► Configuration► Change in user requirements► Technical obsolescence► Regulatory/code compliance► Etc.

Available at building, space, and component levels Can simulate mission change to determine investment requirements for future occupants

Functionality Assessment

Work is automatically created based upon Enterprise-defined rules that capture acceptable levels of risk for differing assets

System evaluates work options to optimize Return on Investment Work is generated using objective ratings AND a defensible set of

enterprise policies, eliminating subjective judgment and gaming of the system.

Enterprise-defined rules generate consistent requirements Service- wide

Work (Requirements) Generation

Work Generation

1990 1995 2000 2005 2010 20202015Year

60

20

80

40

100

CI

Work requirements are automatically generated when condition falls below enterprise policy levels.

SL Gain

CI Gain

0

HVAC (70)

Interior Construction (55)

Repair

Repair

Balance multiple, competing criteria for determination of the best enterprise infrastructure investment strategy

► Tool includes metrics which express [cost] effectiveness, risk, and consequence factors

► Program override available for must-do items

Uniform prioritization of requirements across organization enforces consistent investment guidance.

Requirements Prioritization

Actionable Work Plan

Work is for specific assets; establishestransparency, traceability and

accountability

2010

2010

2010

BUILDER-derived value is more consistent and repeatable than deficiency-based methods

►Work is now generated using objective ratings AND an defensible set of enterprise policies, rather than subjective judgment

►Prioritization scheme can leverage metrics to focus resources on greatest need.

CI computation is based upon objective assessment methods and consistent work rules.

Condition Index (CI)

What-If capability allows changing inventory, policies, prioritization, funding, and forecast period to determine different outcomes. Supports: Budget Creation Budget Defense Course Of Action Analysis Out-year strategic condition trends

► Will levels meet current mission requirements?► Will levels meet future mission requirements?

Actionable intelligence built from the asset up

Forecasting

Forecasting Results

Failure

High Risk

FunctioningHVAC

Electrical

Roofing

Impact on Systems of Funding 50% of Requirement

2012 2013 2014 2015 2016

$200,000,000

$220,000,000

$240,000,000

$260,000,000

$280,000,000

$300,000,000

$320,000,000

$340,000,000

57

58

59

60

61

62

Impact on Portfolio of Funding at 90%, 70% and 50% of the Re-quirement

Deferred Maint. - 90% of Rqmt.

Deferred Maint. - 70% of Rqmt.

Deferred Maint. - 50% of Rqmt.

FCI - 90% Funding

FCI - 70% Funding

FCI - 50% Funding

Fu

nd

ing

in M

illio

ns

($)

Fac

ility

Co

nd

itio

n In

dex

Benefits Over Today

Reduced assessment costsAvoidance of missed opportunity costsAvoidance of stale information costsAdaptability to additional assessment protocolsSustained product improvements through R&DNo product licensing costs (Federally owned)

Take Aways

BUILDER provides consistent, objective, efficient decision support and reporting on facility conditions and investment requirements from the site to the enterprise level

NNSA is following DoD’s and adopting BUILDER as standardized condition assessment process and tool for all components

USACE is supporting implementation efforts for many DoD agencies.

Mission Dependency Index

(MDI)

at a Glance

New Metric

Basic Parameters and Calculations

“A” Matrix

Q1

Q2 “B” Matrix

Q3

Q4“N” Interdependencies

MDI = (16.5(A + (1/8) Bavg + 0.1lnN)-15.5

Answers to Q1 and Q3 select a column within the A and B matrices (typically 4x4). Answers to Q2 an Q4 select rows; a11 and b11 have highest consequence and greatest difficulty to replace.

A = Matrix element chosen by Q1 and Q2 in A Matrix.

Bavg = Average of matrix elements chosen by Q3 and Q4 in the B Matrix for each of N different interdependent assets.

16.5 and 15.5 normalize to 100 max and 1 min values for the 4x4 matrix with a11 and b11 equal to 7 and each element differing from its neighbors by 1. 1/8 and 0.1 lnN are empirical and can be adjusted to fit the user’s intuitive importance of interdependencies.

Key Concepts

MDI is based on the functionality (useful purposes) provided by the asset, not the asset itself. This focuses on why the asset is useful and not on the asset itself.

Restoration of the functionality provided by an asset is not necessarily the same as restoration of the asset.

Loss of functionality has a consequence for mission, assessed separately from the consequences of an accident or other unplanned event that might cause a loss of functionality. Answering Question Q1 captures the severity of the consequence of a loss of the asset’s functionality.

Restoration of functionality requires overcoming a level of difficulty. Answering Question Q2 captures the difficulty of restoring the functionality of an asset.

Some asset functionalities affect the functionality of other assets. Answering Q3 & Q4 capture the consequences and difficulties, similar to Q1 and Q2, for the asset.

MDI is calculated from the consequence of loss of functionality and the difficulty of restoration of functionality, adjusted for asset interdependency.

Take Aways

• Answers the question, “ How much risk am I accepting on the facilities most essential to my mission and commitments?”

• Measures risk across a spectrum from 0 to 100 (instead of the macro current MC/MD/NMCMD bins in use today.)

• Writing Q1, Q2, Q3, and Q4 in terms of senior management priorities allows tailoring to different missions and goals, allowing functionalities supporting safety and environment to compete with direct mission functionalities.

• MDI x Condition Index gives a prioritization metric for maintenance.

• MDI is a key parameter in the work planning portion of the Builder Sustainment Management System.

• Implementation effort can be simplified by preparing standard screenings for general purpose facilities, allowing sites to accept the standard screenings or to modify to fit local circumstances.