Systems Availability Modeling

1
Systems Availability Modeling Analysis

• Systems Availability Modeling Analysis

Rev 04.30.13
2
System Availability Modeling and Analysis

• Availability Metrics, Concepts and Relationships
• System Availability Models
• System Availability Model Development
• Summary

3
Availability Analysis

• provides a mathematical basis for evaluating
  system design and development decisions based on
  system level performance measures in order to
  influence the air vehicle design concurrently
  with support system design.

4
Availability Metrics, Concepts and Relationships
5
System Operational Parameters

• Operational Effectiveness
• Readiness or Availability
• Mission Success
• Ownership Cost
• Logistic Support Cost
• Operating Cost

6
System Performance Measures

• Availability
• A measure of the degree to which an item is in
  an operable state at the start of a mission when
  the mission is called for at a random time.
  Expressed as inherent, achieved, or operational.
• Readiness
• The probability that military forces, units,
  weapons systems, equipment and personnel will be
  capable of undertaking the mission and function
  for which they are designed or organized, at any
  random point in time.
• Sustainablity
• The capability of military forces, units,
  equipments and personnel to maintain a specified
  level of mission activities for specified times.

7
Availability (Operational Readiness)

• The Probability that at any point in time the
  system is either operating satisfactorily or
  ready to be placed in operation on demand when
  used under stated conditions.

8
Operational Readiness (OR) Definition

• Operational Readiness (OR) is defined by the Navy
  to be a condition status indicating an
  operational unit aircraft to be safely flyable
  and capable of performing one or more (but not
  necessarily all) of the primary missions of the
  unit to which assigned.

9
Availability Definition

• Easy to understand
• Difficult to compute
• Uptime and downtime are difficult to define
• Steady state value

10
Availability, Reliability, Maintainability
1 MTBF
Operational State
Failed State
1 MTTR
11
Inherent (Intrinsic) Availability

• Probability that a system or equipment shall
  operate satisfactorily at any given time when
  used under stated conditions, without
  consideration for any schedule or preventive
  maintenance, in an ideal support environment.
• Refers primarily to the built-in capability of
  the system or equipment function of repair
  times and failure frequency
• No defect may or may not be included depending
  upon ground rules.

12
The System View

• Availability
• Sortie Generation Rates
• Basing

Product

• Reliability
• Maintainability
• Supportability
• Testability

• Organization
• Requirements
• Schedule Maintenance
• Unscheduled Maintenance

• Spares
• Technical Publications
• Training
• Support Equipment

13
Availability Analysis Flow Diagram

• Mission Reliability
• MTBF
• MTBM

Reliability Analysis
Availability Analysis
Maintainability Analysis
Cost EffectivenessAnalysis

• MTTR

• MDT (A)
• MDT (L)

Supportability Analysis
Life Cycle CostAnalysis
14
Reliability, Maintainability Supportability
Systems Operation Performance
15
Reliability Maintainability Relationships
16
System Design Evaluation Categories
System/Segment (Type A)Functional Baseline
Operational Effectiveness Evaluation
Operational Suitability Evaluation

• Requirements
• MOEs/MOSs
• Critical Issues
• Test Objectives
• Thresholds
• Deficiency andFailure Tracking

To what degree does this system satisfactorily
support mission accomplishment when used by
representative personnel in the expected or
potential environment for operational employment
of the system considering organization, doctrine,
tactics, survivability, vulnerability, and
threat?
To what degree can this system satisfactorily be
deployed considering availability, compatibility,
transportability, interoperability, reliability,
wartime usage rates, maintainability, safety,
human factors, manpower supportability,
documentation and training requirements?
Functional Effectiveness Evaluation
How and to what degree will this system
satisfactorily contribute to the required
mission(s) in the predicted operational
environment? (a combined, system-level
assessment)
ScheduleEvaluation
CostEvaluation
17
RMS Integration into System Engineering Process
TechnicalDisciplines
Pre-FSD
FSD

• Logistics Concept Planning and Development
• Life Cycle Cost Goals
• Supportability Specifications

• Operations Analysis
• Life Cycle Cost
• Survivability/Vulnerability
• Safety
• Reliability/Parts Standardization
• Maintainability
• Human Factors
• Maintenance Concept/Plan
• Spares Provisioning
• Support Equipment
• Training equipment
• Training
• Technical Publications
• Packaging, Handling, Storage Transportation
• Facilities
• Manpower Requirements Personnel
• Logistics Support Resource Funding
• Energy Management
• Computer Resources

System
SupportSystem
Transition toProduction

• Update ILS Plans
• Quantification of Support Requirements
• Integration of Support Studies and Analyses
• Design Support Trade Off Studies
• Evaluation of Support System Effectiveness

TrainingSystem
System Engineering, LSA, Integrated Logistics
Support
Operations

• Identification Resolution of Support Problems
• Analyses for Operational/Support Concept
  ChangesEvaluation of System Mods Impacts on
  Support

18
System Time Relationships
19
Aircraft Time Breakdown
Availability Analysis Period of Interest
Total Off Time
Total System Operating Time
Total Up Time
Total Down Time
Administrative/ Logistics Delay Time
Active Maintenance Time
Standby Time
Operating Time
C
P
TCM
TPM
20
(No Transcript)
21
Major Availability Analysis Process Elements

• Reliability Analysis Techniques (typical)
• Failure Modes and Effects Analysis
• Failure Modes and Effects Criticality Analysis
• Reliability Block Diagrams
• Failure Rate Estimation
• Maintainability Analysis Techniques (typical)
• Maintenance Task Time Analysis
• Engineering scale models

22
Major Availability Analysis Process Elements

• Supportability Elements (typical)
• Logistics Support Analysis
• Spares Provisioning Levels

23
Major Factor Influencing Availability

• System Reliability Design Characteristics
• MTBF a reliability function which assumes that
  operation occurs after early failure (infant
  mortality) and prior to war-out, i.e., a constant
  failure rate exists.
• MTBMA Mean Time Between Maintenance Actions - a
  reliability function which accounts for all
  causes of maintenance activity, whether a failure
  occurred or not.

24
Major Factor Influencing Availability

• System Maintainability Design Characteristics
• Mean Time To Repair (MTTR) a maintenance
  function, includes corrective maintenance time
  (CMT) and preventive maintenance time (PMT)
• Support System Design Characteristics
• Mean Logistics Down Time (MLDT) a maintenance
  related logistics function which involves spares
  provisioning and logistics delay time (LDT)
  administrative delay time (ADT)

25
Major Factor Influencing Availability

• System Maintainability Design Characteristics
• MTTR a maintenance function, includes corrective
  maintenance time (CMT) and preventive maintenance
  time (PMT)
• Support System Design Characteristics
• Mean Logistics Down Time a maintenance related
  logistics function which involves spares
  provisioning and logistics delay time (LDT)
  administrative delay time (ADT)

26
System availability Models
27
Types of Availability

• Inherent Availability (Ai)
• designed in availability
• does nor consider administrative and logistic
  downtime

28
RM Trade-offs (typical)
Maintainability (MTTR in hours)
120 100 80 60 40 20
A0.984
A0.995
Maximum
A0.999
2000 4000 6000
8000 10000
Reliability (MTBF in hours)
29
Inherent Availability

• Single Element with constant failure rate l and
  constant repair (restore) rate m
• - Instantaneous Inherent Availability-
  Steady State Inherent AvailabilityWhere

30
Inherent Availability

• Series Reliability Configuration with two
  Elements- Steady State Inherent Availability
• - Series Reliability Configuration with n
  Elements
• - Steady State Inherent Availability

E1
E2
l, m
l, m
E1
E2
En
... ...
l1, m1
l2, m2
ln, mn
... ...
31
Inherent Instantaneous Availability

• Two Element active parallel reliability
  configuration - Instantaneous Inherent
  Availability

32
Inherent Instantaneous Availability

• WhereSteady State Inherent Availability

33
Inherent Steady State Availability

• Active Parallel Reliability Configuration with n
  Elements

l1, m1
l2, m2
...
...
ln, mn
34
Inherent Steady State Availability

• Standby Configuration with Two Elements
• - Inherent Steady State Availability

l, m
l, m
35
Operational Availability

• Probability that a system or equipment shall
  operate satisfactorily at any given time (When
  used under stated conditions?)
• Measure of total capacity function of repair
  times, failure frequency, preventive and
  scheduled maintenance, supply downtime,
  administrative down time, support equipment
  downtime,

36
Aircraft Operational Availability (AO) Definition

• Aircraft operation availability AO is defined to
  be the probability that the aircraft is in an
  operable and committable state at a random point
  in time when used in a typical maintenance and
  supply environment.
• The downtime expected under wartime conditions
  (allowing for long term deferral of some
  maintenance) is determined from estimates of the
  rates of essential unscheduled maintenance
  actions (UMAs) and essential removals.

37
Types of Availability

• Operational Availability (A0)
• expected in-service availability
• includes impact of logistics.
• exactly which logistics elements are included
  must be defined in advance.

38
Types of Availability Estimates

• Point Estimate single, average or mean value
  of availability characteristic
• Interval Estimate confidence that availability
  is within a specified range of values (with a
  certain probability)
• Instantaneous Estimate availability measure
  value at a particular point in time
• Special Cases of field system reliability/availabi
  lity estimates
• Apparent Availability availability of a system
  calculated considering detected failures only
• Real Availability availability of a system
  considering all system failures

39
System availability model development
40
System Availability Model Development
41
Model Development Overview

1. Analysis Objectives
2. Analysis Planning
3. Development Approach
4. Development Considerations
5. Inputs and Outputs
6. Data Requirements
7. Algorithm Development
8. Implementation Examples

42
Typical Availability Model Applications

• Overall Requirements assessment
• ECP Evaluation
• Trade Studies on RM
• Wide Range of Sensitivity Analysis
• Manpower Requirements Derivation
• LRU Spares/Not Mission Capable
• due to Spares (NMCS) Evaluation
• Flying Hour Program Evaluation
• Sequential vs Parallel Maintenance Options
• Support System Evaluation
• .

43
General Modeling Options

• Analytical Representations
• Mathematical formulas and symbolic models
• May use computers to process the formulas
• Computer Simulations
• Imitation of the physical phenomena(movement,
  war, performance overtime) using computer
  generated activities and results
• human decision making represented by
  pre-programmed and/or probabilistic decision
  rules
• Assemblage of Gaming People and Tools
• Human-based game playing to achieve insights
  (e.g. war games)
• Field Experiments
• Replications of a physical situation under
  controlled and limited scale environments to
  estimate total system level performance

44
When Simulation Models Make Sense(An Analysts
Checklist)

1. When mathematical models do not exist, or
   analytical methods of solving them have not yet
   been developed
2. When analytical methods are available, but
   mathematical solution methods are too complex to
   use
3. When analytical solutions exist and are possible,
   but are beyond the mathematical capabilities of
   available personnel
4. When it is desired to observe a simulated history
   of the process over a period of time in addition
   to estimating relevant parameters
5. When it may be the only possibility because of
   difficulty in conducting experiments and
   observing phenomena in their actual environment
6. When time compression may be required for systems
   or processes over long time frames

45
When simulation models make sense

• When mathematical models do not exist, or
  analytical methods of solving them have not yet
  been developed
• When analytical methods are available, but
  mathematical solution methods are too complex to
  use
• When analytical solutions exist and are possible,
  but are beyond the mathematical capabilities of
  available personnel
• When it is desired to observed a simulated
  history of the process over a period of time in
  addition to estimating relevant parameters
• When it may be the only possibility because of
  difficulty in conducting experiments and
  observing phenomena in their actual environment

46
Advantages of Simulation

• Permits controlled experimentation with
• consideration of many factors
• manipulation of many individual units
• ability to consider alternative polices
• little or no disturbance of the actual system
• Effective training tool
• Provides operational insight
• May dispel operational myths
• May increase effectiveness of management decision
  making
• May be the only way to solve problem

47
Disadvantages of Simulation

• Costly (very costly?)
• Uses scarce and expensive resources
• Requires fast, high capacity computers (use of
  PCs?)
• Takes a long time to develop
• May hide critical assumptions
• May require expensive field studies
• Very much dependent on availability of data and
  is validity

48
Thoughts To Remember

1. The overall objective of availability modeling
   and analysis is to provide support to the system
   design, development, and deployment process in
   order to influence system design by considering
   all aspects of its reliability, maintainability,
   and support system characteristics
2. The objective remains unaffected by the choice of
   using one model solution technique (e.g.
   simulation) over the other.
3. The choice of one method over another will be
   influenced primarily by outside factors (e.g.
   cost, schedule, availability of data, personnel
   and facility capabilities).

49
Availability Analysis Objectives

• Specification Requirements Evaluation
• Requirement Integration - Conflicts? Attainable?
• Verify and Demonstrate Compliance
• Verify Demonstrate Adequacy of Logistics Support
• Support System Design Influence
• Evaluate Impacts of Changes to Operation and
  Maintenance Concepts
• Analyze Evaluate Operational Suitability
• Support Functional Trade-off Analyses on
  Alternative Designs
• System Design Assessment
• Examine the Total Picture at the System Level
• Address Impacts of All Variables at once
• Evaluate Impacts of Flight/Scenario/Usage Rate
  Changes
• Management Visibility
• Provide Useful Predictions for All Levels of
  Management
• Assist Management in Identification and
  Resolution of Reliability, Maintainability, and
  Supportability Issues

50
RMS Analysis Objectives by Program Phase

• Concept Definition
• Support Contractual Requirements Analysis
• Examine Operations, Maintenance, and Support
  Concepts
• Support Design Concept Trade-off Studies
• Identify Cost, Schedule, Risk, and Support
  Drivers
• Demonstration/Validation
• Refine Concept Definitions
• Support Requirements Allocation Process
• Provide Capability to Influence Design
• Estimate Fielded System performance Levels
• Full-Scale Engineering Development
• Support Detailed Trade-off Studies
• Establish Support System Requirements Baseline
• Assess/Validate Operations, Maintenance, Support
  Concepts
• Production and Deployment
• Asses Fielded System Performance Levels
• Refine Support Concepts/Levels
• Identify System Improvement Requirements

51
RMS Analysis Planning Considerations
Evaluate A/R/S Analysis Reqs.

• Where does data come from?
• Experiment?
• Field tests?
• Previous experience?
• Simulation?
• Other resources?
• What will data be used for?
• How will data be collected and managed?
• What tests/simulations need to be executed, and
  when?
• How will results be dev. and rec?
• How does everything fit together to meet the
  system test eval. objectives?

Develop Test / Analysis Plans

• Critical Issues
• Objectives
• MOEs MOSs
• Success Criteria
• Schedule

• Test Design
• Analysis Plan
• Data Collection Management Plan
• Test Execution Plan
• Documentation Plan
• Test and Evaluation Master Plan

52
RMS Model Development Approach

• Define Model Elements and Specifications
• Operational Activity elemanet Specifications
• System State Conditions and Attribute
  Specifications
• Operational Activity Demand Generation
• System Component Level of Detail Determination
• Support System Resource Definition and
  Specifications
• Define Model Structure
• Model Processing Definition(s)
• System Failure Processing
• System Unscheduled Maintenance Processing
• Model Inputs
• Model Outputs
• Implement Model Structure on the Computer
• Model Activities
• Model Output Measure Calculation Implementation
• Perform Full Model Test Eval. Using Sample Data
• Install Model at User Site and Perform Checkout,
  Train Users

53
Probabilistic Modeling(probabilistic analysis)

1. Purpose To simulate probabilistic situations
   using a random number generator and the
   cumulative probability distribution of interest.
2. Example Distribution of unscheduled maintenance
   timesno action required (none), repair in place
   (RIP), remove and replace (RR), and cannot
   duplicate (CND)

54
Analysis/Model Development Considerations

1. Data Input/Output Formats
2. Data and Output Result Configuration Management
   Control
3. Input/Output Data Approval by Management
4. Baseline and Excursion Data Definitions/Conditions
   
5. Data Screening/Editing Capabilities
6. Model Restart Capabilities
7. Ease of Development and Modification
8. Transparency to the Users (changes to system and
   data)
9. Degree of integration with other models and
   Analyses
10. Convenient Man-in-the-Loop Interfaces
11. Growth/Flexibility/Change Capabilities
12. Others

55
Typical Availability Model Requirements

• Work Unit Code (WUC) Structure
• Total system WUC structure
• Two Digit level definitions (or to levels of
  interest)
• Probability Distributions fro Activity Times (by
  WUC)
• Mission durations and types
• Trouble-shooting times
• On/off aircraft repair times
• Remove, replace, checkout times
• Delay times (spares, personnel, equipment)
• Service and turnaround times
• Preflight and return service times
• Probabilities (by WUC)
• Probability of in-flight failure (gripe)
• Spares, personnel, equipment availability when
  called
• On equipment vs. off-equipment repair rates
• No defect found rates

56
Input Data Sources Parameters
Model Data Element Definitions derived from Air
Force Terms
Air Force RAM Data Sources

• AFR 66-1 (Maintenance Data Collection System-
  MDCS) Data Elements
• CORE Automated Maintenance System (CAMS)
• AFR 65-110 (air Vehicle Inventory Status and
  Reporting System (AVISURS)
• Others

• Reliability in terms of MTBM
• Types 1,2, 6
• On-equipment Off-equipment Maintenance
  Action Definitions
• Repair in Place
• Cannot Duplicate
• Bench Check - Repair
• Bench Check - Serviceable
• Not Repairable in this Station
• Work Unit Code Definitions
• Others

57
Typical Availability Model Output Parameters

• Availability Parameters
• Average mission capable rates (full, partial, not
  capable)
• Instantaneous mission capability status at any
  time in the simulation/analysis period
• System Level Performance Parameters
• Average downtime per sortie
• Average unscheduled maintenance time
• Percent of scheduled sorties accomplished (over
  time)
• Number of sorties cancelled due to pre-sortie
  failure
• Number of unscheduled maintenance actions
  required
• Maintenance Resource Utilization Statistics
• Total resource hours used during simulated period
  
• (by resource type)
• Maximum number in use at any time during
  simulation
• Total number of subsystem spare parts used

58
Characteristics of PC-based Modeling

• Can provide stochastic network processing with
  discrete events using simulation languages
  implemented on PCs (SLAM II)
• Can simulate system operational environments
• Basic operations and maintenance processing
  defined by established input networks
• Specific task information (times, required
  resources, task attributes, etc.) supplied
  through input data
• Will treat system maintenance simulated at line
  replaceable unit (LRU) level of detail with input
  and output data aggregated at the subsystem level
  of detail
• Provides real-time system capability assessment
  over a wide range of design and development
  parameters with relatively small set of input
  data required
• Use of real-time graphics capabilities promotes
  model understanding and display of results of
  different execution conditions and constraints
• Portability permits use in remote and dispersed
  locations for examining impacts of local
  environmental and support conditions

59
What Talents are Required?

• System Operators
• Develop operational and support requirements and
  concepts
• Develop measures of effectiveness (MOEs) and
  supportability (MOSs)
• System Modelers
• Develop system-specific modeling and analysis
  requirements, parameter definitions, input/output
  requirements
• Translate requirements into algorithmic
  definitions
• Applications Programmers
• Implement the model(s) in the appropriate media
  solution
• Systems Analyst
• Perform the required analyses and interpret
  results in terms of system level impacts

60
Same Analysis Models

• Analytical Models
• Inherent Availability Models
• Expected Value Models
• Stochastic/Markov Models
• SAVE (System Availability Estimator)
• Differential Equation Models
• Parametric Models
• Simulation Models (Mainframe PC-based)
• Top-Level Models
• Theater Simulation of Air Base Resources
  (TSAR)-Rand Corp.
• Douglas Aircraft Company Availability Model
  (DACAM)
• System Inventory Analysis Model (SIAM)
• More detailed Models
• Modified Logistics Composite Model (LCOM)-USAF
• Comprehensive A/C Support Effectivenes
  Evaluation.(CASEE)Model
• -USNavy

61
Previous Availability Model Applications
Model System/Agency Applications Application/Purpose
Logistics/Composite Model (LCOM) Aircraft(C-17, B-1, F-11A,D,E,E-3A,F-4E,G,RF-E, A-10, A-7D, CH-53) Space ShuttleClass.Sys. Early Oper. Suitability Anal. Support Sys. Assessment Manpower Req. Analysis Mission Capab. Assessment
Avail./Readiness Model- Personal Comp.Application (ARM-PC) C-17FX-99SABIR Satellite Systems (Mc Donnell Douglas, Rockwell Intl) Early Oper. Suitability Anal. Support Sys. Assessment Mission Capab. Assessment
General Workstation Analysis Model (GWAM) Classified Systems/Clients Workst./Depot Flow Anal. Resource Req./Cost Process Throughput/Turnaround
(Missile) System Inventory Availability Model (SIAM) Classified Systems/Clients Early Oper. Suitability Anal. Depot Req. Assessment Field/Deployed Avail. Anal.
Cruise Missile Availability Models (AAM and GAM) Ground-Launched Cruise Missile (GLCM)Air-Launched Cruise Missile (ALCM) Early Oper. Suitability Anal. Support Req. Assessment Field/Deployed Avail. Anal.
Availability-Oriented Provisioning Model (AOP) Tracking/Data Relay Satellite Station (TDRSS)Class. Sys. Spare Part Prov. Req. Optimum Spare Part Prov. For Availability
Logistics/Maint. Attack Model(LOGATAK,MACATAK) Defense Nuclear Agency US Army Logistics Center Effects of Enemy Interdiction on Logistics Support Systems
Network Repair Level Analysis (NRLA) Model Tactical Remote Sensor System (TRSS) Optimum Repair Level Analyses
62
System Life Cycle Utility of Models/Analyses
- High level analysis -
ECP/Changes/Problem Resolution
63
Summary
64
The Benefits of Availability Modeling Analysis

• Availability Modeling and Analysis provides
• the glue which ties system RMS performance
  evaluation together
• Considers operational environments and stresses
• Identifies dominant failure modes and drivers
• Balances overall support system performance
• rational structure for evaluating system design
  and development decisions based on system level
  performance measures
• one of the few methods capable of estimating
  fielded system performance levels during the
  design and development process.
• Applies to Commercial as well as defense systems