1. 1 Logistics Systems Engineering Availability NTU SY-521-N SMU SYS 7340 Dr. Jerrell T. Stracener, SAE Fellow

2. 2 Performance Measures (DoD Sys Eff) 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

3. 3 Performance Measures (DoD Sys Eff) –and function for which they are designed or organized, at any random point in time. Sustainability: –The capability of military forces, units, equipment and personnel to maintain a specified level of mission activities for specified times.

4. 4 Commercial System Measures Aircraft –Top ten delay/cancellation systems (delays>15 min and cancellations) Delay rates (rate/100 revenue departures) Total interruptions (delays > 15 min & cancels) Daily utilization rates dispatch reliability (%) Maintenance required per cycle

5. 5 Commercial System Measures Vehicles –Average miles between failure Ships –Average steaming days between main turbine failures Power Plants –Unit availability (average operating hours per year)

6. 6 MIL-STD-721 Definitions 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 an unknown (random) time. Reliability –The probability that an item can perform its intended function for a specified interval under stated conditions.

7. 7 MIL-STD-721 Definitions Mean Time Between Failures (MTBF) –A basic measure of reliability for repairable items. The mean number of life units during which all part of the item perform within their specified limits, during a particular measurement interval under stated conditions.

8. 8 Availability, MTBF, Reliability Failed State Operational State 1 MTBF 1 MTTR

9. 9 Availability Definition Easy to understand Difficult to compute Uptime and downtime are difficult to define Steady state value

10. 10 Types of Availability Inherent Availability (Ai): –The designed in availability. Ai calculations ignore all logistics contributions to downtime.

11. 11 Types of Availability Operational Availability (Ao): –The expected in-service availability. Ao calculations include the impact of logistics on availability. Exactly which logistics elements are included must be defined in advance.

12. 12 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. –Mean Time Between Maintenance Action: a reliability function which accounts for all causes of maintenance activity, whether a failure occurred or not.

13. 13 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)

14. 14 System Availability Calculation Produces reasonable results if and only if MTBF >>MTTR Causes availability to be understated by ignoring the case where multiple subsystem failures overlap in time

15. 15 Effect of Availability Model Assumptions Identical redundant elements –Simplifies calculations –Most common method of applying redundancy Hot standby –Can be optimistic, ignores startup time, software load time, etc –Often justified, commonly used method of applying redundancy

16. 16 Effect of Availability Model Assumptions Independence of elements –Produce idealized, optimistic results –Sometimes not justified, particularly with software base systems Perfect switching –Produce optimistic results –Difficult to justify for most systems Unrestricted repair –Minor impact if n is small and MTBF>>MTTR –Allows simpler calculation formulas to be used

17. 17 Effect of Availability Model Assumptions MTBF>>MTTR –Allows the use of simple formulas, not custom model solutions –Usually the case for modern electronic systems

18. 18 Insert slide, 4-19

19. 19 Insert slide, 3-6

20. 20 Choosing an Availability Analysis Method Insert slide, 4-6

21. 21 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

22. 22 Advantages of Simulation May make middle management more effective May be the only way to solve problem

23. 23 Disadvantages of Simulation Costly (very costly?) Uses scarce and expensive resources Requires fast, high capacity computers (use of PC’s?) 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

24. 24 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

25. 25 When simulation models make sense 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 When time compression may be required for systems over long time frames

26. 26 Availability Model Development Approach Define model elements and specifications –Operational Activity Element Specifications –System State Conditions and Attribute Specs. –Operational Activity Demand Generation –System Component Level of Detail Determination –Support System Resource Definition and Specifications

27. 27 Availability Model Development Approach Define Model Structure (Processing, Inputs and Outputs) –Model Processing Definitions –System Failure Processing –System Unscheduled Maintenance Processing –Model Inputs –Model Outputs Implement Model Structure on the Comp. –Model Activities

28. 28 Availability Model Development Approach Implement Model Structure on the Comp. (continue) –Model Output Measure Calculations Implementation Perform Full Model Test & Evaluation Using Sample Data –Validate the model’s ability to produce expected results Install Model at User Site and Perform Checkout, Train Users

29. 29 Insert slide, 2-3

30. 30 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

31. 31 Major Availability Analysis Process Elements Supportability Elements (typical) –Logistics Support Analysis –Spares Provisioning Levels

32. 32 Power Plant Exp. Avail. Relationship Availability Plant Availability where Ai = availability of major equipment or system or A = 1 -  Ui where Ui = unavailability = 1 - Ai

33. 33 Power Plant Exp. Avail. Relationship Typical Fossil Unit Availability Experience (adjusted availability %) –Boiler88.5% –Turbine94.2% –Condenser98.5% –Generator95.6% –Other97.6% Average fossil fueled unit availability

34. 34 Insert slide, 2-6

35. 35 Availability Analysis: A value-added process Availability analysis provides the “glue” which ties system RMS performance evaluation together: –Considers operational environments and stresses –Identifies dominant failure modes –Incorporates repair and replace times estimates –Evaluates overall support system performance

36. 36 Availability Analysis: A value-added process It provides a rational structure for evaluating system design and development decisions based on system level performance measures.