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1 Impact of Decisions Made to Systems Engineering: Cost vs. Reliability System David A. Ekker Stella B. Bondi and Resit Unal November 4-5, 2008 HRA INCOSE.

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Presentation on theme: "1 Impact of Decisions Made to Systems Engineering: Cost vs. Reliability System David A. Ekker Stella B. Bondi and Resit Unal November 4-5, 2008 HRA INCOSE."— Presentation transcript:

1 1 Impact of Decisions Made to Systems Engineering: Cost vs. Reliability System David A. Ekker Stella B. Bondi and Resit Unal November 4-5, 2008 HRA INCOSE CONFERENCE, NEWPORT NEWS, VIRGINIA

2 2 Presentation Outline Introduction Problem Statement Methodology Analysis Operational Impacts Strategies Conclusions

3 3 Introduction Impact on decisions made in terms of cost and reliability Selection of strategy for maintaining an operational system Decisions made are faced with trade-off between cost and operational reliability.

4 4 Problem Statement Background Basic System System requirements

5 5 Background Mission Critical Systems must assure: Operation Safety Critical operable subsystem in process of being replaced Obvious reduction in its MTBF of ~80% Continuous increasing repair costs Scarcity of parts Technical repair knowledge declines Concerns that the subsystem will fail at critical times where safety would be impacted.

6 6 Basic System

7 7 System Requirements Dual, independently operation systems providing data for operations Operating 24/7 with output verified and compared to each other A third system checks periodically the dual system When System–3 is not available, Systems 1 & 2 become critical which means abort of operations for safety assurance.

8 8 Solutions Goals Investigate Various Strategies Optimize Reliability Evaluate Related Cost Minimize decision makers intuition Use a more precise cost vs. reliability mechanism

9 9 Methodology Data collection Determine data distribution and equation parameters Select strategies for analysis Calculate system reliability using distribution equations Compare costs of the various strategies

10 10 Estimate Distribution Parameters Little data available Weibull probability distribution was the best option of approximation for reliability The basic form of the Weibull equation is Where θ is the scale and m is the shape parameter

11 Reliability vs. Time

12 12 Operational Constraints Both SYSTEM-1 and SYSTEM-2 fail and no spares are available, then all operations are aborted until both systems are replaced Failure of either SYSTEM-1 or SYSTEM-2 will result in aborting operations. It is assumed that these situations are predictable in advance. The overall system is expected to operate on a long term schedule and this schedule is available for planning purposes. In certain situations, aborting operations can result in long transit times to a location where spare parts are available.

13 13 Operational Constraints (Contd) Not carrying spares adds additional expense of storage at a central facility and/or shipping costs. Carrying spares incurs a penalty for storage and weight. Aborting certain operations require another system to be immediately dispatched to cover operations and can result in costs on the order of 100 times the cost of a spare module – predictable situations. The life cycle cost only involved purchase and refurbishment cost, it did not include costs of lost operations.

14 14 Strategies Carry no spare Carry one spare Carry two spares Refurbish equipment at a pre-determined time equivalent to carrying one spare Refurbish equipment at a pre-scheduled time coordinated with manufacturer and set at time between missions

15 15 Analysis of Strategies The life cycle cost versus reliability normalized to the least expensive strategy Key contributing factor to the overall system reliability is infant mortality for the carrying spares

16 16 Discussion Of Strategies: Option 1 Repair When Fails (Baseline) Lowest reliability for both situations - unacceptable Least repair cost Greatest adverse operational results

17 17 Discussion Of Strategies: Option 2 Carry One Spare Significant improvement in reliability 42% higher cost Reliability still low when two operating systems are required (0.45)

18 18 Discussion Of Strategies: Option 3 Carry Two Spares Further reliability improvement over carrying one spare, approx. 2x reliability when 2 systems are required Greatest cost (84.5% higher) Acceptable reliability (0.99, 0.97)

19 19 Discussion Of Strategies: Option 4 Refurbish at 62.5% MTBF Compared to carrying one spare: Same cost Same reliability as for carrying one spare Nearly 2x reliability for 2 Units operating Predictability of repairs

20 20 Discussion Of Strategies: Option 5 Refurbish at 58.3% MTBF 10% increase in cost than option 4 Best reliability Lines up with repair cycle Least operational impact

21 21 Planned vs. Corrective Maintenance Strategy Normalized Cost Worst Case Reliability Experienced SYSTEM-1 OR SYSTEM-2 operating SYSTEM-1 AND SYSTEM- 2 operating Carry no spare1.000.45000.0710 Carry 1 spare1.420.98900.4530 Carry 2 spares1.850.99960.9710 Refurbish at 62.5% MTBF 1.420.99000.8200 Refurbish at 58.3% MTBF 1.560.99580.8752

22 22 At least one core module operating Both core modules operating Both core modules Operating - 2 Spares At least one core module Operating - 1 Spare Reliability vs. Age with Spares Reliability Normalized Age, % MTBF

23 23 Conclusions Variation in key parameters can be used to check for the sensitivity of operating guidelines provided If strategy coincides with normally scheduled maintenance periods, less operational impact will result Selecting the proper strategy can be critical for maintaining system reliability and subsequent mission success, yet, not necessarily resulting in significant cost increases Our analysis indicates that a reliability versus cost trade-off may be achievable

24 Future Work There are many cost vs performance studies, yet few cost vs reliability. Develop a metric that provides a cost per reliability so as to compare strategies

25 25 THANK YOU!

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