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Brennan Aircraft Division (BAD) Case Study By Elena White, Luigi DeAngelis & John Ramos.

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Presentation on theme: "Brennan Aircraft Division (BAD) Case Study By Elena White, Luigi DeAngelis & John Ramos."— Presentation transcript:

1 Brennan Aircraft Division (BAD) Case Study By Elena White, Luigi DeAngelis & John Ramos

2 Overview of Presentation Executive Summary Data Analysis Basis of Simulation Conclusion

3 Executive Summary BAD operates large number of plotting machines  Consist of minicomputer system that directs 4 pens to move until desired figure is drawn  Connected to a 4 – by-5 foot table with series of ink pens suspended above it  Very reliable with exception of ink pens clogging, jamming, rendering plotter unusable

4 Executive Summary Cont… BAD replaces ink pen upon failure of each Alternative repair by service manager  Replace all 4 ink pens upon one failure  Ideally reducing the frequency of failures

5 Data Analysis The following data was provided by the case study:  Total cost of downtime $50/hr  Replacement time of 1 pen = 1 hr/pen  Replacement time of 4 pens 2 hr/set  Cost of each pen $8/pen

6 Data Analysis Cont… HoursProbability 10.05 20.15 30.15 40.20 50.20 60.15 70.10 Probability Distribution Between Failures (each pen replaced as it fails)

7 Data Analysis Cont… HoursProbability 100.15 110.25 120.35 130.20 140.05 Probability Distribution Between Failures (4 pens replaced as 1 fails)

8 Data Analysis Cont… Additional data (assumptions used in simulation to establish year utilization) 1 plotter year2500 Hours10hrs/day – 250 days

9 Basis of Simulation Simulated Brennan’s problem for two options  Case 1 : Replace ink pen as it fails  Case 2 : Replace all four ink pens as one fail Used “Next Event Increment Model” approach to carry out the simulation Split runs in “Year (of 2500 hrs each)” this helps in results analysis  Each run is arrested when “close enough” to 2500 hrs. A “While- cycle” would have been best approach. A spreadsheet works well as analysis is simple Used VLOOKUP to instantaneously look-up probability tables and determine hours between plotter failures

10 Basis of Simulation Cont… Computed total time adding downtime to TBF computed from Probability Distribution. Derived total cost of each failure  Cost of 1 pen plus cost of One hour of downtime (case 1) = 58 $  Cost of 4 pens plus cost of Two hour of downtime (case 1) = 132 $  Computed failures for the equivalent of 1 plotter year. Run repeated 5 times (reasonable life-cycle for a plotter).

11 Simulation: Results Case 2 is the most convenient choice evaluated as an average on a 5-Year simulation.

12 Analytical Results A different approach has been followed based on analytical considerations. The Mean for each distribution has been calculated, i.e. MTBF. We calculated number of failures X year as:  Numb. Fail. X Year= 2500 / (MTBF + MT) We calculated costs in 1 Year as:  1 Y Cost = [Numb. of Fail. X Year] * [Repairing Costs]  NOTE: Tot. Cost = [1 Y Cost] * [N Year]

13 Analytical Solution: Results Best Choiche is again Case 2. Note how close Analytical and Simulated results are evaluated as an average on a 5 Y time frame.

14 Conclusion Based on the results achieved with the.xls simulation we observed the progression of costs and maintenance times Determined that in Case 2, replacement of all 4 pens upon one failed pen, will minimize maintenance costs for BAD Analytical results reinforce our simulated study that Case 2 is indeed the best policy to implement. (or viceversa?)

15 Any Questions?


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