Brennan Aircraft Division (BAD) Case Study

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# Brennan Aircraft Division (BAD) Case Study - PowerPoint PPT Presentation

Brennan Aircraft Division (BAD) Case Study. By Elena White, Luigi DeAngelis & John Ramos. Overview of Presentation. Executive Summary Data Analysis Basis of Simulation Conclusion. Executive Summary . BAD operates large number of plotting machines

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### Brennan Aircraft Division (BAD)Case Study

By

Elena White, Luigi DeAngelis &

John Ramos

Overview of Presentation
• Executive Summary
• Data Analysis
• Basis of Simulation
• Conclusion
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
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
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
Data Analysis Cont…
• Probability Distribution Between Failures

(each pen replaced as it fails)

Data Analysis Cont…
• Probability Distribution Between Failures

(4 pens replaced as 1 fails)

Data Analysis Cont…
• Additional data (assumptions used in simulation to establish year utilization)
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
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).
Simulation: Results

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

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]
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.

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?)