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MIT ESD 70J - Syllabus

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ESD.70J Engineering Economy Module Fall 2006 4 Sessions: Sept 11, 12, 13 and 14 (Monday - Thursday) Room 32-115 (Stata Center) 5 to about 7pm Alexander Fadeev and Richard de Neufville BRING LAPTOPS TO CLASS, PREFERABLY WIRELESS NETWORK READY This intensive micro-subject provides the necessary skills in Excel spreadsheet modeling for ESD.71 – Engineering Systems Analysis for Design. Its crux is the dynamic rather than the general deterministic modeling. . Its purpose is to bring entering students up to speed on some of the advanced techniques that we routinely use in analysis. It is motivated by our experience that many students only have an introductory knowledge of Excel, and thus waste a lot of time thrashing about unproductively. Many people think they know Excel, but overlook many efficient tools – such as Data Table and Goal Seek. We assume students know Excel basics such as referencing, names, functions, and formulas. If you do not know these basics, please get yourself an introductory manual and learn them. Three units of credit are offered to those who care to complete the assignment. However, we expect most students will simply learn from doing the worked out examples in class, and will not require credit. Day One – NPV and Sensitivity Analysis Objective: set up spreadsheet properly for efficiency, set up charts, and understand sensitivity analysis by Data Table Issues: 1. proper set-up of spreadsheets: entire entries of input in separate area; set up by formulas (the question is generated from the self-assessment problem) 2. one-way/two-way Data Table (one-way Data Table: for sensitivity on the discount rate for Plan B while the discount rate for Plan A is fixed ; two-way Data Table: for sensitivity on variable costs of Plan A and B; using Goal Seek functionality to find the maximum of variable cost for Plan A so that Plan A is still favored) 3. drawings (Plot the difference of NPVs for the two plans) 4. reference point for the function of “NPV” (also, students need to know how to set up the NPVs using formulas) examples of the use of “Text” function. Steps: 1. opening introduction of the course (objective, schedule, teaching methods, and requirements) 2. objective of the class on Day One 3. question (for set-up of the base case), students try 5 minutes 4. lecturing on proper set-up of the spreadsheet and charts 5. students setup the spreadsheet for the base case, 15 minutes6. posting solution 7. Q&A 8. question (for sensitivity analysis), students try 5 minutes 9. lecturing on Data Table/Goal Seek/Drawings 10. students set up spreadsheet for sensitivity analysis, 15 minutes 11. posting solution sheets 12. lecturing on “NPV” and “Text” function 13. Q&A Day Two - Simulation Objective: random number generator (using simple even distribution), how to count, and simulate Issues: 1. random number generator function such as “Rand()” 2. function such as “Countif” 3. generating Histogram, Cumulative Distribution Function 4. establish a complete simulation sheet (simulate 2000 times for NPV of Plan A) Steps: 1. Objective for the class 2. question (generate a random realization of demand over years), students try 5 minutes 3. lecture on random number generation function 4. students set up spreadsheet for generating realization of demand, 15 minutes 5. posting solution 6. Q&A 7. question (how to simulate thousands of times and draw histogram and CDF), students try 5 minutes 8. Lecturing 9. students set up spreadsheet for simulation, 15 minutes 10. posting solution sheets 11. Q&A Day Three – Modeling Uncertainties Objective: generation of advanced distribution of random variables and the statistical package to analyze available data Issues: 1. Triangular, normal, lognormal distribution 2. exponential growth of demand 3. trend plus uncertainty (generating a stock price realization path) 4. try call option 5. statistical analysis tools to find out important parameters from data set (find out average return and standard deviation for return) Steps: 1. objective of the class 2. lecture on triangular, normal, and lognormal distribution, exponential growth 3. question (simulate stock price), tell them basics for stock price movement 4. students setup the spreadsheet for stock price movement5. posting solution sheet 6. ask how to simulate a call option and give answer 7. Q&A 8. lecture on statistical analysis tool 9. question (find out average return and standard deviation for return) 10. students work on a data set of stock price 11. posting results 12. Q&A Day Four – Analyzing Flexibility and other Objective: What-if analysis and building contingency rules (flexibility) into the spreadsheet, and further Issues: 1. logical functions (“if”, “and”, “or”, etc.) 2. Value at Risk (VAR) Chart 3. using spinner to facilitate sensitivity analysis for simulation spreadsheet where Goal Seek does not work 4. future self-learning: overview of Excel, how to use Excel Help Steps: 1. objective of the class 2. question (adding flexibility and simulating to see what happens),students try 5 minutes 3. introducing logical functions 4. students set up spreadsheet for studying flexiblity 5. posting solution sheets 6. Q&A 7. Questions on VAR, students try 10 minutes 8. posting solution sheets 9. Q&A 10. question (find out the maximum of variable cost for Plan A so that Plan A is still favored under uncertain demand), students try 10 minutes 11. posting solution sheets 12. Q&A 13. lecturing on self-learning Excel and overview of Excel for future guidanceAppendix Big or small? A manufacturer is considering two investment programs to supply a new PC. Market research anticipates rapid market growth: sales are expected to be 300, 000 the first year, 600,000 the second, and 900,000 the third. However, the company recognizes that actual sales may differ by plus or minus 50%. The company has two plans to produce 900,000 units: • Plan A. Build a single plant that could produce 900,000 units. Construction would cost $900 million and be finished in a year. The company would get $2,000 per computer sold, and the incremental manufacturing costs beyond the capital cost of the plant is expected to be $1,280 per computer. • Plan B. Build 3 300,000 unit plants, one each year, in an effort to match expected annual demand. The capital expenditure for each small plant


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