A Case Study on Automotive Battery System Design - Title Page - MIT

More documents

Recommendations

Info

lead to decision-making, as the point forecast means that no decisions need to be made. As anexample, in a new product introduction, a 10-year NPV would utilize a typical demand curveestimate from any number of econometric demand curve models. Perhaps in year 1 the analyst isrelatively close to what will actually happen, but at year 0, it is impossible for the businessanalyst to truly know whether or not the new product has been a success in year 10. In thetraditional NPV model, there is zero chance of product failure, nor any chance of very highsuccess in the product. The analyst has asserted the mean estimate of outcome and used it foranalysis. Thus, this is an unrealistic methodology for developing a business case due to theinability to predict the future.A more detailed analysis may recognize uncertainty in the system. Socrates had the Oracle atDelphi, Operations Managers have the normal distribution, and analysts have expert forecasts.An analyst might calculate three NPV models from an expert’s forecast, one with high-demand,middle demand, and low demand, for a “best, average, and worst” case scenario. By bracketingthe decision process, the analyst has recognized uncertainty and is able to provide an estimate ofdeviation from the expected NPV (ENPV). The ENPV continues to be the same, as the middle“average” case will provide the same answer to the analyst who ran a static NPV. Additionalwork is completed with the same answer; management will continue to choose the “expectedcase”.Recognition of uncertainty might drive an NPV simulation over a distribution of outcomes. It isnot difficult for the analyst with 3 scenarios to fit a curve to those same values, developing asimple model for demand of the new product. Again, the expected value is the answer to theproblem. As the analyst increases the sophistication of the model, there is an acknowledgementthat the future is uncertain. This additional step in analysis leads to acknowledgement without22
action; the analyst continues to develop a passive model of future conditions. Management willnot respond to future conditions in the model.Once the uncertainty analysis has been completed, the real options analyst will begin to developtest cases for “actions”. In other words, if demand for a new product falls to 50% of the originalprojection, a manager would close down the product, zeroing future cost associated withmanufacturing, marketing, etc.. By acknowledging this action, the real options NPV analystbegins to establish thresholds over the Monte Carlo simulation where the product will be shutdown, thus protecting the manufacturer against downside risk. If expected demand in year 5 is10,000, and simulated demand in year 5 is 10, the manager would shut down production. Thereis a cost to shut down, but that will most likely be substantially lower than the cost of continuedproduction due to both fixed and recurring costs. The analyst can establish the value of the shutdown cases and run screening models to evaluate them. For a real option, the analyst willexamine where flexibility in the system may be placed to enhance the ability to shut down.On the other hand, demand may be much higher than anticipated and the manager will want toexpand. In the original analyst’s passive model, there may have been variable cost due toeconomies of scale. In this new model, the analyst must also acknowledge expansion of either amanufacturing facility or the cost of an additional contract manufacturer. By establishing theability to produce beyond the originally expected value, the analyst has created upside potential.If we build the facility to product 10,000 units in year 5, but demand in the simulation is 20,000units, the additional potential revenue is lost unless there is an embedded method for expansion.If we want to limit downside losses and create upside potential, are there any actions that can betaken now to create an easier path for either(de Neufville & Scholtes, Flexibility in EngineeringDesign, 2011)?23
Page 1 and 2: SYSTEM ARCHITECTURE DECISIONS UNDER
Page 4 and 5: SYSTEM ARCHITECTURE DECISIONS UNDER
Page 7 and 8: Figures and TablesTable 4.1: Curren
Page 9 and 10: untested, unknown technology like h
Page 11 and 12: Chapter 2: Literature Survey—Flex
Page 13 and 14: solutions, with a discussion of how
Page 15 and 16: may have extension beyond those pro
Page 17 and 18: Meyer defines the steps to product
Page 19 and 20: The methodology used by de Weck has
Page 21: Chapter 3: Flexibility Valuation Mo
Page 25 and 26: 3.2: The Garage Case</stron
Page 27 and 28: The Garage Case is
Page 29 and 30: In a financial analysis, the engine
Page 31 and 32: outcome may have, optimistically, a
Page 33 and 34: ehavior, presenting the risk of exp
Page 35 and 36: ) Voltage/current may be different
Page 37 and 38: An FHEV or PHEV has different contr
Page 39 and 40: limited capacity for expansion, cau
Page 41 and 42: Chapter 6: Battery Thermal ControlH
Page 43 and 44: In fact, vehicles in the market alr
Page 45 and 46: 6.2: Flexibility Valuation Modeling
Page 47 and 48: This simulation’s primary assumpt
Page 49 and 50: Another interesting observation is
Page 51 and 52: wide range of uncertainties in both
Page 53 and 54: process with less risk. An investme
Page 55 and 56: Beyond the existing model, there ar
Page 57 and 58: Chapter 7: SummaryThe choices made
Page 59 and 60: Clayton, M. (2012, March 5). Chevy
Page 61 and 62: Stenquist, P. (2011, 1 28). New Yor
Page 63: Font: 11 ptPage 6: [22] Formatted M

A Case Study on Automotive Battery System Design - Title Page - MIT

Create successful ePaper yourself

Delete template?

Save as template?