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MT1 note card - strategy major accident 3% minor accident...

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self insured -100,000 -10,000 0 .03(-100000) + .07(-10000) + .9(0) = $-3700 17,126 cheapest but most variable Sampledeviation = √ [(3(102-103.3)^2) +(8(103-103.3)^2) +(9(103- 103.3)^2) / 20 -1] Xbar = (3(102)+8(103) +9(104)/ 20) Efficiency = total value of output/total value of inputs | CP = (USL – LSL)/ 6s | Mean Control chart : UCL = xbarbar + 3 σ xbar aka mean of sample means + 3σ of σ of sample means: σ/ √ N where N is the # samples per day | Range control: day 1: largest: 20.4, smallest: 20.2, 20.4-20.2= .2 range. Find R = avg range: .2+.2+.3 + .1 / 4 = .2 (the middle line) UCL and LCL are from a chart. multiplicative model where: trend = new mean/ old mean seasonal = [(spring 06/mean06) +(spring 07/mean 07)] / 2 = .7083 | now to forecast: spring 08 : x 07 x trend component x seasonal component for spring. | Additive forecast : Trend = NEW mean – OLD mean Seasonal = (spring06 - xbar06) + (spring 07 - xbar 07)/ 2 | Now to forecast = (most recent actual mean) + (trend) + (seasonal) | actual – forecast = error ∑/n to find MFE (bias, + means forecast too low, if all +, there is an upward trend, - means forecast too high, if all -, there is a downward trend.) | actual – forecast^2 = e^2 ∑/n to find MSE (punish big errors) | abs value of actual – forecast = |e| ∑/n to find MAD (proportional errors) | Data Smoothing : 3 month moving avg, weighted, exponential period forecast actual 1 F1 (last year’s mean) A1 2 F2= α(A1) + (1-α)F1 A2 so (% of actual) + (% of previous forecast) Small α if data is random, big α if data is consistent | Plant size/# OR Choose machines: TC = a+bq +cq^2, ATC = a/q + b +cq, Datc/dq = -a/ q^2 + c = 0, C = a/q^2, Q= √a/c (optimal q per facility), solve for q, and plug into ATC to find $cost/unit to compare machine models. OR find q* per plant and divide into desired total output | Expected Profit: = traffic count X yield X (income – cost per customer) - lease – fixed cost, 90,000 cars pass by. Can be by foot traffic in a mall, different alleys have different traffic. Yield factor: how many of the people enter from the traffic: .005, Monthly lease: $5,000,Expected cost per customer: $22, Upfront costs to setup the site (starbucks design): financed as monthly payment of 25,000/ 3 years = $694 | Facility Layout : Max Cycle time = (total time in workshift) /(total # of units per shift required) this is the max station time. Then pick task from slowest to fastest that will fit. Efficiency: “eyeball” N *actual cycle time – 1to n∑ ti = 3*56 – (56+53+48) = 11 minutes. This is the idle time per cycle, aka time wasted per cycle. Line Efficiency: Formula: e = 1 to n ∑ times needed / divided by # of minutes if everyone was busy = (56+53+48)/ (3*56) x 100% = 93.45% busy | Dominated flow patterns: when different products use the same standard order. Variable flow patterns: when different products don’t follow a standard path ex. hospital. | mass of movement = Mass of movement = # of trips X Weight of avg load X distance (V*W*D), we’ll minimize distance based on weight and usage | Job Design : efficiency school: (GILBRETH- each motion is called a therblig), Behavioral school: Emphasizes worker motivation, Henry Towne wrote an article called “the Engineer as an Economist” argued that we’ve been focusing on all the automated machines and how productive they are but we should look at the economics of WHEN and HOW MANY units we should run the machines.
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This note was uploaded on 04/11/2009 for the course ARE 157 taught by Professor Whitney during the Fall '08 term at UC Davis.

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MT1 note card - strategy major accident 3% minor accident...

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