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Ch 61 IT-390Preliminary and Detail Methods. 2 Design and Evaluation ä Preliminary Estimate requested during the initial evaluation for several reasons:

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Presentation on theme: "Ch 61 IT-390Preliminary and Detail Methods. 2 Design and Evaluation ä Preliminary Estimate requested during the initial evaluation for several reasons:"— Presentation transcript:

1 Ch 61 IT-390Preliminary and Detail Methods

2 2 Design and Evaluation ä Preliminary Estimate requested during the initial evaluation for several reasons: ä 1) Investigate the validity of the project ä 2) Clarify direction or change direction ä 3) To allow proper preparation

3 3 Design and Evaluation ä Preliminary Estimates - limited facts specifics ä ROM (Rough Order of Magnitude) ä Methods used are: ä 1) Rules of thumb (heuristic approach) ä 2) Simple calculations

4 4 Design and Evaluation ä Preliminary Estimates ä less than accurate ä Dollarless in value ä No substantial foundation ä Invaluable to continuing or terminating the operation, project, product, or system estimate in whole or part.

5 5 Design and Evaluation ä Detail Estimates are normally a "re- estimate” ä Re-estimate of the Preliminary Estimate ä More discrete information ä Increased accuracy ä Greater legitimacy of analysis (Mathematical/Factual)

6 6 Opinion ä Opinion - judgment or belief stronger than a perception, but weaker than positive knowledge. ä 1) Natural part, but not uneducated ones ä 2) Capable, experienced engineer - good working knowledge ä 3) Natural/Planned experiences ä common sense, judgment, observations, gut feelings, all of which can also be done collectively (with others).

7 7 Conference ä Conference is formulating an educated opinion collectively with "others". ä A consensus (agreement) reached ä "others" - knowledge in specific areas ä engineers only - individual designs (model of estimation) ä Downfall - lack of adequate analysis and verifiable facts

8 8 Comparison ä Similar to "Conference" but uses formal "Logic” ä Compare to similar item(s)

9 9 Unit ä Most popular ä Average ä Rough Order of magnitude (ROM) ä Lump sum ä Module estimating ä Examples of unit estimates include: ä $/sq. foot (the / means “per”) ä $/pound ä $/machine shop man hour

10 10 Learning ä Idea - more often an operation is performed, less time will be required to complete it ä Repetition results in less time or effort expended ä The improved performance is called "Learning"

11 11 Learning ä Identifying Situations for Use of Learning ä Not used in all situations ä Must have ä opportunity for improvement ä reduction in labor hours per unit

12 12 Learning ä Use of the improvement curve should be considered in situations where there is: ä A high proportion of manual labor ä Uninterrupted production ä Production of complex items ä No major technological change ä Continuous pressure to improve

13 13 Learning ä Factors that Support Improvement ä Job Familiarization by Workers ä Improved Production Procedures ä Improved Tooling and Tool Coordination ä Improved WorkFlow Organization ä Improved Product Producibility ä Improved Engineering Support ä Improved Parts Support

14 14 Learning ä First application - manufacture of airframes ä Costs lowered with increasing quantity of production or experience ä Rate of improvement is 20% between doubled quantities ä Therefore, learning curve is 80% or, 2nd unit will take 80% labor of what it took on 1st unit

15 15 Learning ä Other names for learning include: ä Manufacturing progress function ä Experience or dynamic curve

16 16 Learning ä The learning model is based on 3 assumptions: ä 1) Amount of time or cost required to complete a unit of product is less each time the task is undertaken ä 2) Unit time will decrease at a decreasing rate (in other words, the time reduction will slow as time moves on) ä 3) Reduction in unit time follows the model y = ax b (curvilinear from Ch 5)

17 17 Learning ä The underlying hypothesis says: "The direct labor man hours necessary to complete a unit of product will decrease by a constant percentage each time the production quantity is doubled."

18 18 Learning Curve Example

19 19 Learning ä Several equations in this section are useful to us: ä 1)Eq. ä 2)Eq. 6.9, pg. 259 ä 3)Eq. 6.13, pg. 261 ä 4)Eq.

20 20 Learning ä Where for each, ä T = effort per unit of production ä N = unit number ä S = slope of improvement rate, a constant ä K = Constant, for unit 1, dimensions compatible to T ä  = the percent learning as a decimal ä These all assume that (Ni, Ti) and (Nj, Tj) are two points on a log - log curve (straight line) of "N" vs "T" T N Effort. Labor Rate, etc. Unit # (Ti,Ni) (Tj,Nj)

21 21 Learning ä Problem 6.27, pg 294, ä Supplemental Problem ä For the following problems, assume that the unit line is linear. ä Find the first unit value when the 100 th unit is 60 hours with 81% learning. ä Find the value for unit 6 when unit 3 is 1000 hours with 74% learning. ä If the unit value at number 1 $2000, then find the unit dollars for units 20 and 40 with learning rates of 93% and 100%. ä If the cumulative average time at unit 100 is 100, then find the unit, cumulative, and average time at unit 101 for a learning rate of 92%.

22 22 Learning ä Calculated by regression models since data of many points are required ä There are two approaches to learning curves: ä 1) The Wright (cumulative average) system ä 2) The Boeing (unit) system

23 23 Learning ä Ostwald refers to the Crawford system as the "Boeing" system ä In Fig. 6.4 (pg. 258) ä Two systems so it's important to know what data has been collected ä Is it for unit cost or cumulative average cost? ä Each requires a different system and a different set of equations

24 24 Learning ä Wright SystemBoeing System ä cumulative average per unit cumulative average ä Tá = KN s Ta = KN s / (1+s) ä cumulative total effort from unit 1 - N cumulative total ä Tć= KN s+1 Tc = T u or Tc = (T a )(N) ä unit effort unit effort ä Tú = KN s+1 -K(N-1) s+1 Tu = KN s ä Notes: Plot of Tá & Tu are assumed to be linear. ä The “T” in Tá is for time. For cost we could have used a “C” as in Cá, but for simplicity, we will leave the equations as “T”s even when dealing with cost. N = unit number S = slope of improvement rate, a constant K= constant, for unit one

25 25 Learning ä Values in Appendix 5, pg. 553 ä Assumption - "cumulative average" data have been collected and plotted to form the straight line in regression analysis (Wright system)

26 26 Learning ä Example of Wright and Boeing Methods

27 27 Learning ä Slope - determined from historical/predicted from experience ä Minimal improvement in "hard" tooling VS manual labor

28 28 Learning ä Learning curve values typical of general industry groups as of 1995 were: ä Aerospace85% ä Shipbuilding80-85% ä Complex machine tools for new models 75-85% ä Repetitive electronics mfg.90-95% ä Repetitive machining or punch-press oper.90-95% ä Repetitive clerical operations75-85% ä Repetitive welding operations90% ä Construction operations70-90% ä Raw materials93-96% ä Purchased parts85-88%

29 29 Learning ä Theoretical First Unit (TFU) Cost + an estimate of the learning curve slope = a cost estimate in (Ch 8) ä 1) Risk Method - Both the TFU and learning curve slope are estimates ä 2) If slope of the curve is off only +/-5%, at the 1000th unit, estimate is off by 68% ä 3) The TFU cost is the cost (in dollars or man hours) to produce unit #1 ä 4) "theoretical" since rarely will the cost of the first unit produced match this figure ä 5) Why? Because we typically build several prototypes before reaching the 1st unit that have the effect of lowering its cost


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