Talk:Experience curve effects

message: A related, but subtly different, I think, idea, is the relationship between efficiency for a method compared to another method on different time scales.  For instance, a macintosh one-button mouse and GUI is much more efficient on short time scales but a complicated keystroke-based thingy like vim is more efficient on long timescales after becoming comfortable with it.  (I don't like either.)  Similarly, a chording keyboard can theoretically be used more quickly than a regular computer keyboard, but the time it takes to learn makes it unusable in the short term, compared to hunt and peck typing.  Is there a word for this concept? - Omegatron 23:11, May 8, 2005 (UTC)
:This is spoken about as the difference between the "learning phase" and the "automated phase" in this article: http://jef.raskincenter.org/humane_interface/summary_of_thi.html - Omegatron 02:47, Jun 17, 2005 (UTC)
::A relevant quote from Abraham Lincoln:
::If I had six hours to chop down a tree, I'd spend the first four hours sharpening the axe.
::This illustrates the tradeoff between preparation time vs. execution time for a given task. The more trees one needs to chop, the greater the return on a unit of axe-sharpening time. — Teratornis 14:52, 23 August 2006 (UTC)
replies: text: Another is (paraphrasing) "Given ten hours to accomplish a task, an engineer will spend nine hours learning to do it in one hour." - 209.130.150.117 04:58, 4 March 2007 (UTC)
thread_title:  Sharpening the axe vs. chopping the tree 

message: The article states "Each time cumulative volume doubles, ... costs ... fall by a constant ... percentage".  This would imply that mathematically the effect approximates a power law:
:c=Bv^{-\alpha} \,
where v is volume, c is cost, and B and \alpha > 0 are constants.  In fact it is more likely that
:c=A+Bv^{-\alpha} \,
where A is an asymptotic unit cost greater than zero.
Another possibility is that "each time cumulative volume increases by a fixed amount, costs fall by a constant percentage": this would imply that costs decay exponentially, with formula 
:c=A+Be^{-\beta v} \,
Is there evidence for one of these "laws" over another?
Note that for the related area of response time in individual learning of repeated tasks, Heathcote, Brown and Mewhort in their paper The Power Law repealed: the case for an Exponential Law of Practice make a case via statistical analysis that an exponential law usually gives a better approximation to the observed data than a power law does.  - JimR 06:57, 14 July 2005 (UTC)
thread_title: Power law or exponential law?

message: Note that http://www.maaw.info/LearningCurveSummary.htm states that in Wright's original model the cost involved is not the unit cost of the last unit, but the cumulative average unit cost.  The article does not mention this point at present.  I'm not sure if this makes a big enough difference to need remedying.  Any ideas? (More generally, in the apparent absence of pointers to evidence of experimental verification of the effect in practice, I wonder whether the precision of the numerical form of the curve is really justified.) - JimR 07:18, 16 July 2005 (UTC)
thread_title: Cumulative average cost?

message: Isn't Moore's law a special case of this?
:From the consumer's point of view, sort of (except that the consumer is getting different products as Moore's law grinds ahead, not exactly the same product at successively lower costs). From the producer's point of view, not quite. A quote from the Moore's law article:
:As the cost to the consumer of computer power falls, the cost for producers to achieve Moore's Law has the opposite trend: R&D, manufacturing, and test costs have increased steadily with each new generation of chips. As the cost of semiconductor equipment is expected to continue increasing, manufacturers must sell larger and larger quantities of chips to remain profitable. (The cost to tape-out a chip at 0.18um was roughly $300,000 USD. The cost to tape-out a chip at 90nm exceeds $750,000 USD, and the cost is expected to exceed $1.0M USD for 65nm.) — Teratornis 15:11, 23 August 2006 (UTC)
thread_title: Moore's Law

message: see de:Lernkurve --Espoo 20:58, 29 June 2006 (UTC)
replies: text: Historisch gesehen stammt der Begriff der Lernkurve von Hermann Ebbinghaus (1885), der das Konzept der Lernkurve in seiner Monografie "Über das Gedächtnis" vermutlich als Erster verwendete und somit als Erfinder gelten dürfte. In der Psychologie wird der Begriff der Lernkurve mitunter ohne strikte Definition der x- und y-Achsenzuordnung angewandt, sodass die Frage der Steilheit anhand konkreter Beispiele betrachtet werden muss. Eine erste strikte Definition des Begriffs für die Anwendung in der Betriebswirtschaft stammt von Wright (1927).
It seems to state that the idea of the Learning Curve (Lernkurve) stems from Ebbinghaus in 1885, long before Wright in 1927.  But what's the difference between de:Lernkurve and de:Erfahrungskurve?  -- JimR 05:57, 1 July 2006 (UTC)
thread_title:  Ebbinghaus? 

message: Should this be merged into Learning curve? --Jcbutler (talk) 20:31, 19 September 2008 (UTC)
replies: text: As this article and the one on "experience curve" addresses the same topic. A merge would (and redirect of learning curve to here, or vice versa) produce a more comprehensive article to the benefit of all Wikipedia readers. Editor br (talk) 11:37, 9 January 2009 (UTC)
thread_title:  Why two articles? 

message: "Cumulative" is misspelled twice as "Cumulatve" in the chart labels.  —Preceding unsigned comment added by Firebird (talk • contribs) 17:48, 24 January 2010 (UTC)
thread_title:  "Cumulative" is misspelled twice as "Cumulatve" in the chart labels. 

message: I find confusing and partially incorrect the following text from the "Unit curve" section as of 2016-12-24:  
This equation describes the basis for what is called the unit curve. In this equation, Y represents the cost of a specified unit in a production run. For example, If a production run has generated 200 units, the total cost can be derived by taking the equation below and applying it 200 times (for units 1 to 200) and then summing the 200 values. This is cumbersome and requires the use of a computer or published tables of predetermined values. [The following information may be helpful:  When the equation for Yx below is associated with a unit improvement curve it is called a Crawford unit curve.  When exactly the same equation for Yx below is called a cumulative average learning curve, it is called a Wright cumulative average. To calculate a Wright xth unit cost, Px, from its cumulative average, we have 
:P_x = x Y_x - (x-1) Y_{x-1}  
because in this case 
:Y_x = \frac{P_1 + P_2 + \cdots + P_x}{x}.
Now the equation for the unit curve is given by:
:Y_x = K x^{\log_2 (b)}
where
* K is the number of direct labour hours to produce the first unit
* Yx is the number of direct labour hours to produce the xth unit
* x is the unit number
* b is the learning percentage (expressed as a decimal)
::In particular, in the first two set-off lines of math, Yx is the cumulative average learning cost with Px being the cost of unit x.  However in the last set-off line of math, Yx is the cost of unit x.  I propose to delete the reference to Yx and leave the following:  
:::Empirical research has validated the following mathematical form for the unit cost, Px, producing unit number x starting with P1:  
::::P_x = P_1 x^{\log_2 (b)}, 
:::where (1-b) is the proportion reduction in the unit cost with each doubling in the cumulative production.  To see this, not the following:  
::::P_2x = P_1 (2x)^{\log_2 (b)} = P_x 2^{\log_2 (b)} = P_x b 
:::Of course, this is only a statistical average and will rarely if ever exactly predict the unit cost of producing any future product.  However, it has been found to be useful in many contexts.  
::I apologize if this creates other problems with this article.  If it does, I trust someone will correct those problems.  However, I hope no one will just revert these edits and restore the above text that I found erroneous.  Thanks, DavidMCEddy (talk) 03:02, 25 December 2016 (UTC)
thread_title:  Unit curve confusion 

message: I'm deleting the subsection of "Learning curve and learning curve effect" discussing "Cumulative Average Curve", because it seems to contain fundamental errors that I'm not able to fix at this time.  As of 2016-12-24 it read as follows:  
This equation describes the basis for the cumulative average or cum average curve. In this equation, Y represents the average cost of different quantities (X) of units. The significance of the "cum" in cum average is that the average costs are computed for X cumulative units. Therefore, the total cost for X units is the product of X times the cum average cost. For example, to compute the total costs of units 1 to 200, an analyst could compute the cumulative average cost of unit 200 and multiply this value by 200. This is a much easier calculation than in the case of the unit curve.
:\overline{Y_x} = K\frac{\frac{1}{1+\log_2(b)}x^{1+\log_2(b)}}{x}
where
* K is the number of direct labour hours to produce the first unit
* Yx is the average number of direct labour hours to produce first x units
* x is the unit number
* b is the learning percentage
** My concern:  Consider the case x = 1:  By the definition of k, we should have the following:  
:\overline{Y_1} = K
Instead, we have the following:  
:\overline{Y_1} = K\frac{1}{1+\log_2(b)}
This is only true of b = 1, not for arbitrary positive b less than 1.  
As I wrote in the previous section a few minutes ago, I apologize if this creates other problems with this article.  If it does, I trust someone will correct those problems.  However, I hope no one will just revert these edits and restore the above text that I found erroneous.  Thanks, DavidMCEddy (talk) 03:54, 25 December 2016 (UTC)
thread_title:  Errors in discussion of  Cumulative Average Curve

message: One more edit:  I'm deleting the reference to "Equations 1 and 2" from the following line:  "The Learning Curve model posits that for each doubling of the total quantity of items produced, costs decrease by a fixed proportion, as described by Equations 1 and 2."  Wikipedia style does not use equation numbers.  I don't know what these refer to.  I hope this makes the article easier to read and more intelligible.  
Thanks to all who brought the article to this point.  It's generally quite useful, I think -- averaging 200 page views per day over the past 90 days.  It's worth trying to make it easier to read.  I hope I've done that (and not the opposite).  Thanks, DavidMCEddy (talk) 04:00, 25 December 2016 (UTC)
thread_title:  Equations 1 and 2 

message: Not clear what is the difference between these articles Ita140188 (talk) 11:36, 22 April 2024 (UTC)
thread_title:  Proposed merge of [[Learning curve]] with [[Experience curve effects]]