Learning Curve handout

# Learning Curve handout - Manufacturing Progress Function...

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Unformatted text preview: Manufacturing Progress Function Empirical evidence demonstrates that the # of direct labor hours required to complete a unit of product will decrease by a constant % each time the production quantity is doubled. A manufacturing progress model is an expression of the anticipated reduction in direct labor hours in a manufacturing operation. Manufacturing improvement is some- times referred to as "learning". Improvements may come from direct labor learning, management & support staff, tooling, production methods, scheduling, materials handling, and quality control. The Shape of the Progress Function The manufacturing progress function describes a constant percentage improvement as the production quantities double. A 20% improvement curve means that as production quantities. double, there is a 20% reduction in d.i. hours. Note that the smaller the percent rate of improvement, the greater the progressive improvement with production output. e.g. a 90% rate of improvement means that as production quantities double, the average time per unit will decline 10% a 80% rate of improvement means that as production quantities double, the average time per unit will decline 20% The learning curve begins to flatten once the task is mastered. It is best to determine labor standards then. Other considerations: Performance Rating Effect of relearning (new design may have parts similar to old design) "Learn-Forget” Model (/ 2"?! The Unit Formula X = the unit.# YX = the number of direct labor hours required to produce the Xth unit K = the # of direct labor hours required to produce the tst unit 935 = the slope parameter of the manufacturing progress function n = log ¢J (log of learning percent) log 2 n YX= KX n The equation YX= K X is referred to as a “log-linear” function. When plotted on log-log paper the a straight line results and its ¢ slepe is given by an: 1%,}? _-"" L’qug)? quimmvz an 907C. frojnm ¥Mnt+flﬂﬂa WL'EV-LJ {Aan #1 A+ 302000 (infch dia- é“- LUMI‘J .- jdi‘v‘? 4:01” 73;, PEI}? 1H: a‘F cl. If?(% I lager- Aﬁﬂrd N714er ‘14:: 6M: ’4 {‘j‘le MW?“ W” J M 33—0 =~ {’13 E Z "-d 0; 3‘22 J ,5? 2 7‘: K K —c. 322. 73- "moire-v”) 370030 1 30000 f __ TL # 1 qglqj'z; 310nm g”; I, was? 11 (FF élir’rt+’ [rigor AOL“? N Lair-Ht! méy é-t €xrrrrrrJ 613' H 7N '1‘ 7,+71+;,,+y~,: g7}; ‘ xx: Eﬁomlﬂje \fquﬂﬂq 5-0 “HI-Ell? (Eff rifd'cIH-H’é 451+ E. Cumm1a%a'va ﬁVfrﬁjrﬁ VF ’26 50mm {nor unﬁt: CamrJH—t‘r fl”- ﬁpﬁrni’ﬁ (WNW ffrrf'nllﬁji wﬁen MC} math an»: rrcéareé a‘i' a («mah‘ﬁw Gvrmjf a‘F if 5.9m»: Fer mmf. XI : (gnawing-Elm frail-«({‘LN {a ram‘li one (foam-if} K1: (annual-411;“ (arcémfu-k fa lam-311E {We (’05’iw5ﬁi) E : 2 (IL-f. rrclHi-{H-N \$H‘5‘h—E’4Y ’3 clﬁ'tzgllf‘j) Xi H N f K )1: K1 33- : 2 2 "ET 2 7.” TI K :41” Mg 291 £03 ’5 .. I‘- 301d3~!.1?m‘5 H Mng m a——-——~d—-+—-——~ ‘ ————-—-——-_._‘ "gjﬂrf L93 5:: — iaj 596' Laﬁg‘iw 2.0000 a 0, 30M at“; —CI.":'-'~\$' 2 : 7'4: Afﬁrm-h (HYVQ frfq'rra‘géfr) : ¢ __r'" n 2 Ellog Ylﬁlog x — 210g grim Zﬂegx -~ 2 log MIL/I)2 ElogY—n Elegx IUK: Us M M: 1H: 0,? Ain't; rpfn'ki M 1.4. FITTING THE PROGRESS FUNCTION BY LEAST SQUARES Jog 1’sz03 3: - E Jog foJ The slope can be determined as _ -0.ﬂ74l n — = —0.2432 0.304? are -3133: 1 Y‘I- ...
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Learning Curve handout - Manufacturing Progress Function...

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