Manufacturing Progress Functions for Types of Processes

Nadler, Gerald; Smith, Wayne D.

doi:10.1080/00207546308947818

Cited by 55 publications

(19 citation statements)

References 3 publications

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“…Most of these have been summarized by Nadler and Smith (1963), Glover (1966), Pegels (1969), Steedman (1970), Bevis et al (1970), and Miller (1971).…”

Section: )mentioning

confidence: 98%

A learning curve prediction model for operators performing industrial bench assembly operations

Bohlen

Barany

1976

International Journal of Production Research

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Learning curves of operators performing industrial operations vary according to the characteristics of the operator and the characteristics of the operation being performed.In this paper a method is developed to enable prediction of a specific learning curve of the function Y = c+ a( 1-exp -b(t -L)) for a. specific operator performing a specific operation. This specific curve is based on certain measurements of the operator and certain measurements of the operation. IntroductionLearning curves can be characterized as graphical descriptions of the level of achievement (i.e. performance) attained during the learning period. Learning curves for industrial operations are generally of two types. The first type refers to the learning by an individual and is sometimes referred to as , acquisition of skill'. The second type refers to the learning by whole systems of men and machines and is usually referred to as the manufacturing progress function (Glover] 966).A number of authors have set forth various mathematical functions to describe learning curves. Most of these have been summarized by .Most learning curve research has focused on curves which have trials or repetitions or cycles on the X axis and time required to perform the cycle on the Y axis. The curve then indicates the time required for each cycle and indicates that this time decreases as the number of cycles increases.It would appear, however, that a more useful form of the learning curve for representing an industrial operator's output is one which has time Oll the X axis and output (in cycles per unit time) on the Yaxis. Specifically,' days' might be the units on the X axis and production output in ' units per day' on the Y axis. This is especially true where a company measures an operator's output on a time (e.g. daily) basis.Learning curves for industrial operators performing assembly tasks appear to be influenced primarily by the oharacteristios of the specific operator and the specific operation being performed.In this paper a means of predicting, in advance, the learning curve of a specific operator performing a specifie assembly operation is developed using certain' measurements' of the operator and' measurements' of the operation.

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“…Most of these have been summarized by Nadler and Smith (1963), Glover (1966), Pegels (1969), Steedman (1970), Bevis et al (1970), and Miller (1971).…”

Section: )mentioning

confidence: 98%

A learning curve prediction model for operators performing industrial bench assembly operations

Bohlen

Barany

1976

International Journal of Production Research

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“…This phenomenon is called the learning effect and research on its presence in manufacturing systems and on advantages following from that fact are being continuously carried out from 1936 (e.g. Argote, 1996;Jackson, 1998;Keachie & Fontana, 1966;Nadler & Smith, 1963;Yelle, 1979;Young, 1991), when this phenomenon was discovered in aircraft industry by Wright (1936). Nevertheless, the learning effect has attracted particular attention in scheduling just only during the last decade as it became clear that scheduling problems with the learning effect allow to describe many settings that occur inter alia in manufacturing, management, businesses and services sectors (for a survey see Biskup, 2008;Janiak & Rudek, 2009).…”

Section: Introductionmentioning

confidence: 99%

Computational complexity and solution algorithms for flowshop scheduling problems with the learning effect

Rudek

2011

Computers & Industrial Engineering

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“…Learning cost: if a worker has to perform different tasks-either because the cycle time is long or because the line is a flexible one in which different models require different operations-then the number of repetitions per period is considered to be low and the learning effect causes a decrease in productivity that can be translated into what is known as the learning cost [Nadler and Smith (1963) estimate this cost using learning curves in which the time needed to complete a task depends on the number of times that task has been performed].…”

Section: Multiple or Parallel Line Balancing Problemsmentioning

confidence: 99%

A survey of the literature on the multiple or parallel assembly line balancing problem

Lusa

2008

EJIE

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Manufacturing Progress Functions for Types of Processes

Cited by 55 publications

References 3 publications

A learning curve prediction model for operators performing industrial bench assembly operations

A learning curve prediction model for operators performing industrial bench assembly operations

Computational complexity and solution algorithms for flowshop scheduling problems with the learning effect

A survey of the literature on the multiple or parallel assembly line balancing problem

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