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Details van artikel 17 van 18 gevonden artikelen
| Titel: |
Predicting performance times for long cycle time tasks |
| Auteur: |
Dar-El, E.M. Ayas, K. Gilad, I. |
| Verschenen in: |
IIE transactions |
| Paginering: | Jaargang 27 (1995) nr. 3 pagina's 272-281 |
| Jaar: |
1995-06-01 |
| Inhoud: |
A long cycle time task is assumed to consist of a series of non-repetitive unique sub-tasks whose standard times average at about 1 ½ minutes. 'Forgetting' is therefore a consequence of a specific sub-task reappearing in the next cycle after a whole cycle time of other activities is completed. Learning behavior of long cycle tasks is therefore predicted on the learning of its constituent sub-tasks. A method for predicting the learning curve parameters for the sub-tasks (the learning constant, and execution time of the first repetition) are proposed and tested. The extent of 'forgetting' is empirically determined as a function of the learning constant and interruption length. Finally, a model is developed for predicting execution times for long cycle tasks. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 17 van 18 gevonden artikelen
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