๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Operator-specific model: An assembly time prediction model

โœ Scribed by Lynn A. Fish; Colin G. Drury; Martin G. Helander


Publisher
John Wiley and Sons
Year
1997
Tongue
English
Weight
1015 KB
Volume
7
Category
Article
ISSN
1090-8471

No coin nor oath required. For personal study only.

โœฆ Synopsis


A model was developed to predict assembly time for a circuit board assembly task. It was based upon the GOMS language developed for task time prediction in human-computer interaction. It incorporated sequential elements of information processing, defined by cognitive, motor, and perceptual processors, in a critical path network. The model was used to predict assembly time for four assembly strategies using four different combinations of workstation and assembly sequences. The model was useful in predicting cognitive changes associated with the development of expertise. As assemblers gained experience, structural changes in the network implied that several processors were chunked.


๐Ÿ“œ SIMILAR VOLUMES


Modeling and analysis of a mixed-model a
โœ Xiaobo Zhao; Jianyong Liu; Katsuhisa Ohno; Shigenori Kotani ๐Ÿ“‚ Article ๐Ÿ“… 2007 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 138 KB

## Abstract We consider a mixedโ€model assembly line (MMAL) comprised a set of workstations and a conveyor. The workstations are arranged in a serial configuration. The conveyor moves at a constant speed along the workstations. Initial units belonging to different models are successively fed onto th

An approximated principal component pred
โœ Aguilera, Ana M. ;Ocaรฑa, Francisco A. ;Valderrama, Mariano J. ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 196 KB ๐Ÿ‘ 2 views

In this paper, a linear model for forecasting a continuous-time stochastic process in a future interval in terms of its evolution in a past interval is developed. This model is based on linear regression of the principal components in the future against the principal components in the past. In order

A spaceโ€“time model for seasonal hurrican
โœ Thomas H. Jagger; Xufeng Niu; James B. Elsner ๐Ÿ“‚ Article ๐Ÿ“… 2002 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 180 KB

## Abstract A spaceโ€“time count process model is explained and applied to annual North Atlantic hurricane activity. The model uses the bestโ€track data set of historical hurricane positions and intensities, together with climate variables, to determine local spaceโ€“time coefficients of a rightโ€truncat