The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Cet article concerne la planification des ressources dans une installation d'assemblage VLSI. L'installation peut traiter plus de 100 types d'en-cours (Works-In-Process) simultanément. Plus précisément, il réalise une production de mix de produits. Un ancien système d'estimation des ressources, qui donnait une bonne estimation pour une usine de production de mémoires VLSI, s'est mal révélé pour une usine d'assemblage. Pour ajuster l'estimation des ressources machines requises de l'installation d'assemblage, un nouveau paramètre - la valeur de réglage du temps de service - est introduit. La valeur de réglage exprime la réduction de l'utilisation de la machine dans les étapes de traitement en raison de la combinaison de produits. La valeur est déterminée empiriquement et les ressources en machines peuvent être estimées avec une bonne précision. De plus, le temps d'attente pour le traitement dans le tampon entrant est pris en compte avec succès dans l'estimation du temps d'exécution. Cependant, la valeur de réglage n'est pas suffisante pour estimer les ressources humaines. Un nouvel algorithme pour estimer les ressources nécessaires aux ajustements de la machine est proposé. L'algorithme est basé sur une attribution périodique de plusieurs types d'en-cours dans une seule machine, où les ajustements des machines pour la gamme de produits sont pris en compte. Les ajustements constituent des tâches supplémentaires pour les opérateurs dans la gamme de produits. Il estime le taux de demande de l'opérateur et le taux d'utilisation de la machine lorsque plusieurs types d'en-cours avec des taux d'arrivée différents sont traités sur une seule machine. Enfin, ce système d'estimation des ressources considère l'opérateur affecté non seulement au pré-traitement et au post-traitement mais également aux ajustements des machines pour le mix-produits. Les machines, les ressources humaines et les délais d'exécution estimés ont été évalués dans une installation réelle, et il est confirmé que la méthode proposée est applicable dans la planification hebdomadaire ou mensuelle des ressources de l'installation.
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Sumika ARIMA, Kazuyuki SAITO, "Operator Allocation Planning for a Product-Mix VLSI Assembly Facility" in IEICE TRANSACTIONS on Electronics,
vol. E84-C, no. 6, pp. 832-840, June 2001, doi: .
Abstract: This paper concerns resource planning in a VLSI assembly facility. The facility can process more than 100 sorts of WIPs (Works-In-Process) simultaneously. Specifically it performs product-mix production. An old resource estimation system, which gave a good estimation for a memory VLSI production facility, went wrong for an assembly facility. To adjust the estimation of required machinery resources of the assembly facility, a new parameter--the tuning value for the service time--is introduced. The tuning value expresses the reduction in machine utilization in the processing steps due to the product-mix. The value is empirically determined and the machinery resources can be estimated in good accuracy. Also the waiting time for processing in the incoming buffer is successfully considered in the estimation of turnaround time. However the tuning value is not enough in estimating human resources. A novel algorithm to estimate the resources for machine adjustments is proposed. The algorithm is based on a periodic assignment of multiple sorts of WIPs in a single machine, where the adjustments of machines for the product-mix are considered. The adjustments are additional operator's jobs in the product-mix. It estimates the operator request rate and machine utilization rate when multiple sorts of WIPs with different arrival rates are processed in a single machine. Finally, this resource estimation system considers the operator allocated not only to the preprocessing and postprocessing but also to the adjustments of machines for the product-mix. The estimated machinery, human resources, and turnaround time were evaluated in a real facility, and the proposed method is confirmed to be applicable in the weekly or monthly resource planning for the facility.
URL: https://global.ieice.org/en_transactions/electronics/10.1587/e84-c_6_832/_p
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@ARTICLE{e84-c_6_832,
author={Sumika ARIMA, Kazuyuki SAITO, },
journal={IEICE TRANSACTIONS on Electronics},
title={Operator Allocation Planning for a Product-Mix VLSI Assembly Facility},
year={2001},
volume={E84-C},
number={6},
pages={832-840},
abstract={This paper concerns resource planning in a VLSI assembly facility. The facility can process more than 100 sorts of WIPs (Works-In-Process) simultaneously. Specifically it performs product-mix production. An old resource estimation system, which gave a good estimation for a memory VLSI production facility, went wrong for an assembly facility. To adjust the estimation of required machinery resources of the assembly facility, a new parameter--the tuning value for the service time--is introduced. The tuning value expresses the reduction in machine utilization in the processing steps due to the product-mix. The value is empirically determined and the machinery resources can be estimated in good accuracy. Also the waiting time for processing in the incoming buffer is successfully considered in the estimation of turnaround time. However the tuning value is not enough in estimating human resources. A novel algorithm to estimate the resources for machine adjustments is proposed. The algorithm is based on a periodic assignment of multiple sorts of WIPs in a single machine, where the adjustments of machines for the product-mix are considered. The adjustments are additional operator's jobs in the product-mix. It estimates the operator request rate and machine utilization rate when multiple sorts of WIPs with different arrival rates are processed in a single machine. Finally, this resource estimation system considers the operator allocated not only to the preprocessing and postprocessing but also to the adjustments of machines for the product-mix. The estimated machinery, human resources, and turnaround time were evaluated in a real facility, and the proposed method is confirmed to be applicable in the weekly or monthly resource planning for the facility.},
keywords={},
doi={},
ISSN={},
month={June},}
Copier
TY - JOUR
TI - Operator Allocation Planning for a Product-Mix VLSI Assembly Facility
T2 - IEICE TRANSACTIONS on Electronics
SP - 832
EP - 840
AU - Sumika ARIMA
AU - Kazuyuki SAITO
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Electronics
SN -
VL - E84-C
IS - 6
JA - IEICE TRANSACTIONS on Electronics
Y1 - June 2001
AB - This paper concerns resource planning in a VLSI assembly facility. The facility can process more than 100 sorts of WIPs (Works-In-Process) simultaneously. Specifically it performs product-mix production. An old resource estimation system, which gave a good estimation for a memory VLSI production facility, went wrong for an assembly facility. To adjust the estimation of required machinery resources of the assembly facility, a new parameter--the tuning value for the service time--is introduced. The tuning value expresses the reduction in machine utilization in the processing steps due to the product-mix. The value is empirically determined and the machinery resources can be estimated in good accuracy. Also the waiting time for processing in the incoming buffer is successfully considered in the estimation of turnaround time. However the tuning value is not enough in estimating human resources. A novel algorithm to estimate the resources for machine adjustments is proposed. The algorithm is based on a periodic assignment of multiple sorts of WIPs in a single machine, where the adjustments of machines for the product-mix are considered. The adjustments are additional operator's jobs in the product-mix. It estimates the operator request rate and machine utilization rate when multiple sorts of WIPs with different arrival rates are processed in a single machine. Finally, this resource estimation system considers the operator allocated not only to the preprocessing and postprocessing but also to the adjustments of machines for the product-mix. The estimated machinery, human resources, and turnaround time were evaluated in a real facility, and the proposed method is confirmed to be applicable in the weekly or monthly resource planning for the facility.
ER -