Process capability indices are routinely used to estimate the mean-variability performance of industrial products with respect to both targets and specification limits. However, when the target variable is defined over a planar surface of a manufact, it is relevant to assess the capability of the production process locally, that is, at any spatial location of the surface, in particular if the manufact has to be split into pieces to obtain single production items. In this article, focusing on the specification introduced by Clements [Qual Prog., 22, 95–100], we suggest an approach based on additive quantile models to estimate, in a Bayesian paradigm, the index locally. We demonstrate its use in the context of the etching phase of the integrated circuit fabrication process. Since capability of etching processes is typically assessed for batches of wafers, we also propose two algorithms based on resampling to perform local capability analysis at the lot level.

Borgoni, R., Farace, V., & Zappa, D. (2022). Non‐parametric local capability indices for industrial planar manufacts: An application to the etching phase in the microelectronic industry. APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY [10.1002/asmb.2673].

Non‐parametric local capability indices for industrial planar manufacts: An application to the etching phase in the microelectronic industry

Borgoni, Riccardo
Primo
;
Farace, Vincenzo Emanuele;
2022

Abstract

Process capability indices are routinely used to estimate the mean-variability performance of industrial products with respect to both targets and specification limits. However, when the target variable is defined over a planar surface of a manufact, it is relevant to assess the capability of the production process locally, that is, at any spatial location of the surface, in particular if the manufact has to be split into pieces to obtain single production items. In this article, focusing on the specification introduced by Clements [Qual Prog., 22, 95–100], we suggest an approach based on additive quantile models to estimate, in a Bayesian paradigm, the index locally. We demonstrate its use in the context of the etching phase of the integrated circuit fabrication process. Since capability of etching processes is typically assessed for batches of wafers, we also propose two algorithms based on resampling to perform local capability analysis at the lot level.
No
Articolo in rivista - Articolo scientifico
Scientifica
Bayesian semiparametric quantile regression; dry etching; microelectronics; thin plate spline;
English
Borgoni, R., Farace, V., & Zappa, D. (2022). Non‐parametric local capability indices for industrial planar manufacts: An application to the etching phase in the microelectronic industry. APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY [10.1002/asmb.2673].
Borgoni, R; Farace, V; Zappa, D
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10281/354373
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