This paper presents a systematic multivariate process capability index （MPCI） method, which may provide references for assuring and improving process quality levels while achieving an overall evaluation of process q...This paper presents a systematic multivariate process capability index （MPCI） method, which may provide references for assuring and improving process quality levels while achieving an overall evaluation of process quality. The system method includes a spatial MPCI model for multivariate normal distribution data, MPCI model based on factor weight for multivariate no-normal distribution application, and MPCI model based on yield foryield application. At last, examples for calculating MPCI are given, and the experimental results show that this systematic method is effective and practical.展开更多
Process capability indices have been widely used in the manufacturing industry,providing numerical measures on process precision,process accuracy,and process performance.Capability measures for processes with a single...Process capability indices have been widely used in the manufacturing industry,providing numerical measures on process precision,process accuracy,and process performance.Capability measures for processes with a single characteristic have been investigated extensively.However,capability measures for processes with multiple characteristics are comparatively neglected. In this paper,inspired by the approach and model of process capability index investigated by K.S.Chen et al.(2003) and A.B. Yeh et al.(1998),a note model of multivariate process capability index based on non-conformity is presented.As for this index, the data of each single characteristic don’t require satisfying normal distribution,of which its computing is simple and particioners will not fell too theoretical.At last the application analysis is made.展开更多
The existing research of process capability indices of multiple quality characteristics mainly focuses on nonconforming of process output, the concept development of tmivariate process capability indices, quality loss...The existing research of process capability indices of multiple quality characteristics mainly focuses on nonconforming of process output, the concept development of tmivariate process capability indices, quality loss function and various comprehensive evaluation methods. The multivariate complexity increases the computation difficulty of multivariate process capability indices（MPCI）, which makes them hard to be used in practice. In this paper, a new PCA-based MPCI approach is proposed to assess the production capability of the processes that involve multiple product quality characteristics. This approach first transforms the original quality variables into standardized normal variables. MPCI measures are then provided based on the Taam index. Moreover, the statistical properties of these MPCIs, such as confidence intervals and lower confidence bound, are given to let the practitioners understand the capability indices as random variables instead of deterministic variables. A real manufacturing data set and a synthetic data set are used to demonstrate the effectiveness of the proposed method. An implementation procedure is also provided for quality engineers to apply our MPCI approach in their manufacturing processes. The case studies demonstrate the effectiveness and feasibility of this new kind of MPCI, which is easier to be used in production practice. The proposed research provides a novel approach of MPCI calculation.展开更多
After analyzing the multivariate Cpm method （Chan et al. 1991）, this paper presents a spatial multivariate process capability index （PCI） method, which can solve a multivariate off-centered case and may provide re...After analyzing the multivariate Cpm method （Chan et al. 1991）, this paper presents a spatial multivariate process capability index （PCI） method, which can solve a multivariate off-centered case and may provide references for assuring and improving process quality level while achieving an overall evaluation of process quality. Examples for calculating multivariate PCI are given and the experimental results show that the systematic method presented is effective and actual.展开更多
In this article, we studied the bearings made by one company in Shanghai. Through statistical process controlling the quality characteristic of bearings’ diameters and multi-vary analysis is applied to find the key v...In this article, we studied the bearings made by one company in Shanghai. Through statistical process controlling the quality characteristic of bearings’ diameters and multi-vary analysis is applied to find the key variation factors which have an influence on the quality characteristic of the bearings, the quality level of the bearings of this company is improved.展开更多
This study provides a framework of target costing to extend its original scope when the underlying distribution is non-normal. The new specification limits can be derived by listening to the market price from Taguchi ...This study provides a framework of target costing to extend its original scope when the underlying distribution is non-normal. The new specification limits can be derived by listening to the market price from Taguchi loss function. Later, the new specification limits can be linked through the non-normality-based C^^pk value along with non-normality-based X^^-Rcontrol charts to derive goal control limits. Moreover, an example is provided to illustrate the usefulness of the proposed framework of target costing by relentlessly reducing cost and improving product quality to gain competitiveness in the marketplace.展开更多
文摘This paper presents a systematic multivariate process capability index （MPCI） method, which may provide references for assuring and improving process quality levels while achieving an overall evaluation of process quality. The system method includes a spatial MPCI model for multivariate normal distribution data, MPCI model based on factor weight for multivariate no-normal distribution application, and MPCI model based on yield foryield application. At last, examples for calculating MPCI are given, and the experimental results show that this systematic method is effective and practical.
基金Contract/grant sponsor:China National Key Laboratory for analog IC(51439040103DZ0102)
文摘Process capability indices have been widely used in the manufacturing industry,providing numerical measures on process precision,process accuracy,and process performance.Capability measures for processes with a single characteristic have been investigated extensively.However,capability measures for processes with multiple characteristics are comparatively neglected. In this paper,inspired by the approach and model of process capability index investigated by K.S.Chen et al.(2003) and A.B. Yeh et al.(1998),a note model of multivariate process capability index based on non-conformity is presented.As for this index, the data of each single characteristic don’t require satisfying normal distribution,of which its computing is simple and particioners will not fell too theoretical.At last the application analysis is made.
基金supported by National Natural Science Foundation of China(Grant Nos.70802043,71225006 and 71002105)
文摘The existing research of process capability indices of multiple quality characteristics mainly focuses on nonconforming of process output, the concept development of tmivariate process capability indices, quality loss function and various comprehensive evaluation methods. The multivariate complexity increases the computation difficulty of multivariate process capability indices（MPCI）, which makes them hard to be used in practice. In this paper, a new PCA-based MPCI approach is proposed to assess the production capability of the processes that involve multiple product quality characteristics. This approach first transforms the original quality variables into standardized normal variables. MPCI measures are then provided based on the Taam index. Moreover, the statistical properties of these MPCIs, such as confidence intervals and lower confidence bound, are given to let the practitioners understand the capability indices as random variables instead of deterministic variables. A real manufacturing data set and a synthetic data set are used to demonstrate the effectiveness of the proposed method. An implementation procedure is also provided for quality engineers to apply our MPCI approach in their manufacturing processes. The case studies demonstrate the effectiveness and feasibility of this new kind of MPCI, which is easier to be used in production practice. The proposed research provides a novel approach of MPCI calculation.
基金Project supported by the Natural Science Foundation of Shaanxi Province(No.2012JQ8048)the Basic Research Foundation of North-western Polytechnical University(No.JC20110232)
文摘After analyzing the multivariate Cpm method （Chan et al. 1991）, this paper presents a spatial multivariate process capability index （PCI） method, which can solve a multivariate off-centered case and may provide references for assuring and improving process quality level while achieving an overall evaluation of process quality. Examples for calculating multivariate PCI are given and the experimental results show that the systematic method presented is effective and actual.
文摘In this article, we studied the bearings made by one company in Shanghai. Through statistical process controlling the quality characteristic of bearings’ diameters and multi-vary analysis is applied to find the key variation factors which have an influence on the quality characteristic of the bearings, the quality level of the bearings of this company is improved.
文摘This study provides a framework of target costing to extend its original scope when the underlying distribution is non-normal. The new specification limits can be derived by listening to the market price from Taguchi loss function. Later, the new specification limits can be linked through the non-normality-based C^^pk value along with non-normality-based X^^-Rcontrol charts to derive goal control limits. Moreover, an example is provided to illustrate the usefulness of the proposed framework of target costing by relentlessly reducing cost and improving product quality to gain competitiveness in the marketplace.
