scholarly journals Process Quality Evaluation Model with Taguchi Cost Loss Index

2021 ◽  
Vol 11 (21) ◽  
pp. 10182
Author(s):  
Chiao-Tzu Huang ◽  
Kuei-Kuei Lai
Keyword(s):  
Confidence Interval ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Process Capability ◽  
Process Quality ◽  
Statistical Testing ◽  
Process Capability Indices ◽  
Capability Indices ◽  
Loss Index ◽  
Quality Evaluation Model

Process Capability Indices (PCIs) are not only a good communication tools between sales departments and customers but also convenient tools for internal engineers to evaluate and analyze process capabilities of products. Many statisticians and process engineers are dedicated to research on process capability indices, among which the Taguchi cost loss index can reflect both the process yield and process cost loss at the same time. Therefore, in this study the Taguchi cost loss index was used to propose a novel process quality evaluation model. After the process was stabilized, a process capability evaluation was carried out. This study used Boole’s inequality and DeMorgan’s theorem to derive the (1 – α) ×100% confidence region of (δ,γ2) based on control chart data. The study adopted the mathematical programming method to find the (1 – α) ×100% confidence interval of the Taguchi cost loss index then employed a (1 – α) ×100% confidence interval to perform statistical testing and to determine whether the process needed improvement.

Analyzing processing quality of machine tools via processed product: Example of ball valve processing machine

2020 ◽  
Vol 234 (4) ◽  
pp. 331-341 ◽  
Author(s):  
Kuen-Suan Chen ◽  
Der-Fa Chen ◽  
Ming-Chieh Huang ◽  
Tsang-Chuan Chang
Keyword(s):  
Machine Tools ◽  
Process Capability ◽  
Quality Characteristics ◽  
Process Quality ◽  
Quality Analysis ◽  
Process Capability Indices ◽  
Processing Quality ◽  
Accuracy And Precision ◽  
Capability Indices

Machine tools are fundamental equipment in industrial production, and their processing quality exerts a direct impact on the quality of the component product that they process. Thus, machine tool manufacturers develop various machine tools depending on market needs and processing functions, and the processed component products generally possess multiple smaller-the-better, larger-the-better, and nominal-the-best quality characteristics at the same time. For this reason, this study employed the widely used process capability indices, [Formula: see text], [Formula: see text], and [Formula: see text] to develop a model that can evaluate the process quality of component products and analyze the processing quality of various machine tools. We first converted the process capability indices into functions of the accuracy and precision indices and constructed a multi-characteristic quality analysis chart that can identify the reason for poor process quality in a quality characteristic. Furthermore, considering the fact that the process capability indices can only be estimated, which may lead to misjudgment in the evaluation of process quality, we derived the [Formula: see text] upper confidence limits of indices and the coordinates formed by the corresponding accuracy and precision indices. Manufacturers can then evaluate the process quality levels of the quality characteristics based on where the coordinates falls in the multi-characteristic quality analysis chart. This can more reliably assist manufacturers in monitoring the processing quality of their machine tools and providing feedback to the machine tool manufacturers for machine improvement.

scholarly journals Fuzzy Quality Evaluation Model Constructed by Process Quality Index

2021 ◽  
Vol 11 (23) ◽  
pp. 11262
Author(s):  
Chun-Min Yu ◽  
Chih-Feng Wu ◽  
Kuen-Suan Chen ◽  
Chang-Hsien Hsu
Keyword(s):  
Quality Index ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Process Quality ◽  
Small Sample ◽  
Sample Sizes ◽  
Sampling Errors ◽  
Process Yield ◽  
Small Sample Sizes ◽  
Quality Evaluation Model

Many studies have pointed out that the-smaller-the-better quality characteristics (QC) can be found in many important components of machine tools, such as roundness, verticality, and surface roughness of axes, bearings, and gears. This paper applied a process quality index that is capable of measuring the level of process quality. Meanwhile, a model of fuzzy quality evaluation was developed by the process quality index as having a one-to-one mathematical relationship with the process yield. In addition to assessing the level of process quality, the model can also be employed as a basis for determining whether to improve the process quality at the same time. This model can cope with the problem of small sample sizes arising from the need for enterprises’ quick response, which means that the accuracy of the evaluation can still be maintained in the case of small sample sizes. Moreover, this fuzzy quality evaluation model is built on the confidence interval, enabling a decline in the probability of misjudgment incurred by sampling errors.

Measuring the Capability for One Process with Spherical Tolerance

2013 ◽  
Vol 284-287 ◽  
pp. 3717-3726
Author(s):  
Liang Chyau Sheu ◽  
Chi Huang Yeh ◽  
Ching Ho Yen ◽  
Chia Hao Chang
Keyword(s):  
Manufacturing Industry ◽  
Process Capability ◽  
Quality Characteristic ◽  
Process Capability Indices ◽  
Measuring Process ◽  
Process Yield ◽  
Effective Measure ◽  
Capability Indices ◽  
Process Loss ◽  
Loss Index

Process capability indices, Cp, Cpk, and Cpm, are well-known indices used widely in the manufacturing industry for measuring process reproduction capability according to manufacturing specifications, but limited to cases with single engineering specification. Therefore, for processes where the quality characteristic is the location relative to a specific location, they can not provide an effective measure. In this paper, we propose a process loss index LG to evaluate the process capability for this issue. Based on the index, we provide the corresponding transformation for production yield. In addition, we tabulate some critical values for process loss index LG to judge if the process capability is capable. The proposed method is useful for the practitioners to measure the process loss and determine whether a process meets the present process yield requirement.

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