scholarly journals Developing a Novel Fuzzy Evaluation Model by One-Sided Specification Capability Indices

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1076
Author(s):  
Wei Lo ◽  
Chun-Ming Yang ◽  
Kuei-Kuei Lai ◽  
Shao-Yu Li ◽  
Chi-Han Chen
Keyword(s):  
Evaluation Model ◽  
Critical Value ◽  
Process Quality ◽  
Quality Characteristic ◽  
Fuzzy Membership Function ◽  
Environmental Damage ◽  
Quality Level ◽  
Fuzzy Evaluation ◽  
Radar Chart ◽  
Fuzzy Evaluation Model

When all of the one-sided specification indices of each quality characteristic reach the requirements of the process quality level, they can ensure that the process capability of the product meets the requirements of the process quality level. This study constructs a fuzzy membership function based on the upper confidence limit of the index, derives the fuzzy critical value, and then labels the fuzzy critical value on the axis of the visualized radar chart as well as connects adjacent critical points to shape a regular polygonal critical region. Next, this study calculates the observed value of the index to estimate and mark it on the axis for forming a visualized fuzzy radar evaluation chart. Obviously, this fuzzy evaluation model not only reduces the testing cost but also makes the quality level quickly meet the requirements of the specifications. Further, the radar chart can reduce the risk of misjudgment attributable to sampling errors and help improve the accuracy of evaluation by a confidence-upper-limit-based fuzzy evaluation model. Therefore, this easy-to-use visualized fuzzy radar evaluation chart is used as an evaluation interface, which has good and convenient management performance to identify and improve critical-to-quality quickly. Improving the quality of the process before the product is completed will also have the advantage of reducing social losses and environmental damage costs.

scholarly journals The Fuzzy Process Quality Evaluation Model for the STB Quality Characteristic of Machining

2020 ◽  
Vol 10 (22) ◽  
pp. 8272
Author(s):  
Win-Jet Luo ◽  
Kuen-Suan Chen ◽  
Chun-Min Yu ◽  
Ting-Hsin Hsu
Keyword(s):  
Machine Tool ◽  
Evaluation Model ◽  
Quality Characteristics ◽  
Process Quality ◽  
Quality Characteristic ◽  
Quality Level ◽  
Sampling Errors ◽  
Statistical Process ◽  
Accuracy And Precision ◽  
Fuzzy Process

Whether it is important components of a machine tool itself or various important components processed by the machine tool, many vital quality characteristics mostly belong to the smaller-the-better type. When the process quality levels of these quality characteristics do not attain to the criteria, friction loss may increase during the machine operation, affecting not only the process precision and accuracy but also the lifetime of the product. Therefore, this study applied a smaller-the-better six-sigma quality index simultaneously demonstrating process quality level and process yield. Besides, in coping with statistical process control data, a one-tail confidence-interval-based fuzzy testing method was developed to evaluate process quality. Because this approach is built on the basis of confidence intervals, it can reduce the possibility of misjudgment resulting from sampling errors as well as integrate past experience to enhance the accuracy and precision of the assessment, and then it can grasp the timeliness of improvement.

scholarly journals A Fuzzy Evaluation Model Aimed at Smaller-the-Better-Type Quality Characteristics

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2513
Author(s):  
Kuen-Suan Chen ◽  
Tsun-Hung Huang
Keyword(s):  
Confidence Interval ◽  
Quality Index ◽  
Evaluation Model ◽  
Quality Characteristics ◽  
Process Quality ◽  
Small Sample ◽  
Fuzzy Evaluation ◽  
Sample Sizes ◽  
Small Sample Sizes ◽  
Fuzzy Evaluation Model

Numerous key components of tool machines possess critical smaller-the-better-type quality characteristics. Under the assumption of normality, a one-to-one mathematical relationship exists between the process quality index and the process yield. Therefore, this paper utilized the index to produce a quality fuzzy evaluation model aimed at the small-the-better-type quality characteristics and adopted the model as a decision-making basis for improvement. First, we derived the 100(1 −α)% confidence region of the process mean and process standard deviation. Next, we obtained the 100(1 −α)% confidence interval of the quality index using the mathematical programming method. Furthermore, a one-tailed fuzzy testing method based on this confidence interval was proposed, aiming to assess the process quality. In addition, enterprises’ pursuit of rapid response often results in small sample sizes. Since the evaluation model is built on the basis of the confidence interval, not only can it diminish the risk of wrong judgment due to sampling errors, but it also can enhance the accuracy of evaluations for small sample sizes.

scholarly journals Effect of Curriculum Planning for Physical Education in Colleges on Innovation Ability

2020 ◽  
Vol 15 (12) ◽  
pp. 103
Author(s):  
Huiqiu Guo
Keyword(s):  
Physical Education ◽  
Fuzzy Theory ◽  
Evaluation Model ◽  
Curriculum Planning ◽  
Practical Significance ◽  
Fuzzy Evaluation ◽  
Promoting Effect ◽  
Innovation Ability ◽  
Fuzzy Evaluation Model ◽  
Current Curriculum

With poor integrity and unclear goals, the curriculum planning for physical education (PE) in colleges cannot effectively promote the innovation ability of students. To solve the problem, this paper attempts to clearly evaluate the effect of curriculum planning for college PE on the innovation ability of PE majors. Based on the defects of the current curriculum planning, the authors put forward several strategies and suggestions to enhance the promoting effect of college PE curriculum planning on innovation ability. Following the fuzzy theory, an index system and a fuzzy evaluation model were put forward to quantify the effect of college PE curriculum planning on innovation ability. The research results have great theoretical and practical significance.

Fuzzy Evaluation of Water Quality in Water Distribution System Based on Entropy Weight and EPANET

2012 ◽  
Vol 518-523 ◽  
pp. 3703-3706
Author(s):  
Ling Ping Zhao ◽  
Fen Ge Zhang ◽  
Liang Fei Dong ◽  
Yong Wei ◽  
Bao Hua Tu ◽  
...  
Keyword(s):  
Water Quality ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Evaluation Model ◽  
Fuzzy Evaluation ◽  
Entropy Weight ◽  
Simulation Data ◽  
Fuzzy Evaluation Model

According to the fuzziness of water quality in water distribution system, based on the simulation data of water quality obtained by using EPANET software,and applying entropy weight theory in the fuzzy evaluation of water quality, fuzzy evaluation model of water quality based on entropy weight and EPANET is established. Water quality in water distribution system of Hengshanqiao town is evaluated by using this method.Evaluation results are relatively objective and credible, proving that the method is simple and practical, scientific and reliable.

scholarly journals Confidence Interval Based Fuzzy Evaluation Model for an Integrated-Circuit Packaging Molding Process

2019 ◽  
Vol 9 (13) ◽  
pp. 2623 ◽  
Author(s):  
Chun-Ming Yang ◽  
Kuo-Ping Lin ◽  
Kuen-Suan Chen
Keyword(s):  
Confidence Interval ◽  
Integrated Circuit ◽  
Evaluation Model ◽  
Measurement Data ◽  
Electronics Industry ◽  
Green Economy ◽  
Fuzzy Evaluation ◽  
Molding Process ◽  
Ic Packaging ◽  
Fuzzy Evaluation Model

The electronics industry in Taiwan has achieved a complete information and communication technology chain with a firm position in the global electronics industry. The integrated-circuit (IC) packaging industry chain adopts a professional division of labor model, and each process (including wafer dicing, die bonding, wire bonding, molding, and other subsequent processes) must have enhanced process capabilities to ensure the quality of the final product. Increasing quality can also lower the chances of waste and rework, lengthen product lifespan, and reduce maintenance, which means fewer resources invested, less pollution and damage to the environment, and smaller social losses. This contributes to the creation of a green process. This paper developed a complete quality evaluation model for the IC packaging molding process from the perspective of a green economy. The Six Sigma quality index (SSQI), which can fully reflect process yield and quality levels, is selected as a primary evaluation tool in this study. Since this index contains unknown parameters, a confidence interval based fuzzy evaluation model is proposed to increase estimation accuracy and overcome the issue of uncertainties in measurement data. Finally, a numerical example is given to illustrate the applicability and effectiveness of the proposed method.

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