scholarly journals Quality Control for Medium Voltage Insulator via a Knowledge-Informed SPSA Based on Historical Gradient Approximations

Processes ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 146 ◽  
Author(s):  
Xiangsong Kong ◽  
Jiaming Guo ◽  
Dongbin Zheng ◽  
Ji Zhang ◽  
Wei Fu
Keyword(s):  
Quality Control ◽  
Process Parameters ◽  
Weight Control ◽  
Control Method ◽  
Parameters Optimization ◽  
Experimental Simulation ◽  
Iteration Step ◽  
Step Size ◽  
Medium Voltage ◽  
Voltage Insulator

Medium voltage insulators are essential and versatile components in electrical engineering. Quality control of the manufacturing process for the insulators has a significant role in their economic production and reliable operation. As the quality of medium voltage insulator is mainly affected by the process parameters of the automatic pressure gelation process (APG), the optimal process settings are required to achieve a satisfactory quality target. However, traditional process parameters’ optimization methods are often cumbersome and cost-consuming. Moreover, the operational cost of APG for insulator production is relatively high. Therefore, the determination of the optimal settings becomes a significant challenge for the quality control of insulators. To address the above issues, an idea of knowledge-informed optimization was proposed in this study. Based on the above idea, a knowledge-informed simultaneous perturbation stochastic approximation (SPSA) methodology was formulated to reduce the optimization costs, and thus improve the efficiency of quality control. Considering the characteristics of SPSA, the historical gradient approximations generated during the optimization process were utilized to improve the accuracy of gradient estimations and to tune the iteration step size adaptively. Therefore, an implementation of a quality control strategy of knowledge-informed SPSA based on historical gradient approximations (GK-SPSA) was thus constructed. In this paper, the GK-SPSA-based quality control method was applied to the weight control of a kind of post insulators. The experimental simulation results showed that the revised knowledge-informed SPSA was effective and efficient on quality control of medium voltage insulators.

scholarly journals A Knowledge-Informed Simplex Search Method Based on Historical Quasi-Gradient Estimations and Its Application on Quality Control of Medium Voltage Insulators

Processes ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 770
Author(s):  
Xiangsong Kong ◽  
Dongbin Zheng
Keyword(s):  
Quality Control ◽  
Weight Control ◽  
Control Method ◽  
Search Method ◽  
Experimental Simulation ◽  
Process Conditions ◽  
Medium Voltage ◽  
Simplex Search ◽  
Simplex Search Method ◽  
Gradient Based

Quality control is of great significance for the economical manufacturing and reliable application of medium voltage insulators. With the increasingly stringent quality control requirement, traditional quality control methods in this field face a growing challenge on their efficiency. Therefore, this study aims to achieve quality specifications by optimizing process conditions with the least costs. Thus, a knowledge-informed simplex search method was proposed based on an idea of knowledge-informed optimization to enhance the optimization efficiency. Firstly, a new mathematical quantity, quasi-gradient estimation, was generated following a reconstruction of the simplex search from the essence and the development history of the method. Based on this quantity, the gradient-free method possessed the same gradient property and unified form as the gradient-based methods. Secondly, an implementation of the knowledge-informed simplex search method based on historical quasi-gradient estimations (short for GK-SS) was constructed. The GK-SS-based quality control method utilized the historical quasi-gradient estimations for each simplex generated during the optimization process to improve the method’s search directions’ accuracy in a statistical sense. Finally, this method was applied to the weight control of a kind of post insulator. The experimental simulation results showed that the method is effective and efficient in the quality control of medium voltage insulators.

A Step Size Control Method Improving Estimation Speed in Double Talk Term

2013 ◽  
Vol E96.A (7) ◽  
pp. 1543-1551 ◽  
Author(s):  
Takuto YOSHIOKA ◽  
Kana YAMASAKI ◽  
Takuya SAWADA ◽  
Kensaku FUJII ◽  
Mitsuji MUNEYASU ◽  
...  
Keyword(s):  
Control Method ◽  
Size Control ◽  
Step Size ◽  
Step Size Control

Perencanaan Pengendalian Kualitas Produk Pakaian Bayi dengan Metode Six Sigma Pada CV. AGP

JEMAP ◽  
2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Albertus Reynaldo Kurniawan ◽  
Bayu Prestianto
Keyword(s):  
Quality Control ◽  
Continuous Improvement ◽  
Six Sigma ◽  
Screen Printing ◽  
Control Method ◽  
Operational Performance ◽  
Machine Maintenance ◽  
Quality Product ◽  
Break Time ◽  
And Control

Quality control becomes an important key for companies in suppressing the number of defective produced products. Six Sigma is a quality control method that aims to minimize defective products to the lowest point or achieve operational performance with a sigma value of 6 with only yielding 3.4 defective products of 1 million product. Stages of Six Sigma method starts from the DMAIC (Define, Measure, Analyze, Improve and Control) stages that help the company in improving quality and continuous improvement. Based on the results of research on baby clothes products, data in March 2018 the percentage of defective products produced reached 1.4% exceeding 1% tolerance limit, with a Sigma value of 4.14 meaning a possible defect product of 4033.39 opportunities per million products. In the pareto diagram there were 5 types of CTQ (Critical to Quality) such as oblique obras, blobor screen printing, there is a fabric / head cloth code on the final product, hollow fabric / thin fabric fiber, and dirty cloth. The factors caused quality problems such as Manpower, Materials, Environtment, and Machine. Suggestion for consideration of company improvement was continuous improvement on every existing quality problem like in Manpower factor namely improving comprehension, awareness of employees in producing quality product and improve employee's accuracy, Strength Quality Control and give break time. Materials by making the method of cutting the fabric head, the Machine by scheduling machine maintenance and the provision of needle containers at each employees desk sewing and better environtment by installing exhaust fan and renovating the production room.

Chemical Fingerprint Analysis and Simultaneous Determination of Nucleosides and Amino Acids in Kang Fu Xin Liquid by High Performance Liquid Chromatography with Diode Array Detector

2020 ◽  
Vol 16 (7) ◽  
pp. 831-843
Author(s):  
Yuwen Wang ◽  
Shuping Li ◽  
Liuhong Zhang ◽  
Shenglan Qi ◽  
Huida Guan ◽  
...  
Keyword(s):  
Amino Acids ◽  
Quality Control ◽  
Uric Acid ◽  
Control Method ◽  
Principal Component ◽  
Gradient Elution ◽  
Hplc Method ◽  
Array Detector ◽  
Fingerprint Analysis ◽  
Wavelength Switching

Background and Objective: Kang Fu Xin liquid (KFX) is an official preparation made from the ethanol extract product from P. Americana. The present quality control method cannot control the quality of the preparation well. The aim of the present study is to establish a convenient HPLC method for multicomponents determination combined with fingerprint analysis for quality control of KFX. Methods: An HPLC-DAD method with gradient elution and detective wavelength switching program was developed to establish HPLC fingerprints of KFX, and 38 batches of KFX were compared and evaluated by similarity analysis (SA), hierarchical clustering analysis (HCA), and principal component analysis (PCA). Meanwhile, six nucleosides and three amino acids, including uracil, hypoxanthine, uric acid, adenosine, xanthine, inosine, tyrosine, phenylalanine and tryptophan in KFX were determined based on the HPLC fingerprints. Results: An HPLC method assisted with gradient elution and wavelength switching program was established and validated for multicomponents determination combined with fingerprint analysis of KFX. The results demonstrated that the similarity values of the KFX samples were more than 0.845. PCA indicated that peaks 4 (hypoxanthine), 7 (xanthine), 9 (tyrosine), 11, 13 and 17 might be the characteristic contributed components. The nine constituents in KFX, uracil, hypoxanthine, uric acid, adenosine, xanthine, inosine, tyrosine, phenylalanine and tryptophan, showed good regression (R2 > 0.9997) within test ranges and the recoveries of the method for all analytes were in the range from 96.74 to 104.24%. The limits of detections and quantifications for nine constituents in DAD were less than 0.22 and 0.43 μg•mL-1, respectively. Conclusion: The qualitative analysis of chemical fingerprints and the quantitative analysis of multiple indicators provide a powerful and rational way to control the KFX quality for pharmaceutical companies.

scholarly journals Parameters Optimization of Auxiliary Gas Process for Double-Wire SS316L Stainless Steel Arc Additive Manufacturing

Metals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 190
Author(s):  
Wei Wu ◽  
Jiaxiang Xue ◽  
Wei Xu ◽  
Hongyan Lin ◽  
Heqing Tang ◽  
...  
Keyword(s):  
Stainless Steel ◽  
Additive Manufacturing ◽  
Process Parameters ◽  
Evaluation System ◽  
Gas Flow ◽  
Interactive Effect ◽  
Parameters Optimization ◽  
Heat Accumulation ◽  
Auxiliary Process ◽  
Strength And Stiffness

Serious heat accumulation limits the further efficiency and application in additive manufacturing (AM). This study accordingly proposed a double-wire SS316L stainless steel arc AM with a two-direction auxiliary gas process to research the effect of three parameters, such as auxiliary gas nozzle angle, auxiliary gas flow rate and nozzle-to-substrate distance on depositions, then based on the Box–Behnken Design response surface, a regression equation between three parameters and the total score were established to optimized parameters by an evaluation system. The results showed that samples with nozzle angle of 30° had poor morphology but good properties, and increasing gas flow or decreasing distance would enhance the airflow strength and stiffness, then strongly stir the molten pool and resist the interference. Then a diverse combination of auxiliary process parameters had different influences on the morphology and properties, and an interactive effect on the comprehensive score. Ultimately the optimal auxiliary gas process parameters were 17.4°, 25 L/min and 10.44 mm, which not only bettered the morphology, but refined the grains and improved the properties due to the stirring and cooling effect of the auxiliary gas, which provides a feasible way for quality and efficiency improvements in arc additive manufacturing.

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