Quality control in capacitor production and testing

Increasing competition and the need for higher reliability have created new dimensions in the measurement of quality and targeting for zero defect production. Traditionally, the quality control function was performed by a team of inspectors. Quality control has now become a company-wide phenomenon. Conventional tools and sampling plans are of limited use today. Effective organizational quality implementation strategy, backed by involvement of top management and adequate informations system, is needed to achieve the desired quality levels This work deals with development and implementation of total quality control using PCs in an organization engaged in development and manufacture of precision engineering components. The approach used in this work has been need-based and evolutionary, since the problem-solving capability and expertise needed had to be developed from within the organization. This study forms a part of a project dealing with transformation of an organization using conventional produ...

This research proposes a resource allocation model of Data QC (Quality Control) activities using COQ (Cost of Quality). The model has been developed based on a series of research efforts such as COQ classifications, weight determination of Data QC activities, and an aggregation approach between COQ and Data QC activities. In the first stage of this research, COQ was divided into the four typical classifications (prevention costs, appraisal costs, internal failure costs and external failure costs) through the opinions from five professionals in Data QC. In the second stage, the weights of Data QC activities were elicited from the field professionals. An aggregation model between COQ and Data QC activities has been then proposed to help the practitioners make a resource allocation strategy. DEA (Data Envelopment Analysis) was utilized for locating efficient decision points. The proposed resource allocation model has been validated using the case of Korea national defense information system. This research is unique in that it applies the concept of COQ to the data management for the first time and that it demonstrates a possible contribution to a real world case for budget allocation of national defense information.Keywords: resource allocation, data quality control, cost of quality1. 서 론

Keywords: percutaneous coronary intervention; structural heart disease intervention; congential heart disease; adults; congenital heart disease; pediatrics

Quality is a critical dimension in business competition that influences a company's competitiveness. Quality costs, including production and defect repair, play an important role in product quality control. High quality can increase market share and sales value, as well as reduce costs, thereby increasing company profitability. Based on this phenomenon, researchers conducted a meta-analysis based on research objectives, variables, research objects, research population/sample, data collection techniques, and analytical tools used.This research aims to determine and develop research regarding quality and profitability cost models. This research uses a meta-analysis method. Meta analysis is a review of a number of research results on similar problems. The unit of analysis in the research is written documents about quality cost model research in the form of journal articles based on their suitability to the research theme. The data analysis used is quantitative data analysis with percentages and qualitative data analysis for data resulting from descriptive analysis of 20 studies related to the effect of quality costs on profitability. The findings of the meta-analysis results based on research objectives, research variables used, research population/sample, data collection techniques and analysis tools show that the quality cost model categories can contribute to evaluating the optimization of quality achievements

Roads are essential necessity of every nation and it is possible that even with proper designs, the roads might not be constructed to the design standard due to poor quality assurance and control resulting in poor pavement quality. This study presents experimental results carried out on various hot - mix asphalt (HMA) samples obtained across different Asphalt plants in South West Nigeria. This was done to determine the extent to which the HMA used in the construction and rehabilitation of Nigerian roads affect their service life. Six samples of the asphalt binder (bitumen) were obtained from each plant over a period of six months and tested. The tested properties were assessed based on the level of conformance with the specifications and requirements from the FMWH General Specification (Roads and Bridges). The results revealed that HMA from plant B had a specific gravity of 1.01, penetration of 65.00 mm, softening point of 53 oC, flash point of 237.00 oC, peak Marshall Stability of 18.25 kN, flow of 3.87 mm and voids in total mixture peak value of 5.08 %. HMA from plant E had a specific gravity of 1.03, penetration of 65.00 mm, softening point of 51 oC, flash point of 239.00 oC, peak marshall stability of 18.26 kN, flow of 3.67 mm and voids in total mixture peak value of 4.99 % and these were adjudged the best in conformance with the FMWH specifications. Adequate monitoring of HMA quality for either binder or wearing courses by carrying out quality control and assurance tests is thereby recommended as it affects pavement durability and performance. Keywords: Hot-mix asphalt, quality assurance, quality control, marshall stability, flow test

The main goals of quality management are customer satisfaction by delivery of defect free products, and radical reduction of defect rates and quality costs in production. Controlled processes are the most important way to reach these goals. In electronics production, the processes are complex and are subject to many strong environmental influences, especially for production of small batches of assemblies (high mix/low volume). Tools are required to compare the quality behaviors of different technological processes caused by different electronic products and establish the correct inspection strategy: no inspection, 100% inspection or statistical process control (SPC). To answer these questions we have developed simple quality cost models. The quality costs are the system used to compare different inspection strategies. The costs are calculated by the use of mathematical quality cost models. The authors presented linear cost models at ISSE 1999 in Dresden. These models also reflect the influence of pseudo defects and defect flow at inspection processes. The quality cost models can be used as a decision aid in test process organization (100% inspection, SPC or no inspection after the considered process). In the case of SPC, it is possible to get an adapted sampling plan. The investigations were made in cooperation with the electronics production of a large international enterprise. The basic quality cost models and the extension for SPC are explained here. The implementation, successful use and economical results of using these models are presented.

Based on holons theory, the product quality control holonic structure for extended enterprises is constructed by the similarity characteristic of quality control function extended enterprises. In the structure, the quality control holons that has autonomy and cooperation ability are established, and by the analysis of holon cooperation operation, by means of the definition and description the cooperation relations among holons, the structure can complete complex cooperation in internal and external cooperation holons to improve the ability and efficiency of product quality control. The implementation strategy of the product quality control holonic structure is constructed by finite state markov chains to dynamically describe cooperation relationship, and forecast the dynamic cooperation tendency to serve for quality decision. Finally, the implementation strategy can be demonstrated and validated the proposed idea by Flexsim software. It shows that the product quality control holonic structure for extended enterprises can satisfy the agility, distribution, and robustness requirements the quality control among enterprises.

With the rapid development of the global manufacturing industry, an efficient and accurate quality control system has become key to enhancing competitiveness. Ultrasonic Nondestructive Testing (NDT), as an efficient means of quality inspection, plays a crucial role in improving manufacturing quality through the precision of its data analysis. This study aims to explore the application of ultrasonic NDT data in manufacturing quality control by integrating machine learning technologies, with a specific focus on the Wavelet Neural Network optimized by Genetic Algorithms (GA-WNN). This study achieved significant prediction and evaluation results by applying a GA-WNN to quality control in manufacturing. Compared to traditional Wavelet Neural Network (WNN) models, the GA-WNN more effectively identifies and predicts potential quality issues, especially in noisy data and complex production environments, demonstrating higher accuracy and stability. When predicting possible defect types in the manufacturing process, the GA-WNN showed a notable improvement in accuracy over other models. Additionally, in quality stability evaluation, GA-WNN was able to capture production fluctuations more accurately, providing more valuable results for decision-making. The methodologies and discoveries of this study offer new perspectives and tools for quality control in manufacturing and the analysis of ultrasonic NDT data, presenting broad application prospects.

Zippers play a vital role in the functionality and durability of apparel and accessories, yet they are often overlooked in favour of aesthetic considerations such as length and colour. The study employed Total Quality Management (TQM) Theory. TQM emphasizes continuous improvement, customer satisfaction, and quality control in manufacturing and production. This theory is relevant because it highlights the importance of producing zippers that meet industry standards, ensuring durability, strength, and functionality. This study employed a comparative experimental research design to evaluate the mechanical performance, colourfastness, and dimensional stability of five selected zipper brands (A, B, C, D and E) on the Ghanaian Market composed of metal and nylon materials. A total of 72 zippers were procured for the experiment. Mechanical strength was assessed based on top stop strength, puller attachment strength, and lateral strength, while colourfastness was tested under washing and rubbing conditions. Dimensional stability was measured in terms of percentage changes in length and width. The statistical software employed for the analysis of the data collected was the Statistical Package and Service Solution (SPSS) for Windows version 26. The results indicate that metal zippers exhibit superior mechanical strength, higher colourfastness ratings, and better dimensional stability than nylon zippers. ANOVA and t-tests at 0.05 alpha levels confirm that these differences are statistically significant (p < 0.001 and p = 0.002, respectively). Correlation analysis reveals strong positive relationships between colourfastness and mechanical strength, emphasizing the impact of material quality on zipper durability. The findings highlight the importance of selecting high-performance zippers for applications requiring enhanced durability and longevity. Metal zippers consistently outperformed nylon zippers in all measured parameters, showing greater resistance to tensile forces, superior colour retention, and minimal dimensional changes. The statistical analyses confirm these findings, with significant differences observed between the two material types. The correlation analysis further supports the interdependence between colourfastness and mechanical strength, indicating that zippers with better colour retention tend to have higher strength parameters. It was recommended that product designers should prioritize strength and durability by selecting zippers suitable for the intended application, ensuring robustness in high-stress environments. Quality control teams must focus on maintaining high wash and wet colourfastness in zippers, particularly for products exposed to frequent washing or outdoor conditions. To guarantee the selection of high-quality materials, standardized testing protocols should be implemented to evaluate zipper performance in real-world conditions.

In view of the problems of lagging and poor predictability for ship assembly and welding quality control, the digital twin technology is applied to realize the quality prediction and control of ship group product. Based on the analysis of internal and external quality factors, a digital twin-based quality prediction and control process was proposed. Furthermore, the digital twin model of quality prediction and control was established, including physical assembly and welding entity, virtual assembly and welding model, the quality prediction and control system, and twin data. Next, the real-time data collection based on the Internet of Things and the twin data organization based on XML were used to create a virtual-real mapping mechanism. Then, the machine learning technology is applied to predict the process quality of ship group products. Finally, a small group is taken as an example to verify the proposed method. The results show that the established prediction model can accurately evaluate the welding angular deformation of group products and also provide a new idea for the quality control of shipbuilding.

A shortage of housing is a prominent issue across the globe. Traditional on-site construction methods seem too inefficient to meet the increasing housing demand. As a solution, many countries, including the United States, Germany, Singapore, Japan, Hong Kong and Australia, have introduced off-site manufacturing methods to increase the housing supply. Different from the traditional way of on-site construction, off-site manufacturing is a technique that involves manufacturing building components in a controlled environment. Despite strong government support and industry attempts to increase off-site manufacturing, the current building consenting and inspection processes in New Zealand have significant quality-related issues. Therefore, this study aimed to identify the gaps in current quality assurance processes used in off-site manufacturing and recommend a framework in order to gain credibility and the acceptance of the construction market. The study collected qualitative data from industry experts (e.g., developers, architects, engineers, project managers, quantity surveyors, head contractors and council officers) who had significant experience in current quality assurance regimes in New Zealand prefabrication construction. The key themes for designing the proposed framework were generated using content analysis of the primary data collected from semi-structured interviews with industry experts. The study has found that standardisation in off-shore products regarding the New Zealand Building Code remains the biggest challenge in the consenting process. Quality assurance and inspection test plans are the developer’s responsibility and are typically provided by third-party inspectors. In this post-Covid-19 world-building, consent authorities rely heavily on third-party inspection companies that apply more rigorous auditing. Essentially, the most important parts of quality assurance are to have an experienced team and to adopt a holistic approach by engaging stakeholders early in the design stage. The stakeholders should consider recommendations for mandatory after-service insurance to ensure end-customer interests are protected. The findings of this study can contribute to the early engagement of different stakeholders to ensure overseas manufacturing of building components meets New Zealand quality standards. It is expected that the new quality assurance framework would help to promote off-site manufacturing for the New Zealand housing sector.

In many chemical and allied manufacturing systems, product quality is controlled based on postprocess quality inspection on sampled final products. Statistical analysis of the identified quality problems is then utilized to improve process operation, and thus the quality of succeeding products. Although this type of reactive quality control (QC) is necessary, it is not only inefficient because it “waits for” the occurrence of product quality problems, but also ineffective due to usually a significant time lag from problem identification, through solution derivation, to action taking. Furthermore, the derived solutions for problem solving are mostly heuristic in nature. This paper introduces a proactive product QC approach, which is established based on the concept of integrated product and process (IPP) control. Aiming at simultaneous dynamic control of process operation and product manufacturing, this approach ensures all‐time systematic control of both process performance and product quality. From the view point of both process control and product control, it is shown that IPP control can be realized by resorting to a well known scheme, cascade control. The IPP control problem for Single‐Input‐Single‐Output systems can be formulated rigorously, and the control laws can be identified readily. A synthesized IPP control system can effectively reject disturbances on the process and the product, and have excellent set‐point tracking capability, regardless of the type of interaction between the process and the product. The efficacy and attractiveness of the IPP control system design methodology are demonstrated through two types of case studies. © 2007 American Institute of Chemical Engineers AIChE J, 2007

Resistance (load-carrying capacity) of a bridge girder is a random variable and can be determined by considering the uncertainty in material, fabrication, and professional/analysis properties. Previous calibrations of load and resistance factor design (LRFD) determined the distribution of bridge resistance on the basis of data from more than 30 years ago. This study uses the latest Material properties available in, the literature to update the resistance distribution. The statistical distribution of the resistance was determined through Monte Carlo simulation. The results of the analysis show an increase in bias and a decrease in the coefficient of variation (COV) for all types of bridges in comparison with those used in previous calibration studies. The changes in bias and COV are the result of higher bias and lower COV in material properties owing to better quality control in concrete and steel manufacturing. Steel and concrete bridges saw the greatest change in resistance distribution. Prestressed bridges saw little change because the material properties of prestressing steel, which is the most sensitive parameter in the prestressed bridges, did not change significantly since the previous calibration study. With these resistance distributions, it is expected that the calibration of the load factor in the AASHTO specification will lead to a lower live load factor, thereby possibly reducing the material cost of the bridge. In addition, the ratio of actual to required (design) resistances of representative bridges in Missouri was determined. The analysis showed that almost all representative bridges had a capacity-to-demand ratio greater than 1 according to current AASHTO standards.

In recent years a growing demand for natural fiber-reinforced plastic components and structures has been observed. One important area of application is transportation, particularly in the automotive industry. Due to market demand, innovative process technologies for fast, cost-effective and quality-driven manufacture of natural fiber-reinforced plastic components is required. This paper will focus on the development of technologies for automised manufacturing of NFRP-components with resin infusion processes. At present NFRP-components are manufactured automatically but without flexibility concerning the deviations of material properties or part geometries. This lack of control in manufacturing results in long cycle times, low process control and high costs. The Bremen Institute for Engineering Design (BIK) is developing and improving machine and process technologies for automised textile handling. The handling system has to meet the requirements of large, limp textile material. The authors have mutually developed methods for the simplified simulation of textiles. The simulation supports the evaluation of textiles and handling devices concerning the ability for better control in manufacturing. To meet these requirements, a simulation of the textile material with the “Finite Element Analysis” method supports the part and process design by reducing developing time and costs. For this purpose, the authors showed a simplified model with a reduced set of material data which is required for the FEA-model.

An intelligent hybrid approach for industrial quality control combining neural networks, fuzzy logic and fractal theory