• Journal of the Society of Naval Architects of Korea
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• v.46 no.1
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• pp.57-68
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• 2009

In automotive industries, reusability of product information is increasing through database construction of previous product data. The product data is stored by data quality management in product information systems. For naval ships, have the functional similarity by the ships of the same classification and class, that are built by series. Information of hull structures as well as embarked equipments are similar. So it would be effective to use database systems that are considered product information quality of previous ships in design and production processes. In this paper we discuss product information quality in database construction of naval ship product models. For this, we propose a basic concept and reference model for data quality verification. Based on this concept, A verification guideline is defined and it is applied for the case study of the digital naval ship which was built to the naval ship product model.

• Korean Journal of Computational Design and Engineering
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• v.10 no.4
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• pp.274-283
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• 2005

Product data quality (PDQ) is a real and significant issue in today's manufacturing environment. In the Korean automotive industry, much of the design work takes place with the support of software tools, such as CAD systems. Although many designers frequently encounter quality problems regarding product data, there is no investigation into the present state of CAD usage and PDQ activities before. The Korean automotive industry is responsible for about 11.1 percent of the total value of manufactured goods in Korea and 7.9 percent of employment in manufacturing. A study performed by the Research Triangle Institute showed that imperfect interoperability imposes at least $\$1$ billion per year on the members of the U.S. automotive supply chain. The trends toward concurrent engineering and out-sourcing have elevated the importance of high-quality product data and efficient product data exchange. This paper shows the results from a survey of PDQ conducted on seven 1st tiers among members of the Korean automotive supply chain.

• Corrosion Science and Technology
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• v.23 no.2
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• pp.131-138
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• 2024

This paper introduces Primetals Technologies' Through-Process Optimization (TPO) Services and Through-Process Quality Control (TPQC) System, which integrate domain knowledge, software, and automation expertise to assist steel producers in achieving operational excellence. TPQC collects high-resolution process and product data from the entire production route, providing visualizations and facilitating quality assurance. It also enables the application of artificial intelligence techniques to optimize processes, accelerate steel grade development, and enhance product quality. The main objective of TPO is to grow and digitize operational know-how, increase profitability, and better meet customer needs. The paper describes the contribution of these systems to achieving operational excellence, with a focus on quality assurance. Transparent and traceable production data is used for manual and automatic quality evaluation, resulting in product quality status and guiding the product disposition process. Deviation management is supported by rule-based and AI-based assistants, along with monitoring, alarming, and reporting functions ensuring early recognition of deviations. Embedded root cause proposals and their corrective and compensatory actions facilitate decision support to maintain product quality. Quality indicators and predictive quality models further enhance the efficiency of the quality assurance process. Utilizing the quality assurance software package, TPQC acts as a "one-truth" platform for product quality key players.

• Journal of Korean Society for Quality Management
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• v.40 no.4
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• pp.599-614
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• 2012

Purpose: We measure service quality based on service process, and examine relationships among product quality, product and service loyalty. Methods: We develop a construct to evaluate process based service quality. We collect data from customers of auto maintenance centers to measure perceived product quality, service and product quality. We test relationships between constructs using structural equation model and regression analysis. Results: Relationships among perceived-product quality, service quality, service loyalty, and product loyalty are all significant. Conclusion: Perceived-product quality has a indirect impact through service quality and loyalty in addition to a direct impact on product loyalty.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.123-133
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• 2021

The purpose of this study was to analyze the influence of product quality factors, product risk, company reputation, and service quality on the purchase intention of insurance policies by customers in Indonesia. The variables in this study are product quality, service quality, company reputation, perceived risk, and purchase intention. This study uses a quantitative approach. Primary data were obtained from 154 respondents. Data processing and model testing use the Structural Equation Modeling procedure with Lisrel 8.80. At the significance level of 0.05, the research found that product quality had a positive and significant effect on purchase intention; product quality had a positive and significant effect on company reputation; product quality had a positive and significant effect on perceived risk perception; company reputation had a positive and significant effect on purchase intention; company reputation has a positive and insignificant effect on service quality; product quality has a positive, but non-significant effect on service quality; service quality has a positive and significant effect on purchase intention; perceived risk has a negative and significant effect on purchase intention; perceived risk has a positive and significant impact on service quality; and perceived risk has a positive and significant effect on company reputation.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.1
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• pp.184-193
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• 2005

Digital representations of products and parts have largely replaced physical drawings as the form in which product data are stored, analyzed, and communicated among the people contributing to the design of an automobile. Many individuals and companies participate in the design of an increasingly complex automobile; hence, the design process depends critically on team members' ability to share information about essential design elements. These trends have elevated the importance of the quality of product data and its efficient exchange. In this paper, we show state-of-the-art on Product Data Quality(PDQ), and activities of PDQ assurance. And we propose a novel design history-based approach for diagnosis and healing of a CAD model.

• IE interfaces
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• v.24 no.1
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• pp.58-70
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• 2011

As more individuals and organizations participate in the complex design process of manufacturing industry, collaborative product development and management of the global supply chain have become more popular. Although the product quality concerns once focused on the manufacturing process, they are now directed at earlier stages of the design cycle where the engineering product is created as a 3D CAD model. In this paper, we describe the current state of product data quality activities in the manufacturing industry and the yardstick to measure 3D CAD data quality. Moreover we introduce a quality assurance method through the result of statistical analysis of 3D CAD models and suggest a six sigma level of CAD data quality by analyzing 76 samples provided from three Korean automotive companies.

• The Journal of Economics, Marketing and Management
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• v.11 no.2
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• pp.23-32
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• 2023

Purpose: This study examines the effect of full information disclosure on seller profit when there exists information asymmetry between sellers and buyers, focusing on the risk averseness of buyers. By investigating the interaction between product quality and perceived risk through online sales data, we attempt to figure out the incentive structure of full information disclosure specifically when buyers are risk-averse, so that we can suggest more feasible information disclosure strategy to sellers. Research design, data and methodology: Our empirical model analyzes the sales data of collectible goods from a major online seller using Poisson regression. In our model, we have specifically considered risk-averseness of buyers by estimating the interaction effect between the product quality and perceived risk on seller profit, aiming for a more precise empirical analysis on sellers' incentive structure of full disclosure. Results: Our empirical analysis strongly supports the effect of interaction between product quality and perceived risk, showing that the incentive for full disclosure is much stronger when product quality is higher, and vice versa. Therefore, sellers are strongly encouraged to voluntarily reveal product weaknesses when their product quality is higher than average, while it is more profitable to hide any product defects when quality claim is lower than average. Conclusions: This study supports the related literature by confirming economic incentives for full disclosure, and also supplements and strengthens previous studies by presenting that the effect of interaction between product quality and perceived risk strongly affects seller profit. Our unique finding supports both mandatory disclosure and voluntary disclosure arguments and presents practical implications to marketing managers by suggesting that seller's incentive for revealing weaknesses depends on the level of seller's product quality.

• The Journal of Economics, Marketing and Management
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• v.12 no.1
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• pp.1-15
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• 2024

Purpose: This study aims to explore the critical factors in the quality control activities of agricultural products in e-commerce companies and analyze how these factors affect customers' perceived value and repurchase intention. Finally, it further reveals the mediating role of perceived value between the factors of quality control activities of agricultural products and customer repurchase intention. Research design, data and methodology: This study identified six independent factors within agricultural product quality control activities: freshness, assurance, diversity, grading, packaging, and timeliness. Subsequently, the impact of these factors on customer repurchase intention was analyzed. Additionally, perceived value was considered as an intermediary variable between the independent and dependent variables. Data was gathered from 269 Chinese consumers who had experience purchasing on agricultural product e-commerce websites. Results: The study results indicate that the relevant factors within agricultural product quality control activities strongly influence customer repurchase intention, with perceived value mediating this relationship. Conclusions: The significance of this study lies in its exploration of the relevant factors within agricultural product e-commerce's product quality control activities. It identifies their impact on customer repurchase intention and confirms the mediating role of perceived value. The results of this research offer valuable insights and practical guidance for academics in related research fields and practitioners in the agricultural product e-commerce industry.

• The Korean Journal of Franchise Management
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• v.11 no.3
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• pp.7-18
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• 2020

Purpose: Recently, information on 'Delicious Restaurants (Mat-zip)' and 'Famous Bakeries' can be obtained through various media such as TV, Internet search, and SNS, and the culture of finding and sharing them has become a trend. Since PZB's SERVQUAL, there have been many studies measuring service quality, leading to hotels, restaurants and coffee shops. These studies of service quality include product quality in the service quality dimension. Hotels, restaurants, and coffee shops are provided with intangible services while customers visit and stay, but 'Delicious Restaurants (Mat-zip)' and 'Famous Bakeries' often stop by to buy products and return home. Therefore, the study on the effect of quality on customer behavior on 'Delicious Restaurants (Mat-zip)' should consider product quality separately. In this study, we want to study how each quality element affects the perceived value and response of customers by separating product quality and service quality. Research design, data, and methodology: This study tested the structural model of how the quality of products and services of famous bakeries affect customers' perceived value and response. As the quality factors, products, tangible services, and employee services were adopted, and perceived values adopted utilitarian and hedonic values, and customer responses adopted customer satisfaction and behavior intention. For this study, 203 survey data with experience using famous bakeries were analyzed using SPSS 22.0 and AMOS 22.0. Result: The research results are as follows. First, product quality positively influenced utilitarian value, hedonic value, and customer satisfaction, tangible service quality positively influenced utilitarian value, and employee service quality positively influenced hedonic value. Second, utilitarian value had a positive effect on behavioral intention, and hedonic value had a positive effect on customer satisfaction. Conclusions: In a famous bakery, it is basic that product quality should be given priority, and for customer satisfaction, employee service quality is half as important. In addition, for Behavior Intension (revisit by the customer), in addition to product quality, the quality of tangible services and employee services should be maintained at a quarter level.