• Title/Summary/Keyword: Steel Companies

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Impact Resistance Testing of NK55 Ophthalmic Lenses in Domestic Market (국내 유통 NK55 재질 안경렌즈의 내충격 시험 평가)

  • Park, Mijung;Jeon, Inchul;Hwang, Kwang Hoon;Byun, Woongjin;Kim, So Ra
    • Journal of Korean Ophthalmic Optics Society
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    • v.16 no.3
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    • pp.229-235
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    • 2011
  • Purpose: The present study was performed to evaluate the safety of ophthalmic lenses in domestic market since eyeglasses wearers could be exposed to the negligent accident by damaged ophthalmic lenses. Method: Totally, 160 ophthalmic lenses (NK55, ${n_{d}}$ = 1.56) with the refractive powers of -3D, -6D, +3D, +6D manufactured by 4 companies in domestic market were evaluated using drop ball test. In accordance with FDA standard, steel ball (~16 g) was freely dropped on these ophthalmic lenses from 127 cm high and the surfaces of lenses were observed. Results: From the study, center thicknesses of NK55 ophthalmic lenses manufactured by 4 different companies showed somewhat different numbers even though the lenses had the same refractive index and powers. All convex lenses of +3D, +6D were evaluated as the safe lenses since there was no damage such as crack and broken found on the lens surfaces after drop ball testing. However, some noticeable broken was shown on the surfaces of concave lenses with relatively thinner center thickness. Especially, 59(73.8%) of total 80 concave lenses with the refractive power of -3D and -6D classified as unacceptable lenses to FDA standard. Conclusions: From the results, the negligent accident by damaged ophthalmic lenses should be considered as well as the correction of visual acuity, design and price when customers purchase eyeglasses. Thus, the enforcement regulation like drop ball testing of uncut ophthalmic lens could be suggested to guarantee the safety of ophthalmic lenses in domestic market.

A Machine Learning-based Total Production Time Prediction Method for Customized-Manufacturing Companies (주문생산 기업을 위한 기계학습 기반 총생산시간 예측 기법)

  • Park, Do-Myung;Choi, HyungRim;Park, Byung-Kwon
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.177-190
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    • 2021
  • Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

Performance Evaluation Method for Facility Inspection and Diagnostic Technologies (첨단기술을 활용한 시설물 점검 및 진단 기술 검·인증을 위한 성능평가 방법론)

  • Lee, Young-Ho;Bae, Sung-Jae;Jung, Wook;Cho, Jae-Yong;Hong, Sung-Ho;Nam, Woo-Suk;Kim, Young-Min;Kim, Jung-Yeol
    • Journal of the Society of Disaster Information
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    • v.16 no.1
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    • pp.178-191
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    • 2020
  • Purpose: This paper proposes a performance evaluation method for state-of-the-art facility inspection/diagnostic equipment through a trend survey of equipment and standardization systems of US, Japan, and Korea. This paper also suggests the priority of developing a performance evaluation method through expert interviews and surveys. Method: In this study, report for the last 5 years of FMS, state-of-the-art equipment of facility maintenance companies/safety diagnosis specialist agencies and papers/research reports/patents of NTIS were analyzed to identify recent trends of facility inspection/diagnostic equipment usages. standardization system of US, Japan, and Korea were analyzed to figure out a suitable form of a performance evaluation method for the domestic situation. And expert interview and survey were conducted to identify the priority of developing a performance evaluation method. Result: The performance evaluation method must be developed by the shape that only evaluates performance, regardless of types of equipment, on inspection item level for creative technology development. The priority of developing the performance evaluation method was identified as crack detection of concrete for durability evaluation and displacement/deformation/fatigue detection of concrete and steel for stability evaluation. Conclusion: The performance evaluation method will be developed firstly for the crack detection of concrete for durability evaluation and displacement/deformation/fatigue detection of concrete/steel for stability evaluation. In order to promote creative technology development, the performance evaluation method should be developed in a form that provides standardized specimens or testbeds and can be applied regardless of types of technologies.

Business Relationships and Structural Bonding: A Study of American Metal Industry (산업재 거래관계와 구조적 결합: 미국 금속산업의 분석 연구)

  • Han, Sang-Lin;Kim, Yun-Tae;Oh, Chang-Yeob;Chung, Jae-Moon
    • Journal of Global Scholars of Marketing Science
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    • v.18 no.3
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    • pp.115-132
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    • 2008
  • Metal industry is one of the most representative heavy industries and the median sales volume of steel and nonferrous metal companies is over one billion dollars in the case America [Forbes 2006]. As seen in the recent business market situation, an increasing number of industrial manufacturers and suppliers are moving from adversarial to cooperative exchange attitudes that support the long-term relationships with their customers. This article presents the results of an empirical study of the antecedent factors of business relationships in metal industry of the United States. Commitment has been reviewed as a significant and critical variable in research on inter-organizational relationships (Hong et al. 2007, Kim et al. 2007). The future stability of any buyer-seller relationship depends upon the commitment made by the interactants to their relationship. Commitment, according to Dwyer et al. [1987], refers to "an implicit or explicit pledge of relational continuity between exchange partners" and they consider commitment to be the most advanced phase of buyer-seller exchange relationship. Bonds are made because the members need their partners in order to do something and this integration on a task basis can be either symbiotic or cooperative (Svensson 2008). To the extent that members seek the same or mutually supporting ends, there will be strong bonds among them. In other words, the principle that affects the strength of bonds is 'economy of decision making' [Turner 1970]. These bonds provide an important idea to study the causes of business long-term relationships in a sense that organizations can be mutually bonded by a common interest in the economic matters. Recently, the framework of structural bonding has been used to study the buyer-seller relationships in industrial marketing [Han and Sung 2008, Williams et al. 1998, Wilson 1995] in that this structural bonding is a crucial part of the theoretical justification for distinguishing discrete transactions from ongoing long-term relationships. The major antecedent factors of buyer commitment such as technology, CLalt, transaction-specific assets, and importance were identified and explored from the perspective of structural bonding. Research hypotheses were developed and tested by using survey data from the middle managers in the metal industry. H1: Level of technology of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H2: Comparison level of alternatives is negatively related to the level of structural bonding between the buyer and the seller. H3: Amount of the transaction-specific assets is positively related to the level of structural bonding between the buyer and the seller. H4: Importance of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H5: Level of structural bonding is positively related to the level of commitment to the relationship. To examine the major antecedent factors of industrial buyer's structural bonding and long-term relationship, questionnaire was prepared, mailed out to the sample of 400 purchasing managers of the US metal industry (SIC codes 33 and 34). After a follow-up request, 139 informants returnedthe questionnaires, resulting in a response rate of 35 percent. 134 responses were used in the final analysis after dropping 5 incomplete questionnaires. All measures were analyzed for reliability and validity following the guidelines offered by Churchill [1979] and Anderson and Gerbing [1988]., the results of fitting the model to the data indicated that the hypothesized model provides a good fit to the data. Goodness-of-fit index (GFI = 0.94) and other indices ( chi-square = 78.02 with p-value = 0.13, Adjusted GFI = 0.90, Normed Fit Index = 0.92) indicated that a major proportion of variances and covariances in the data was accounted for by the model as a whole, and all the parameter estimates showed statistical significance as evidenced by large t-values. All the factor loadings were significantly different from zero. On these grounds we judged the hypothesized model to be a reasonable representation of the data. The results from the present study suggest several implications for buyer-seller relationships. Theoretically, we attempted to conceptualize the antecedent factors of buyer-seller long-term relationships from the perspective of structural bondingin metal industry. The four underlying determinants (i.e. technology, CLalt, transaction-specific assets, and importance) of structural bonding are very critical variables of buyer-seller long-term business relationships. Our model of structural bonding makes an attempt to systematically examine the relationship between the antecedent factors of structural bonding and long-term commitment. Managerially, this research provides industrial purchasing managers with a good framework to assess the interaction processes with their partners and, ability to position their business relationships from the perspective of structural bonding. In other words, based on those underlying variables, industrial purchasing managers can determine the strength of the company's relationships with the key suppliers and its state of preparation to be a successful partner with those suppliers. Both the supplying and customer companies can also benefit by using the concept of 'structural bonding' and evaluating their relationships with key business partners from the structural point of view. In general, the results indicate that structural bonding gives a critical impact on the level of relationship commitment. Managerial implications and limitations of the study are also discussed.

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Survey of Current Status of Casting Industry in Korea (국내 주조산업 현황조사)

  • Cho, Minsu;Lee, Jisuk;Lee, Sanghwan;Lee, Sangmok
    • Journal of Korea Foundry Society
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    • v.41 no.2
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    • pp.144-152
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    • 2021
  • Based on the analysis of the current state of the world's foundry industry, we looked at the international competitiveness of Korea's foundry industry for the past 20 years. Korea's total foundry production is 2.52 million tons, and the production per company (so-called productivity) is 2,831 tons, which is the eighth largest in the world and down one position for the case of total foundry production, while productivity remains its position compared to three years ago. Korea is the only one of the top 10 foundry to see a decline in production. Similar to the global situation, Korean products consist of 38% of grey csat iron, 31% of ductile cast iron, 15% of aluminum, and 9% of cast steel. In order to obtain statistics on Korea's foundry industry, the survey conducted a service project for approximately nine months from April 2020. Various statistical surveys and sample in-depth surveys by the Korean standard industry class were evaluated for various contents of the domestic casting industry. We also looked at the number of companies, the distribution by region, the number of workers and the percentage of foreigners, and the distribution of each job, as well as the R&D investment status according to the size of the enterprise. Together, sales, exports, sales and various profit ratios were analyzed to measure the earning power of foundry industry. In addition, the classification by grouping the foundry industry according to the process utilized by focusing on each company, and to determine the sales, exports, and yield status for each process was also investigated on the basis. Based on these data, the domestic foundry industry has presented a variety of offers for the following issues for sustainable growth; global ranking, marginal corporate restructuring, training of domestic technical people, differentiated support policies by company size and process.