Abstract:Management area of leadership and commitment in the quality management system is a mean to achieve successful functions, even more on construction industry. The objective of this research is to analyze the correlation between leadership and commitment focus management area and quality performance as indicated by rework. Research location is uranium (U), thorium (Th), and rare earth elements (REE) processing pilot plant construction area in Center for Nuclear Minerals Technology-BATAN. Primary data were collect… Show more
“…The correlation coefficient (resulting value) was utilized in this research to measure the relationship amongst the quality management factors and project quality that indicated by contamination. Within the statistical analysis, produce statistical significance testing (pvalue) which as important as the coefficient correlation value [16]. Statistical significance testing (p-value) is The P value or calculated probability, is the probability of finding the observed or more extreme, results when the null hypothesis (H0) of a study question is true [26].…”
Section: Methodsmentioning
confidence: 99%
“…Statistical significance testing (p-value) is The P value or calculated probability, is the probability of finding the observed or more extreme, results when the null hypothesis (H0) of a study question is true [26]. This research use the p-value at 0.05 as used in previous studies [16,17,27,28]. The interpreting size of correlation coefficient shown in Table 3 [25].…”
“…Top management commitment, staff training, communication, and organizational culture are factors that affect the quality of a project [7]. Leadership, commitment, responsibility, and authority for the management system, corporate policy, infrastructure, and environment work [16].…”
Monitoring and supervision of factors that predominantly affect the successful implementation of quality management systems on the project will improve the quality of construction that provides a safety factor in the construction of a pilot plant nuclear fuel processing, to determine those factors is the aim of this research. The separation of Uranium, Thorium, and Rare Earth Metals Pilot Plant was used as a case of the research. Adopted descriptive research design were the primary data collected using questionnaires. Data collected analysed thought multiple linear regressions that only done on factors that have correlation strong – very strong. International Standard Organisation series 9001:2015 and International Atomic Energy Agency safety standards series No. GS-R3 were used as independent variables (X), contamination level was used as dependent variable (Y) that reflected project quality. The result is there are three factors that statistically significant influencing project quality: leadership and commitment, project planning, and safety culture. Those factors influencing the achievement of construction quality of the pilot plant uranium, thorium and rare earth element i.e. 92.3%, while the remaining 7.7% (100-92.3%) is determined by other variables.
“…The correlation coefficient (resulting value) was utilized in this research to measure the relationship amongst the quality management factors and project quality that indicated by contamination. Within the statistical analysis, produce statistical significance testing (pvalue) which as important as the coefficient correlation value [16]. Statistical significance testing (p-value) is The P value or calculated probability, is the probability of finding the observed or more extreme, results when the null hypothesis (H0) of a study question is true [26].…”
Section: Methodsmentioning
confidence: 99%
“…Statistical significance testing (p-value) is The P value or calculated probability, is the probability of finding the observed or more extreme, results when the null hypothesis (H0) of a study question is true [26]. This research use the p-value at 0.05 as used in previous studies [16,17,27,28]. The interpreting size of correlation coefficient shown in Table 3 [25].…”
“…Top management commitment, staff training, communication, and organizational culture are factors that affect the quality of a project [7]. Leadership, commitment, responsibility, and authority for the management system, corporate policy, infrastructure, and environment work [16].…”
Monitoring and supervision of factors that predominantly affect the successful implementation of quality management systems on the project will improve the quality of construction that provides a safety factor in the construction of a pilot plant nuclear fuel processing, to determine those factors is the aim of this research. The separation of Uranium, Thorium, and Rare Earth Metals Pilot Plant was used as a case of the research. Adopted descriptive research design were the primary data collected using questionnaires. Data collected analysed thought multiple linear regressions that only done on factors that have correlation strong – very strong. International Standard Organisation series 9001:2015 and International Atomic Energy Agency safety standards series No. GS-R3 were used as independent variables (X), contamination level was used as dependent variable (Y) that reflected project quality. The result is there are three factors that statistically significant influencing project quality: leadership and commitment, project planning, and safety culture. Those factors influencing the achievement of construction quality of the pilot plant uranium, thorium and rare earth element i.e. 92.3%, while the remaining 7.7% (100-92.3%) is determined by other variables.
“…Oryantasyon, gözlem yapılabilmesi için nesneye yönelik olmalıdır. Sistem, toplam kalite kontrolü sağlamak için aşağıdaki özellikleri kapsamalıdır (Madyaningarum et al, 2018):…”
Günümüzde Moore yasasına uygun şekilde gücü hızla artıp ucuzlayan bilgisayarlar yapay görme sistemlerinin yaygınlaşmasının önünü açmıştır. Bununla beraber yapay görme sistemlerinin yazılımlar, kameralar, ışık sistemleri gibi başka bileşenler gerektirmesi ve bu bileşenlerin entegrasyonu ile eğitim çalışmaları konuyu ciddi bir yatırım konumuna getirmektedir. Kuşkusuz yapay görme sistemlerinin endüstride ve iç lojistik uygulamalarda kalitesizlik maliyetlerini azaltan çok önemli bir araç olması yatırımları teşvik etmektedir. Ancak ekonomiklik ilkesine uyması da vazgeçilemez koşuldur. Dolayısı ile bu sistemlerin kullanıldıkları süre boyunca götürülerinin üstünde getiri sağlamalarına dikkat edilmelidir. Bu çalışmada kalite iyileştirmeleri sağlamak amaçlı kullanılması düşünülen yapay görme sistemlerinin yatırım karlılığının anlaşılmasını kestirecek bir model tanıtılmaktadır. Ülkemiz genelinde yürüttüğümüz araştırmalar ile EMVA (European Machine Vision Association) ile yaptığımız görüşmeler çerçevesinde temin edilen veriler benzer bir modelin bulunmaması nedeniyle kimi karsız yatırımların yapılmakta olduğu, kimi karlı olabilecek yatırım fırsatlarının kaçırıldığı gerçeklerini ortaya çıkartmıştır. Model, kalitesizlik maliyetlerini, yapay görme sisteminin tahmini bedelini, kalitesizlik maliyetlerinde yapay görme sistemi sayesinde sağlanabilecek tasarruf tutarını veri olarak almakta ve işgücü maliyetleri açısından da bir öneri geliştirmektedir.
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