• Geomechanics and Engineering
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• v.32 no.5
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• pp.503-512
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• 2023

In tunneling projects, a significant part of the costs is spent on segment production. By more economically producing, the cost of tunnel construction can be greatly reduced, especially in long and large-diameter tunnels. In the present study, the effect of using the Carousel method in the improvement of the production system performance compared to the conventional Static system has been studied. To carry out the research, a quantitative comparison of cost and production time was carried out for two production methods using the available documentation. The opinions of experts have been obtained using questionnaires and qualitative comparison of cost, time and production quality was done by implementation of statistical analysis. The SPSS software and the univariate t-test were used to analyze the questionnaires. According to the results of statistical analysis with SPSS, the use of the Carousel method will reduce production time and costs along with increasing manufacturing quality. According to the documentation analysis, the Carousel method reduces the cost of production by almost 30% and leads to a reduction of the production time to approximately 40% of the Static moulds system. The Carousel method has a higher production rate, efficiency, and better performance. Research into quantifying the benefits of Carousel method in the production system performance is very limited. This comparison is based on real information from the under construction Tabriz Metro project. This article can be very helpful in choosing the best production method.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.428-439
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• 2020

The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

• Korean Journal of Construction Engineering and Management
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• v.5 no.5 s.21
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• pp.93-100
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• 2004

For accurate construction contract time estimation, few parameters are more significant than crew production rates and factors affecting the rates. However, statistical analysis techniques for finding such factors are not always simple mainly because there are many factors and the interaction between factors is not well quantitatively understood. This paper presents methodology of identifying factors driving crew production rates. The methodology is further demonstrated with representative data collected by the author from 13 on-going highway constructions. Three factors were identified as statistically significant drivers of Cap crew production rate: 'Cap Size (m3/ea)'; 'Cap Length (m)'; and 'Cap Shape (Rectangle vs. Inverted 'T')'. It was also found that the production rates are best explained by a multiple regression model with two of the drivers; 'Cap Size' and 'Cap Shape'.

• Journal of Microbiology and Biotechnology
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• v.28 no.6
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• pp.902-908
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• 2018

Optimization of the culture medium to maximize menaquinone-7 (MK-7) production by Bacillus subtilis strain KCTC 12392BP in static culture was carried out using statistical experimental methods, including one factor at a time, fractional factorial design, and response surface methodology (RSM). Maltose (carbon source), tryptone (nitrogen source), and glycerol (activator) were identified as the key medium components for MK-7 synthesis by the fractional factorial design, and were selected for statistical optimization by RSM. The statistical analysis indicated that, in the range that was studied, maltose, tryptone, and glycerol were all critical factors having profound effects on the production of MK-7, with their coefficients for linear and quadratic all significant at the p < 0.05 level. The established model was efficient and feasible, with a determination coefficient ($R^2$) of 0.9419. The predicted concentrations of maltose, tryptone, and glycerol in the optimal medium were determined as 36.78, 62.76, and 58.90 g/l, respectively. In this optimized medium, the maximum yield of MK-7 reached a remarkably high level of $71.95{\pm}1.00{\mu}g/ml$ after 9 days of static fermentation, which further verified the practicability of this optimized strategy.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.130-139
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• 2016

The purpose of this paper is to analyze the problems and the sources of defective products and draw improvement plans in a small plastic boat manufacturing process using TOC (Theory Of Constraints) and statistical analysis. TOC is a methodology to present a scheme for optimization of production process by finding the CCR (Capacity Constraints Resource) in the organization or the all production process through the concentration improvement activity. In this paper, we found and reformed constraints and bottlenecks in plastic boat manufacturing process in the target company for less defect ratio and production cost by applying DBR (Drum, Buffer, Rope) scheduling. And we set the threshold values for the critical process variables using statistical analysis. The result can be summarized as follows. First, CCRs in inventory control, material mix, and oven setting were found and solutions were suggested by applying DBR method. Second, the logical thinking process was utilized to find core conflict factors and draw solutions. Third, to specify the solution plan, experiment data were statistically analyzed. Data were collected from the daily journal addressing the details of 96 products such as temperature, humidity, duration and temperature of heating process, rotation speed, duration time of cooling, and the temperature of removal process. Basic statistics and logistic regression analysis were conducted with the defection as the dependent variable. Finally, critical values for major processes were proposed based on the analysis. This paper has a practical importance in contribution to the quality level of the target company through theoretical approach, TOC, and statistical analysis. However, limited number of data might depreciate the significance of the analysis and therefore it will be interesting further research direction to specify the significant manufacturing conditions across different products and processes.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.6
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• pp.373-382
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• 2013

The weight of floating offshore plant, such as an FPSO(Floating, Production, Storage, and Off-loading unit) and an offshore wind turbine, is important for estimating the amount of production material and for determining the production method. Furthermore, the weight is a factor which affects in the building cost and production time of the floating offshore plant. Although the importance of the weight has long been recognized, the weight has been roughly estimated by using the existing design and production data, and designer's experience. To solve this problem, a simplified model for the weight estimation of the floating offshore plant using the statistical method was proposed in this study. To do this, various data for estimating the weight of the floating offshore plant were collected through the literature survey, and then the correlation analysis and the multiple regression analysis were performed to generate the simplified model for the weight estimation. Finally, to examine the applicability of the developed model, it was applied to examples of the weight estimation of an FPSO topsides and an offshore wind turbine. As a result, it was shown that the developed model can be applied the weight estimation process of the floating offshore plant at the early design stage.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.707-716
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• 2018

Purpose: This study aims to analyze the management performance and production efficiency of strawberry farmers who introduced smart farming, one of the primary symbols of the fourth industrial revolution in the agricultural sector. Methods: We conducted an empirical survey of strawberry farms using smart farming and analyzed production efficiency using DEA method. Results: First, difficulties for strawberry farmers introducing smart farming included time and money spent on parts replacement and additional costs due to compatibility problems with existing facilities after the adoption. Second, strawberry farmers using smart farming increased their total income by producing higher yield and improving quality thanks to the competent growth management. Third, the analysis of production efficiencies before and after smart farming found improvement in technical efficiency, pure technical efficiency, and scale efficiency. But, the gaps in technical and scale efficiencies among the farms widened. Conclusion: Based on the results above, following policy suggestions are offered. First, an environment control technology suitable for strawberry farming needs to be developed. Second, the smart farming technology needs to be standardized by the government. Third, new smart farm models need to be developed to accommodate to the facilities and environment in Korea through collecting big data including high-quality data on the environment, growth, and yield. Fourth, continuing education needs to be provided to narrow the gap in smart farming technology among strawberry farmers.

• Advances in Energy Research
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• v.4 no.1
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• pp.69-86
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• 2016

The quest to reduce the level of overdependence on fossil fuel product and to provide all required information on proven existing alternatives for renewable energy has resulted into rapid growth of research globally to identify efficient alternative renewable energy sources and the process technologies that are sustainable and environmentally friendly. The present study is aimed at production and characterization of bioethanol produced from sugarcane juice using a $2^4$ factorial design investigating the effect of four parameters (reaction temperature, time, concentration of bacteria used and amount of substrate). The optimum bioethanol yield of 19.3% was achieved at a reaction temperature of $30^{\circ}C$, time of 72 hours, yeast concentration of 2 g and 300 g concentration of substrate (sugarcane juice). The result of statistical analysis of variance shows that the concentration of yeast had the highest effect of 7.325 and % contribution of 82.72% while the substrate concentration had the lowest effect and % contribution of -0.25 and 0.096% respectively. The bioethanol produced was then characterized for some fuel properties such as flash point, specific gravity, cloud point, pour point, sulphur content, acidity, density and kinematic viscosity. The results of bioethanol characterization conform to American society for testing and materials (ASTM) standard. Hence, sugarcane juice is a good and sustainable feedstock for bioethanol production in Nigeria owing relative abundance, cheap source of supply and available land for large scale production.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.513-523
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• 2000

The X-12-ARIMA program was utilized on the analysis of the time series trend on 76 Korean industrial activities data in order to ensure that the trading day effect adjustment as well as the seasonal effect adjustment is needed to extract the fundamental trend-cycle factors from various economic time series data. The trading day effect is strongly correlated with the activity of production and shipping but not with the activity of inventory. Furthermore, the industrial activities were classified with respect to the sensitivity on the tranding day effect.

• Journal of the Korean Dietetic Association
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• v.5 no.2
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• pp.182-193
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• 1999

The purpose of this research is to analysis the general job of 76 dietitian on common management of school food service in Kyoung-buk area. In this research we asked them some general aspects, and made use of three variants(job performing time, the degree of major recognition, and the degree of difficulty) each question after classifying their jobs into 13 standard jobs. Statistical data analysis was completed using SPSS package program. The results of this survey showed the following : 1. The types of common management are as in the following : of the whole 76, 37 on the rotative trip to one single school, 8 to two schools, 1 to three schools, 28 on the trip to one single school plus central food production and 1 on the trip to two schools plus central food production. 2. The average job performing time in his or her school is 2813 minutes(8.52 hours) per week. 3. The factor of the evaluation and study of school foodservice has the highest level in every variant, but there were no standard job which needed the high-level difficulty and the longer job performing time as it needed the low degree of major recognition.