• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.405-430
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• 2021

Production planning is a key part of production management of manufacturing enterprises. Since computerization began, modern production planning has been developed starting with Material Requirement Planning (MRP), and today Enterprise Resource Planning (ERP), Advanced Planning and Scheduling (APS), Supply Chain Management (SCM) has been spreading and advanced. However, in the shipbuilding field, rather than applying these general-purpose production planning methodologies, in most cases, each shipyard has developed its own production planning system. This is because the applications of general-purpose production planning methods are limited due to the order-taking industry such as shipbuilding with highly complicated construction process consisting of millions of parts per ship. This study introduces the design and development of the production planning system reflecting the production environment of heavy shipyards in Korea. Since Korean shipyards such as Hyundai, Daewoo and Samsung build more than 10 ships per year (50-70 ships in the case of large shipyards), a planning system for the mixed production with complex construction processes is required. This study draws requirements using PI/BPR (process innovation and business process reengineering) methodology to develop a production planning system for shipyards that simultaneously build several ships. Then, CBD software development methodology was applied for the design and implementation of planning system with drawn requirements. It is expected that the systematic development procedure as well as the requirements and functional elements for the development of the shipyard production planning system introduced in this study will be able to present important guidelines in the related research field of shipbuilding management.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.504-509
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• 2004

Safety assessment of construction projects may be affected by various factors such as types and scale of projects, construction methods, procedure, climactic, and site conditions etc. Presently, in planning and design phases, designers are still often uncertain of their responsibilities, l3i]I information and training of safety. Therefore, designers are still failing to exploit the potential that have to eliminate and reduce risks on site. In this study, the concepts of safety impact assessment is introduced in order to derive the performing design for safety in design phase. For this purpose, a framework for safety impact assessment model using risk-based approach for construction projects is suggested. The suggested model includes of information survey and scenarios, classification of safety impact factors occurred by design and construction, and quantitative estimation of magnitude and frequency. Moreover, the checklist which is enable to identify relationship between safety impact factors and design factors is developed and the methodology of safety impact assessment model using risk-based approach is also proposed.

• Journal of Korean Association for Spatial Structures
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• v.11 no.2
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• pp.129-138
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• 2011

Construction methods for underground structure are classified as bottom-up, up-up, and top-down methods depending on the procedure of construction related to a superstructure. In top-down construction methods, building's main structure is built from the ground level downwards by sequentially alternating ground excavation and structure construction. In the mean time, the main structure is also used as supporting structure for earth-retaining wall, which results in the increased stability of the earth-retaining wall due to the minimized deformation in adjacent structures and surrounding grounds. In addition, the method makes it easy to secure a field for construction work in the downtown area by using each floor slabs as working spaces. However top-down construction method is often avoided since an excavation under the slab has low efficiency and difficult environment for work, and high cost compared with earth anchor method. This paper proposes a combined construction method where semi-open cut is selected as excavation work, slurry as earth -retaining wall and CWS as top-down construction method. In the case study targeted for an actual construction project, the proposed method is compared with existing top-down construction method in terms of economic feasibility, construction period and work efficiency. The proposed construction method results in increased work efficiency in the transportation of earth and sand, and steel frame erection, better quality management in PHD construction, and reduced construction period.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2005.11a
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• pp.141-148
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• 2005

This study as a demand of reconstruction allows the longevity of the multi complex, analyze the problems and solutions for a long term maintenance planning scheme, and how to save contingency fund to utilize. The major role of the multi complex housing market reflects Positively on our valuable society, provides a better life of environment on top of longevity and for the superior living duality. For a achievement and improvement existing long term maintenance Plan and contingency fund system should be considered as follows. First, shall be expanded more units of house as smaller group. Second, advice from expert shall be reconsidered, eliminated, and protected reorganizing an informal reconstruction planning comparatively legal procedure must be renegotiated and pursued. Third, the fund which saved for the contingency has to clarified as tax free item by government. It's not only mistreated as a limitation of personal asset but also treated as national source Despite of rather compulsive and constructive method must be noticed by whoever owns for, more positive follows, promotion and directing must be able to guide its understanding and adherence of importance and inevitability.

• Steel and Composite Structures
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• v.50 no.4
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• pp.443-458
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• 2024

The construction industry, one of the biggest producers of greenhouse emissions, is under a lot of pressure as a result of growing worries about how climate change may affect local communities. Geopolymer concrete (GPC) has emerged as a feasible choice for construction materials as a result of the environmental issues connected to the manufacture of cement. The findings of this study contribute to the development of machine learning methods for estimating the properties of eco-friendly concrete, which might be used in lieu of traditional concrete to reduce CO₂ emissions in the building industry. In the present work, the compressive strength (f_c) of GPC is calculated using random forests regression (RFR) methodology where natural zeolite (NZ) and silica fume (SF) replace ground granulated blast-furnace slag (GGBFS). From the literature, a thorough set of experimental experiments on GPC samples were compiled, totaling 254 data rows. The considered RFR integrated with artificial hummingbird optimization (AHA), black widow optimization algorithm (BWOA), and chimp optimization algorithm (ChOA), abbreviated as ARFR, BRFR, and CRFR. The outcomes obtained for RFR models demonstrated satisfactory performance across all evaluation metrics in the prediction procedure. For R² metric, the CRFR model gained 0.9988 and 0.9981 in the train and test data set higher than those for BRFR (0.9982 and 0.9969), followed by ARFR (0.9971 and 0.9956). Some other error and distribution metrics depicted a roughly 50% improvement for CRFR respect to ARFR.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.2
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• pp.70-78
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• 2013

Plants which are having conditions of high temperature and pressure always are exposed to danger. In order to prevent unexpected accidents, safety management that can effectively and appropriately examine facilities is required in plant operation. RBI(Risk-Based Inspection) technology in API 581 is one of standard management technique for evaluating risk on petroleum plants. There are qualitative and quantitative assessments in RBI methodology. Quantitative evaluation step is complex and required much information, so high-risk facilities in plant are selected firstly by qualitative method. Qualitative RBI is performed by choosing the answer in prepared questionnaire. However, it is difficult to believe thoroughly results from survey including ambiguous information. In this study, the procedure of qualitative RBI analysis with considering probability distribution concept were proposed by using Monte Carlo simulation method in order to increase reliability in spite of uncertain factors. In addition, qualitative risk of cooling system for LNG plant was evaluated using proposed procedure. Although 20 items of total 39 assessment items are applied to uncertain factors, risk section of high probability(89%) were verified. The detailed results were described in manuscript.

• Journal of Korean Society of Disaster and Security
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• v.10 no.1
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• pp.11-17
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• 2017

The case study on ground subsidence was conducted and the cause of ground subsidence was evaluated, main cause were insufficient site exploration, inaccurate strength parameters, defective temporary wall, insufficient reaction for boiling and heaving, excessive excavation and so on. Risk factors during excavation were identified from the cause of ground subsidence and risk factors were site exploration, selecting excavation method, structure analysis, measurement plan, excavation method construction, underground water level change, natural disaster and construction management. The survey of the experts on risk factors identified was conducted to evaluate the importance of risk factors, and confidence analysis was performed to evaluate the significance level between survey result and survey respondent using Chi-square Test.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.923-935
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• 2006

As the knowledge-based society has been constructed, the size of work process that has to be done grows bigger and the amount of the information that has to be analyzed increases. So each company is trying to construct more conformable process models in business model. In order to support the process construction of companies practically, in this paper tools of Six Sigma is applied to process definition and tools of PSP is applied schedule management. And to use the proposed tools efficiently, the procedure of process definition and schedule management are suggested. The goal of the proposed method is to achieve the process aim within the Time-To-Market by applying the process management of organizations and persons. And the goal of individuals is to improve personal process with the collected data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.122-129
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• 2010

High-performance concrete (HPC) is a new terminology used in concrete construction industry. Several studies have shown that concrete strength development is determined not only by the water-to-cement ratio but also influenced by the content of other concrete ingredients. HPC is a highly complex material, which makes modeling its behavior a very difficult task. This paper aimed at demonstrating the possibilities of adapting artificial neural network (ANN) to predict the comprresive strength of HPC. Mahalanobis Distance (MD) outlier detection method used for the purpose increase prediction ability of ANN. The detailed procedure of calculating Mahalanobis Distance (MD) is described. The effects of outlier compared with before and after artificial neural network training. MD outlier detection method successfully removed existence of outlier and improved the neural network training and prediction performance.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.6
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• pp.183-193
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• 2003

Most construction works on the soft ground adopt instrumentation to manage settlement and stability of the embankment. The rapid progress of the information technologies and the digital data acquisition on the soft ground instrumentation has led to the fast-growing amount of data. Although valuable information about the behaviour of the soft ground may be hiding behind the data, most of the data are used restrictedly only for the management of settlement and stability. One of the critical issues on soft ground instrumentation is the long-term settlement prediction. Some observational settlement analysis methods are used for this purpose. But the reliability of the analysis results is remained in vague. The knowledge could be discovered from a large volume of experiences on the observational settlement analysis. In this article, we present a database to store settlement records and data mining procedure. A large volume of knowledge about observational settlement prediction were collected from the database by applying the filtering algorithm and knowledge discovery algorithm. Statistical analysis revealed that the reliability of observational settlement analysis depends on stay duration and estimated degree of consolidation.