• Journal of Institute of Convergence Technology
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• 제3권1호
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• pp.41-44
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• 2013

Process and manufacturing data are numerously accumulated to the enterprise database in industries but little of those data are utilized. Data mining can support a decision to manager in process from the data. However, it is not easy to field managers because a proper adoption of various schemes is very difficult. In this paper, six scenarios are conducted using data mining schemes for the various situations of field claims such as yield problem, trend analysis and prediction of yield according to changes of operating conditions, etc. Scenarios, like templates, of various analysis situations are helpful to users.

• Journal of Institute of Control, Robotics and Systems
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• 제15권10호
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• pp.1056-1061
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• 2009

This paper proposes a short-term water demand forecasting algorithm based on kalman filtering with data mining for sustainable water supply and effective energy saving. The proposed algorithm utilizes a mining method of water supply data and a decision tree method with special days like Chuseok. And the parameters of MLAR (Multi Linear Auto Regression) model are estimated by Kalman filtering algorithm. Thus, we can achieve the practicality of the proposed forecasting algorithm through the good results applied to actual operation data.

• The Journal of Information Systems
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• 제20권3호
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• pp.1-24
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• 2011

Recently, six sigma has been widely adopted in a variety of industries as a disciplined, data-driven problem solving approach or methodology supported by a handful of powerful statistical tools in order to reduce variation through continuous process improvement. Also, data mining has been widely used to discover unknown knowledge from a large volume of data using various modeling techniques such as neural network, decision tree, regression analysis, etc. This paper proposes a six sigma methodology based on data mining for effectively and efficiently processing massive data in driving six sigma projects. The proposed methodology is applied in the hot stove system which is a major energy-consuming process in a "P" steel company for improvement of heat efficiency through reduction of energy consumption. The results show optimal operation conditions and reduction of the hot stove energy cost by 15%.

• Journal of information and communication convergence engineering
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• 제16권1호
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• pp.52-59
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• 2018

Odoo is an enterprise resource planning information system providing modules to support the basic business function in companies. This research will look into the development of an additional module at Odoo. This module is a data mining module using Market Basket Analysis (MBA) using FP-Growth algorithm in managing OLTP of sales transaction to be useful information for users to improve the analysis of company business strategy. The FP-Growth algorithm used in the application was able to produce multidimensional association rules. The company will know more about their sales and customers' buying habits. Performing sales trend analysis will give a valuable insight into the inner-workings of the business. The testing of the module is using the data from X Supermarket. The final result of this module is generated from a data mining process in the form of association rule. The rule is presented in narrative and graphical form to be understood easier.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제27권2호
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• pp.10-16
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• 2004

Data mining technique is the exploration and analysis, by automatic or semiautomatic means, of large quantities of data in order to discover meaningful patterns and rules. This paper uses a data mining technique for the prediction of defect types in manufacturing Process. The Purpose of this Paper is to model the recognition of defect type Patterns and Prediction of each defect type before it occurs in manufacturing process. The proposed model consists of data handling, defect type analysis, and defect type prediction stages. The performance measurement shows that it is higher in prediction accuracy than logistic regression model.

• Journal of the Korean Society for Precision Engineering
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• 제20권6호
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• pp.178-188
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• 2003

A study on the dynamic analysis of a tracked vehicle for mining on deep-sea bed with very soft soil is presented. An equation for the interaction between track and soft soil is employed to develop a track/soil interaction module called TVAS. The vehicle is modeled as a multi-body dynamic system using a multi-body dynamic analysis program. The developed module is incorporated into the multi-body dynamic analysis program with a user subroutine. The dynamic behavior and design of the mining vehicle on deep-sea bed is investigated.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제30권2호
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• pp.99-105
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• 2007

According to the automated manufacturing processes followed by the development of computer manufacturing technologies, products or quality characteristics produced on the processes have measured and recorded automatically. Much amount of data daily produced on the processes may not be efficiently analyzed by current statistical methodologies (i.e., statistical quality control and statistical process control methodologies) because of the dimensionality associated with many input and response variables. Although a number of statistical methods to handle this situation, there is room for improvement. In order to overcome this limitation, we integrated data mining and robust design approach in this research. We find efficiently the significant input variables that connected with the interesting response variables by using the data mining technique. And we find the optimum operating condition of process by using RSM and robust design approach.

• Journal of Power Electronics
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• 제14권5호
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• pp.1028-1037
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• 2014

To optimize controller design and improve static and dynamic performances of three-phase four-leg inverter systems, a compound control method that combines state feedback and quasi-sliding mode variable structure control is proposed. The linear coordinate change matrix and the state variable feedback equations are derived based on the mathematical model of three-phase four-leg inverters. Based on system relative degrees, sliding surfaces and quasi-sliding mode controllers are designed for converted linear systems. This control method exhibits the advantages of both state feedback and sliding mode control. The proposed controllers provide flexible dynamic control response and excellent stable control performance with chattering suppression. The feasibility of the proposed strategy is verified by conducting simulations and experiments.

• International Journal of Knowledge Content Development & Technology
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• 제3권2호
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• pp.43-65
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• 2013

In this work, we first introduce two main approaches to writing requirements and then propose a method based on Natural Language Processing to improve requirement authoring and the overall coherence, cohesion and organization of requirement documents. We investigate the structure of requirement kernels, and then the discourse structure associated with those kernels. This will then enable the system to accurately extract requirements and their related contexts from texts (called requirement mining). Finally, we relate a first experimentation on requirement mining based on texts from seven companies. An evaluation that compares those results with manually annotated corpora of documents is given to conclude.

• Industrial Engineering and Management Systems
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• 제11권1호
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• pp.94-102
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• 2012

In this paper, an interactive planning and scheduling framework are proposed for optimising operations from pits to crushers in ore mining industry. Series of theoretical and practical operations research techniques are investigated to improve the overall efficiency of mining systems due to the facts that mining managers need to tackle optimisation problems within different horizons and with different levels of detail. Under this framework, mine design planning, mine production sequencing and mine transportation scheduling models are integrated and interacted within a whole optimisation system. The proposed integrated framework could be used by mining industry for reducing equipment costs, improving the production efficiency and maximising the net present value.