• 한국공작기계학회논문집
• /
• 제15권5호
• /
• pp.59-64
• /
• 2006

The automation of hot rolling process requires the developments of several mathematical models for simulation and quantitative description of the industrial operations involved in order to achieve the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties). The mathematical modeling of hot rolling process has long been recognized to be a desirable approach to investigate rolling operating practice and design of mill requirement. To achieve this objectives, a new teaming method with neural network to improve the accuracy of rolling force prediction in hot rolling mill is developed. Also, Genetic Algorithm(GA) is applied to select the optimal structure of the neural network and compared with that of engineers experience. It is shown from this research that both structure selection methods can lead to similar results.

• 한국공작기계학회논문집
• /
• 제14권1호
• /
• pp.52-57
• /
• 2005

In the foe of global competition, the requirements for the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a mai or change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models for simulation and quantitative description of the industrial operations involved. In this paper, an on-line training neural network for both long-term teaming and short-term teaming was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 2003년도 춘계학술대회 논문집
• /
• pp.124-129
• /
• 2003

In the face of global competitor the requirements flor the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a major change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models fir simulation and quantitative description of the industrial operations involved. In this paper, a on-line training neural network for both long-term teaming and short-term teaming was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.

• 제어로봇시스템학회논문지
• /
• 제5권6호
• /
• pp.676-682
• /
• 1999

A study which develops a controller design methodology that has flexibility of eigenstructure assignment within the stability-robustness contraints of LQR is requried and has been performed. The previously developd control design methodology, namely, EALQR(Eigenstructure Assignment/LQR) has better performance than that of conventional LQR or eigenstructure assignment but has a constraint for the weitgting matrix in LQR, which could be indefinite for high-order system. In this paper, the effects of the indefinite Q in EALQR on the frequency domain properties are analyzed. The robustness criterion and quantitative frequency domain properties are also resented. Finally, the frequency domain properties of EALQR has been analyzed by applying to a flight control system design example.

• 제어로봇시스템학회논문지
• /
• 제13권3호
• /
• pp.256-262
• /
• 2007

In mass customization, the focus is variety and customization through flexibility and quick responsiveness. Mass customizers seek to provide personalized, custom-designed products at low prices to give customers exactly what they want and to provide sufficient variety in products and services. The idea of the product family is the most adequate approach to realize mass customization. An understanding of customer needs using functional decomposition becomes necessary to enhance the performance of the product family. This paper focuses on functional architecture modeling based on customer need regarding sub-functions for the product family. A quantitative functional model captures product functionality and customer need. Based on customer need ratings and sub-function, a product-function matrix was created. Additionally, a product-product matrix was generated to provide a similarity index among product families. A case study for implementing the functional architecture modeling was performed on the single use cameras.

• 대한안전경영과학회지
• /
• 제1권1호
• /
• pp.101-110
• /
• 1999

QFD is a market driven design and development methodology for products and services to meet or exceed customer's needs and expectations, This method enables to specify clearly the customer's needs and then evaluate the product capability in terms of its impact on meeting those needs. Process of satisfying customers begins with effectively soliciting their different needs and wants which may be non-technical and imprecise in nature. Although the HoQ is a comprehensive tool for showing the relationships between attributes, it lacks the flexibility to deal with the inherent inexactness and vagueness in the voice of customer. In this paper, fuzzy theory is introduced to overcome this limitation. Qualitative customer requirements are interpreted quantitative data through fuzzy inference procedure, and then target value is determined.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 2002년도 추계학술대회 논문집
• /
• pp.41-46
• /
• 2002

In the face of global competition, the requirements fer the continuously increasing productivity, flexibility and quality (dimensional accuracy, mechanical properties and surface properties) have imposed a major change on steel manufacturing industries. The automation of hot rolling process requires the developments of several mathematical models for simulation and quantitative description of the industrial operations involved. To achieve this objectives, a new loaming method with neural network to improve the accuracy of rolling force prediction in hot rolling mill is developed. Also, Genetic Algorithm(GA) is applied to select the optimal structure of the neural network and compared with that of engineers experience. It is shown from this research that both structure selection methods can lead to similar results.

• Communications for Statistical Applications and Methods
• /
• 제28권2호
• /
• pp.99-118
• /
• 2021

In this paper, we introduce an extended form of the inverse power Lomax model via Marshall-Olkin approach. We call it the Marshall-Olkin inverse power Lomax (MOIPL) distribution. The four- parameter MOIPL distribution is very flexible which contains some former and new models. Vital properties of the MOIPL distribution are affirmed. Maximum likelihood estimators and approximate confidence intervals are considered under Type I censored samples. Maximum likelihood estimates are evaluated according to simulation study. Bayesian estimators as well as Bayesian credible intervals under symmetric loss function are obtained via Markov chain Monte Carlo (MCMC) approach. Finally, the flexibility of the new model is analyzed by means of two real data sets. It is found that the MOIPL model provides closer fits than some other models based on the selected criteria.

• International Journal of Computer Science & Network Security
• /
• 제22권7호
• /
• pp.371-382
• /
• 2022

The trend of Bring Your Own Device (BYOD) is gaining popularity all over the world with its innumerable benefits such as financial gain, greater employee satisfaction, better job efficiency, boosted morale, and improved flexibility. However, this unstoppable and inevitable trend also brings its own challenges and risks while managing and controlling corporate data and networks. BYOD is vulnerable to attacks by viruses, malware, or spyware that can reach sensitive data and disclose information, modify access policies, disrupt services, create financial issues, minimise productivity, and entail some legal implications. The key focus of this research is how Saudi Arabia has approached BYOD with the help of their 5-step solution model and quantitative research methodology. The result of this study is a statement about what users know about this trend, their opinions about it, and suggestion to increase the employee awareness.

• 기술혁신학회지
• /
• 제18권1호
• /
• pp.1-27
• /
• 2015

우리나라는 글로벌 기술경쟁력 제고를 위해 연구개발에 대한 투자를 지속적으로 증대시켜왔다. 우리나라의 GDP대비 연구개발투자비는 4.15%로 세계 1위 수준이며, 이 가운데 기업부문은 전체 투자의 78.5%를 차지하며 매우 중요한 역할을 수행하고 있다. 그러나 더 이상 양적인 투자 증대에는 한계가 존재하기에 R&D투자에 대한 질적 수준을 높여 효율성을 제고하기 위한 노력이 절실히 필요한 실정이다. 이러한 연유로 본 연구에서는 기업의 경영성과를 제고하기 위한 방안을 강구하기 위한 연구를 수행하였다. 이를 위해 그동안 학문적으로 그 중요성이 강조된 연구개발 초기 단계인 기술전략과 기술기획 역량이 기업의 성과제고에 미치는 영향요인을 실증적으로 검증하고자 하였다. 실증분석 결과, 기술전략과 기술기획 활동이 경영성과 제고에 매우 유의미한 영향을 미치는 것으로 나타났으며, 조직유연성의 경우 개별적인 요인 또한 중요하지만 기술기획 활동을 긍정적으로 조절하여 경영성과 제고에 기여함을 확인하였다. 본 연구에서는 기업의 기술혁신 활동을 실제적으로 파악하기 위해 기업연구소를 운영하고 있는 전체 기업을 대상으로 표본조사를 수행하였으며, 분석방법으로는 다중회귀분석과 분위회귀분석을 활용하였다.