In light of the expanding use of technology in education, we attempted to analyze how Korean college students perceived the use of Machine Translation (MT) tools in the classroom. Specifically, this study attempted to explore students’ perceptions of their ability to use MT tools and to measure the reliability of the MT-generated output, along with measuring students’ general sense of confidence in English learning. This research analyzed 183 EFL college students’ responses to an online survey, and a one-way ANOVA was used to test for the differences in the averages of three groups. The results of data analysis revealed that 1) Among beginners, intermediate learners, and advanced learners, those self-identifying as advanced had the highest scores on all the factors measured.; 2) There was a significant mean difference in students’ perceptions of the ability to use MT tools, their beliefs regarding MT’s effectiveness as a learning tool, and affective attitudes towards the use of MT tools between beginner and advanced groups. Based on the findings, pedagogical implications for the effective use of MT tools in the Korean EFL classrooms, and suggestions for future research were presented.

The purpose of this research is to find out how EFL college learners utilized machine translation while writing their presentation scripts. Specifically, it attempted to examine the characteristics of the English translation outputs by MT and students’ self-edited drafts, and their perceptions toward the use of MT in English writing classes. Six college students were asked to submit one Korean draft, two machine translation drafts, and one self-edited draft, and two in-depth interviews were conducted with each of the participants during the course of the semester. Grammarly (2022), a free online grammar and spelling checker, was used to examine the characteristics of the collected writings, and Miles and Huberman’s (1994) three-step analytic method was employed to analyze the data from the in-depth interviews. The results of data analysis revealed that 1) there were more lexical errors than grammatical errors, and the number of the errors did not show a big difference between the different drafts; 2) Also, students viewed the use of MT in the English writing classes positively but found it difficult to properly use. Based on the research findings, pedagogical implications for the effective use of MT in English writing classes were suggested.

In the process of cutting large aircraft parts, the tool may be abnormally worn or damaged due to various factors such as mechanical vibration, disturbances such as chips, and physical properties of the workpiece, which may result in deterioration of the surface quality of the workpiece. Because workpieces used for large aircrafts parts are expensive and require strict processing quality, a maintenance plan is required to minimize the deterioration of the workpiece quality that can be caused by unexpected abnormalities of the tool and take maintenance measures at an earlier stage that does not adversely affect the machining. In this paper, we propose a method to indirectly monitor the tool condition that can affect the machining quality of large aircraft parts through real-time monitoring of the current signal applied to the spindle motor during machining by comparing whether the monitored current shows an abnormal pattern during actual machining by using this as a reference pattern. First, 30 types of tools are used for machining large aircraft parts, and three tools with relatively frequent breakages among these tools were selected as monitoring targets by reflecting the opinions of processing experts in the field. Second, when creating the CNC machining program, the M code, which is a CNC auxiliary function, is inserted at the starting and ending positions of the tool to be monitored using the editing tool, so that monitoring start and end times can be notified. Third, the monitoring program was run with the M code signal notified from the CNC controller by using the DAQ (Data Acquisition) device, and the machine learning algorithms for detecting abnormality of the current signal received in real time could be used to determine whether there was an abnormality. Fourth, through the implementation of the prototype system, the feasibility of the method proposed in this paper was shown and verified through an actual example.

본 사례는 공작기계산업의 A사에서 수행한 R&D 개발완료 과제 79건을 대상으로 R&D 효율성을 DEA를 활용하여 분석하고, 그 개선방안을 제시한 것이다. DEA 분석에서투입변수는 R&D 투자비와 연구인력 맨먼스, 산출변수는 개발기간 목표달성률과 예상매출액(5년간)으로 설정하였으며, 표본은 제품, 선행기술, 제어기술로 구분하여 분석하였다. 여기서선행기술은 제품성능을 위한 요소기술과 응용프로그램을 개발하는 것이고 제어기술은 컴퓨터를 토대로 수치제어 프로그램을 설계하는 것이다. 분석결과에 따르면 제품, 제어기술, 선행기술 순으로 효율적으로 운영되고 있어 선행기술의 효율성이 가장 낮았다. 그 이유는 선행기술의 불학실성에 기인한다. 선행기술은 개발목표를 정하기 어렵고 개발계획도 수립하기 어렵다. 심지어 운영하는 과정에도 환경변화가 영향을 미친다. 투자효율성 분석결과에서 CRS는 제품 34.6%, 선행기술 14.3%, 제어기술 38.9%이다. IRS는 제품 53.8%, 선행기술 85.7%, 제어기술 38.9%이다. DRS는 제품 11.5%, 선행기술0%, 제어기술 22.2%이다. 전체적으로 본 사례는 과다투입보다는 과소투입이 문제가 되고 있다. 이는 R&D 투자 부족을 의미한다. 주목할 부분은 기업의 미래 경쟁력이 될 수 있는 응용기술에 대한 과소투입이 심각하다는 것이다. 비효율적 DMU의 효율적 운영을 위해서는 최적의 투입량을 관리해야하며, 이것은 준거집단과의 비교를 통해 구할 수 있다.

Intelligent machines respond to external environments on the basis of decisions that are made by sensing the changes in the environment and analyzing the obtained information. This study focuses on the construction of a knowledge base which enables decision making with that information. Approximately 70% of all errors that occur in machine tools are caused by thermal error. In order to proactive deal with these errors, a system which measures the temperature of each part and predicts and compensates the displacement of each axis has been developed. The system was built in an open type controller to enable machine tools to measure temperature changes and compensate the displacement. The construction of a machining knowledge base is important for the implementation of intelligent machine tools, and is expected to be applicable to the network based intelligent machine tools which look set to appear sooner or later.

신뢰성이란 단기간에 측정되는 성능과는 다른 지표로서 흔히 장기간에 걸쳐 평가되는 품질의 척도이다. Oil Cooler는 공작기계(machine tools)의 주축 및 구동부 등에서 발생하는 열 변형을 제어하는 장치로서 공작기계의 신뢰성 향상을 위해서는 oil cooler의 신뢰성 개선이 이루어져야 한다. 본 연구에서는 oil cooler의 신뢰성 개선을 위해 고장률 데이터베이스를 이용한 신뢰성 예측과 이를 통한 취약부품 분석을 실시하고 신뢰성 시험기를

  In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence are applied for many industrial products and machine tools are the center of manufacturing devices in intelligent manufacturing devices. T

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence are applied for many industrial products and machine tools are the center of manufacturing devices in intelligent manufacturing devices. The purpose of this paper is to present the design of Decision Support Agent that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It communicates with other active agents such as sensory and dialogue agent. The proposed design of decision support agent facilitates the effective operation and control of machine tools and provides a systematic way to integrate the expert's knowledge that will implement Intelligent Machine Tools.