In this paper, we aim to improve the output quality of a food 3D printer through optimized component design and implementation. Existing 3D printers produce customized outputs according to consumer needs, but have problems with output speed and poor quality. In this paper, we aim to solve this problem through optimized design of unit parts such as the extruder, nozzle, guide, and external case. Fusion 360 was used for element design, and in the performance evaluation of the implemented system, the average precision was 0.06mm, which is higher than the non-repeatable precision of ±0.1㎜ of other products, and the feed speed of the existing system was evaluated to be more than twice as fast, from 70mm/s to 140mm/s. In the future, we plan to continuously research output elements that can produce texture and color and device control methods for convenience.

In this study, various pre-treatment methods were evaluated for microalgae separation. These methods aimed to facilitate safe, rapid, and cost-effective online imaging for real-time observation and cell counting. As pre-treatment techniques, heating, chemical hydrolysis, heating combined with chemical hydrolysis, and sonication were employed. The effectiveness of these methods was evaluated in the context of online imaging quality through experimentation on cultivated microalgae (Chlorella vulgaris and Scenedesmus quadricauda). The chemical treatment method was found to be inappropriate for improving image acquisition. The heating pre-treatment method exhibited a drawback of prolonged cell dispersion time. Additionally, the heating combined with chemical hydrolysis method was confirmed to have the lowest dispersion effect for Chlorella vulgaris. Conversely, ultrasonication emerged as a promising technique for microalgae separation in terms of repeatability and reproducibility. This study suggests the potential for selecting optimal pre-treatment methods to effectively operate real-time online monitoring devices, paving the way for future research and applications in microalgae cultivation and imaging.

우리나라는 삼면이 바다로 이루어져 있고, 이에 따라 많은 해양 시설로 인한 위험유해물질이 배출되고 있으나, 배출관리 및 규제 시스템이 미비한 상황이다. 따라서, 위험유해물질(HNS) 관리를 위하여 효율적으로 데이터를 수집할 수 있는 시스템이 필요하 다. 본 연구에서는 HNS 데이터를 효율적으로 관리 및 저장하기 위한 데이터 표준화 시스템을 설계하고 이의 표준화 방안을 제시하고 자 한다.

In this study, we focus on the improvement of data quality transmitted from a weather buoy that guides a route of ships. The buoy has an Internet-of-Thing (IoT) including sensors to collect meteorological data and the buoy’s status, and it also has a wireless communication device to send them to the central database in a ground control center and ships nearby. The time interval of data collected by the sensor is irregular, and fault data is often detected. Therefore, this study provides a framework to improve data quality using machine learning models. The normal data pattern is trained by machine learning models, and the trained models detect the fault data from the collected data set of the sensor and adjust them. For determining fault data, interquartile range (IQR) removes the value outside the outlier, and an NGBoost algorithm removes the data above the upper bound and below the lower bound. The removed data is interpolated using NGBoost or long-short term memory (LSTM) algorithm. The performance of the suggested process is evaluated by actual weather buoy data from Korea to improve the quality of ‘AIR_TEMPERATURE’ data by using other data from the same buoy. The performance of our proposed framework has been validated through computational experiments based on real-world data, confirming its suitability for practical applications in real- world scenarios.

탁주의 제조과정 중 사입량의 비율을 조절하여 담금 조건을 달리하는 증량 담금법과 3단 담금법으로 탁주를 제조하여 탁주의 품질특성을 조사하였 다. 3단 담금법에서 초기 당도가 높았으나, 발효가 진행됨에 따라 발효 6일차 까지는 10.5oBrix로 서서히 감소하다가, 그 이후 다시 상승하였다. 증량 담금법의 알코올 증가량은 3단 담금법에 비해 초기 발효속도는 완만했으나 발효완료 시 16.0%에 도달한 반면, 3단 담금법은 초기 발효속도가 빨랐으나, 14.9%로 발효가 완료되었다. 초기 아미노산도는 3단 담금법에서는 2.3%로 높았으나, 증량 담금법은 아미노산도가 서서히 증가하여 발효완료시 3.2%였고, 3단 담금법에서는 3.3%에 도달하였다. 증량 담금법에서 Sake meter value (SMV)는 발효 3일차에 -13.1까지 감소하였으나, 그 이후 지속적으로 증가하여 발효 종료시 11.3으로 나타났다. 관능검사 결과 전반적 기호도는 단맛과 쓴맛의 기호도가 우수했던 증량 담금법에서 더 높게 나타났다.

Ball stud parts are manufactured by a cold forging process, and fastening with other parts is secured through a head part cutting process. In order to improve process quality, stabilization of the forging quality of the head is given priority. To this end, in this study, a predictive model was developed for the purpose of improving forging quality. The prediction accuracy of the model based on 450 data sets acquired from the manufacturing site was low. As a result of gradually multiplying the data set based on FE simulation, it was expected that it would be possible to develop a predictive model with an accuracy of about 95%. It is essential to build automated labeling of forging load and dimensional data at manufacturing sites, and to apply a refinement algorithm for filtering data sets. Finally, in order to optimize the ball stud manufacturing process, it is necessary to develop a quality prediction model linked to the forging and cutting processes.

The cutting quality of abrasive water jet cutting of aluminum alloy(Al-5083) for shipbuilding is affected by the surface roughness, cutting pressure, cutting speed, and the distance between nozzle and material. The cross-section of water jet cutting is formed a V-shape as the cutting speed increase. The upper width(kerf width) is wide and the lower surface is narrow. The width of cutting cross-sections are effected in the order of cutting speed, cutting pressure, and distance between nozzle and material. From the experimental results, to improve of cutting quality of abrasive water jet cutting of aluminum alloy(Al-5083) for shipbuilding, the optimal cutting conditions to improve the surface roughness and kef width are proposed and discussed.

PURPOSES : The purpose of this study is to identify a gradation control method that minimizes the volatility of recycled aggregates to maintain the quality of reclaimed asphalt mixtures. METHODS : In this study, two types (0~13 and 0~10 mm) of recycled aggregate stockpiles with an extraction viscosity of 40,000 poise and a 19 mm hot asphalt mixture with virgin aggregates are used. The test methods are evaluated for plastic deformation resistance using the Hamburg wheel-tracking test and for low-temperature crack resistance using the dynamic modulus test. In the field, the performance is evaluated via an accelerated pavement test. RESULTS : The Hamburg wheel-tracking test shows good water resistance as well as less than 5 mm of deformation. The result of a dynamic modulus test at -5 °C shows a 92.9% low-temperature crack resistance as compared with that of the 19 mm dense grade hot-mix asphalt mixture. The result of the accelerated pavement test confirms that the performances of the 19 mm dense grade hot-mix asphalt mixture and reclaimed asphalt mixture are equal owing a 1.2 cm plastic deformation. CONCLUSIONS : By evaluating the plastic deformation resistance and crack resistance of the reclaimed asphalt mixture based on a stockpile gradation controlled at 0~10 mm via an indoor test, it is discovered that the plastic deformation resistance increases partially, whereas the crack resistance remains almost unchanged. The accelerated pavement test confirms that a performance equivalent to that of a 19 mm dense grade hot-mix asphalt mixture is achieved.

Along with the increase in demand for rescue services, the types of rescue services are also diversifying. Accordingly, rescue workers are exposed to various unpredictable dangerous situations, and the possibility of safety accidents is increasing, so the need for systematic management of safety accidents by rescue teams is emerging. It is necessary to present a roadmap for improving the quality of rescue services. An integrated technology roadmap tool that can be used immediately to improve structural quality was applied. The driving elements of the roadmap are composed of three elements that constitute the improvement of structural quality. It can be divided into safety management, professional competence and other (policy support) fields. This study intends to present a long-term and short-term roadmap by dividing it into safety management, professional competency, and other (policy support) fields.