본 연구는 태양광 기반으로 인공광 병렬 광공급 시스템을 개발하고 상추 재배효과를 구명하기 위하여 수행하였다. 태양광 기반으로 인공광원을 공급하는 장치는 광원 공급부, 전원 공급부, 시스템 계측 및 제어부로 구성하였다. 광원공급부는 태양광 전송장치(광파이버)와 LED 램프(인공광)로 구성하였고, 태양광 전송장치는 광 전송률이 우수한 석영재질의 광섬유(Optical fiber)로 제작되었으며, 인공광은 LED 중 White 램프를 사용하였다. 전원 공급부는 누전 차단기, SMPS, LED 제어기 및 릴레이로 구성하였다. 시스템계측 및 제어부는 터치스크린과 지그비(ZigBee) 통신모듈, 광량센서로 구성하였다. 구성한 장치의 성능시험 결과 광량센서로 측정된 강도가 200μmol·m-2·s-1 이하가 되면 자동적으로 LED 램프가 작동되어 보광하는 것을 확인하였다. 또한 본 장치를 활용하여 상추를 재배한 결과, 엽장, 뿌리길이, 엽록소 함량 및 지하부 생체중이 LED 처리보다 큰 것으로 나타났다. 따라서 본 장치 는 화석연료 고갈 등으로 전기 사용에 제한이 올 때 폐쇄형 식 물공장 같은 시설에서 작물을 재배할 수 있을 것으로 판단된다.

본 연구는 폐쇄형 식물공장에서 시금치 수경재배시 세가지의 인공광이 생육, 광합성 및 품질에 미치는 영향을 규명하기 위해 수행되었다. 세가지 광 처리구는 적색 (660nm), 청색 (450nm) 및 녹색 (550nm) LED를 사용하여, R660 / B450 = 4/1 (RBL), R660 / B450 / G550 = 5/2/3 (WWL); R660 / B450 / G550 = 1/1/1 (WL) 비율로 혼합하였고, 동일한 광도로 설정하였다 (PPFD = 190 μmol‧m-2 ‧s-1). 생육조사결과 초장, 엽수는 WL이 가장 적었다. SPAD, 순광합성율, Fv/Fm, LAI, 근권부 생육은 RBL이 가장 높았고 통계적으로 유의하였다. 줄기, 잎, 뿌리의 생체중, 뿌리의 건물중은 세가지 처리구에서 유의한 차이를 보였다. 대조적으로 WL의 칼륨의 함량은 WWL과 RBL 가운데 가장 높았지만, 반면 칼륨과 철의 함량은 RBL이 가장 높았다. 비타민C 함량도 시험구간 유의한 차이를 보였다. 질소와 옥살산 함량은 WL이 가장 높았고, 용해성 고체와 비타민C 함량은 RBL이 가장 높았다. 옥살산, 질소 함량은 WWL에서 감소하는 경향을 보였고, RBL의 옥살산 함량은 WL와 WWL과 차이가 없었다. 모든 처리구에서 Salmonella, E.coli.는 감염되지 않았다. 결론적으로, RBL이 시금치의 생육에 적합하지만, 적색, 청색과 적정하게 혼합된 녹색광은 시금치의 생육에 긍정적인 영향을 미친다고 판단된다.

To enhance the effectiveness of the FMS (flexible manufacturing system), it is necessary for the manufacturing control system to be upgraded by integrating the cyber and the physical manufacturing systems. Using the CPPS (Cyber-Physical Production System) concept, this study proposes a 4-stage vertical integration and control framework for an aircraft parts manufacturing plant. In the proposed framework, the process controller prepares the operations schedule for processing work orders generated from the APS (advanced planning & scheduling) system. The scheduled operations and the related control commands are assigned to equipments by the dispatcher of the line controller. The line monitor is responsible for monitoring the overall status of the FMS including work orders and equipments. Finally the process monitor uses the simulation model to check the performance of the production plan using real time plant status data. The W-FMCS (Wing rib-Flexible Manufacturing Control & Simulation) are developed to implement the proposed 4-stage CPPS based FMS control architecture. The effectiveness of the proposed control architecture is examined by the real plant’s operational data such as utilization and throughput. The performance improvement examined shows the usefulness of the framework in managing the smart factory’s operation by providing a practical approach to integrate cyber and physical production systems.

Recently, as the quality of life of modern people improves, interest in environmental noise is gradually increasing. As the public's awareness of environmental rights increased, it was necessary to grasp the actual condition of the noise source and systematic noise management plan. The data is expected to be used as a response to noise-related complaints. As a result measured using the factory noise monitoring system, the amount of data measured every 5 minutes from 00:00 to 24:00 can obtain 288 noise levels and frequency characteristics per day, and frequency using 1/3 octave-band. The analysis reveals what frequency range affects the noise from the metal working plant near the office. In addition, it can be seen that it is possible to compare with the reference value by using the stored data divided into night time, day time, and evening time for each time zone, and it is determined that it is possible to secure smooth data about the noise source to be measured.

The South Korean government is actively assisting the supply of the smart factory solutions to SMEs (Small & Medium-sized Enterprises) according to its manufacturing innovation 3.0 policy for the smart manufacturing as the 4th industrial revolution era unfolds. This study analyzed the impacts of the smart factory solutions, which have been supplied by the government, on the companies performances. The effects of the level of smart factory and the operation capabilities for the smart factory solutions on company performances, and the mediating effects of manufacturing capabilities have been analyzed using SPSS and AMOS. The data for this survey-based study were collected from the SMEs which implemented the smart factory solutions since 2015. The results show that the level of smart factory solutions adopted and operation capabilities for the smart factories do not have direct effects on the company performances, but their mediating effects on the manufacturing capabilities matter and the manufacturing capabilities effect directly on the company performances. In addition significant factors boosting the operation capability for the smart factory and the levels of the smart factory solutions are identified. Finally, the policy direction for enhancing the smart factory effects is presented, and the future research directions along with the limitations are suggested.

This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

식물공장에 재배 가능한 작물은 매우 다양할 것으로 본다. 식물공장에서 재식밀도에 대한 중요성이 인식되고 있다. 본 연구는 완전제어형 식물공장에서 콜라비의 재배에 적합한 재식밀도를 구명하기 위하여 수행되었다. 식물공장 형태는 형광등을 이용한 완전제어형태로, 박막수경재배를 이용하여 재배하였다. 재식밀도는 22plants/m2(15×30cm), 27 plants/m2(15×25cm), 그리고 33 plants/m2(15×20cm)로 처리 하였다. 식물체당 지상부 생체중과 건물중 또는 식물체당 벌브의 지상부 생체중와 건물중에는 재식밀도간 유의적인 차이를 보이지 않았다. 단위면적당 지상부 생체중과 건물중 또는 단위면적당 벌브의 지상부 생체중과 건물중에는 재식밀도가 높은 처리구(33plants/m2)에서 높게 나타났다. 재식밀도와 초장, 엽면적, 광합성, 경도 및 엽록 소간에는 유의적인 차이를 보이지 않았다. 재식밀도와 벌브 높이와 지름 및 당도간에는 유의적인 차이를 보였다. 재식밀도가 낮은 22plants/m2 처리구에서 가장 높은 벌브 높이와 지름을 보였으며, 당도 또한 높았다. 이상의 결과를 바탕으로 결론을 내리면, 경제성을 고려한 생육적인 측면에서는 단위면적당 생산량이 많은 재식밀도 33plants/m2 (15×20cm)가 적정하였으나, 당도와 같은 품질적인 측면에서는 재식밀도 22plants/m2 (15×30cm)가 적정하였다.

The study aimed to determine effects of light emitting diode (LED) and the ultraviolet radiation (UVA) light of plant factory on plant growth and ascorbic acid content of spinach (Spinacia oleracea cv. Shusiro). Plants were grown in a NFT (Nutrient Film Technique) system for 28 days after transplanting with fluorescent light (FL, control), LEDs and UVA (Blue+UVA (BUV), Red and Blue (R:B(2:1)) + UVA (RBUV), Red+UVA (RUV), White LED (W), Red and Blue (R:B(2:1)), Blue (B), Red (R)) under the same light intensity (130 μmol·m-2·s-1) and photoperiod (16/8h = day/night). All the light sources containing the R (R, RB, RUV, and RBUV) showed leaf epinasty symptom at 21 days after transplanting (DAT). Under the RUV treatment, the lengths of leaf and leaf petiole were significantly reduced and the leaf width was increased, lowering the leaf shape index, compared to the R treatment. Under the BUV, however, the lengths of leaf and leaf petiole were increased significantly, and the leaf number was increased compared to B. Under the RBUV treatment, the leaf length was significantly shorter than other treatments, while no significant difference between the RBUV and RB for the fresh and dry weights and leaf area. Dry weights at 28 days after transplanting were significantly higher in the R, RUV and BUV treatments than those in the W and FL. The leaf area was significantly higher under the BUV treatment. The ascorbic acid content of the 28 day-old spinach under the B was significantly higher, followed by the BUV, and significantly lower in FL and R. All the integrated data suggest that the BUV light seems to be the most suitable for growth and quality of hydroponically grown spinach in a plant factory.