• 대한기계학회논문집
• /
• 제19권6호
• /
• pp.1490-1500
• /
• 1995

Compression molding of SMC (Sheet Molding Compound) in a thin plaque with substructures like a rib is involved with the formation of surface defect along the centerline over the rib area called by sink mark depending on process parameters. The surface quality of the external panels in automotive manufacturing is so critical that this kind of defect should be eliminated during manufacturing stages. The effect of process parameters on sink mark formation and the distribution of chopped fiberglasses in the compression molded thin plaque with a rib was experimentally investigated in the present study. In order to estimate the effect of the molding parameters such as molding temperature, mold closing speed, depth of the rib, corner radius of the rib, and final molded part thickness of flat portion on the depth of sink mark and the distribution of fiberglasses in the molded SMC part with the rib under the present experimental conditions, the molding parameters used in experiments were non-dimensionalized equation for predicting the depth of sink mark was determined through dimensional analysis based on the experimental data. The orientation and distribution of fiberglasses and fillers which directly affect the formation and depth of sink mark were investigated by taking the photographs of the cross-sectional area of the molded specimen using scanning electron microscope. The experimental results proposed from this investigation are useful in understanding the formation of sink mark and predicting the depth of sink mark in compression molding of SMC with substructures.

• 한국생산제조학회지
• /
• 제22권4호
• /
• pp.686-692
• /
• 2013

Today, environmental issues have become a matter of worldwide concern. In particular, automobile industries engage in considerable research and investment to develop high-efficiency and ecofriendly cars. Most ecofriendly cars use natural gas or hydrogen gas instead of fossil fuels. In this regard, low-weight and high-pressure vessels have gradually been developed to increase the driving distance of a car. However, most pressure vessels installed in cars develop many defects over time owing to shocks sustained when the car is being driven. Such defects can cause the explosion of the pressure vessel. Therefore it is important to prevent such explosions due to internal defects. The use of shearography for measuring the internal defects of objects afford many advantages. It is a non-contact and non-destructive method, and it is not limited by the object shape. In this study, the internal defect deformation and strain of an aluminum liner that is used in a CNG bus for the fuel storage tank is measured using shearography. It is important to measure the strain and deformation in order to detect defects and repair the pressure vessel. To verify the accuracy of the shearography measurement method, the measurement results of shearography, out-of-plane ESPI, and FEM are compared quantitatively.

• 한국산학기술학회논문지
• /
• 제18권2호
• /
• pp.335-341
• /
• 2017

본 논문은 모터 샤프트 제조 공정에서 발생하는 이중컷 불량을 검사하기 위한 영상 처리 알고리즘을 제안하였다. 알고리즘은 영상의 밝기를 이용하여 외곽선을 추출하는 단계와 추출된 외곽선을 이용하여 이진화된 경계선 그래프를 구하는 단계, 최종적으로 이진화된 경계선 그래프를 이용하여 불량품을 판정하는 단계로 구성된다. 본 논문에서는 두 절단면이 분리되어 있는 결함과 두 절단면이 연결되어 있는 결함을 각각 type 1 결함과 type 2 결함이라고 정의하였다. 실제 제조 과정에서 112개의 양품과 44개의 불량품 (type 1 불량 34개 및 type 2 불량 10개) 샘플을 수집하였으며, 수집한 샘플을 이용하여 제안된 알고리즘을 검증하였다. 알고리즘 시험 결과 100% 정확도로 양품과 불량품을 판정하였으며, 불량품의 경우도 type 1 불량과 type 2 불량을 정확히 구분하는 것으로 확인되었다. 본 논문에서 제안한 알고리즘은 추가적으로 다양한 샘플에 대해 신뢰성을 확보한 후 실제 현장에 사용할 계획이다.

• 한국융합학회논문지
• /
• 제8권11호
• /
• pp.43-48
• /
• 2017

반도체는 산업 기술의 발전을 주도하고 있는 첨단기술로서 전자제품의 소형, 경량화 달성으로 전자산업 시장을 끌어가고 있는 상황이다. 특히 반도체 생산 공정은 정밀하고 복잡한 공정으로 이루어져 있어 효과적인 생산이 필요하며, 최근 불량 검출을 위하여 컴퓨터와 카메라를 융합한 비전 시스템이 활용되고 있고, 특수한 공정에 의하여 가공된 미세 패턴의 형상을 측정하기 위한 시스템의 수요가 급속하게 증대되고 있다. 본 논문에서는 반도체 패키지의 스크래치 결함을 검출하기 위하여 마스크 이미지를 이용한 비전 알고리즘을 제안한다. 제안 시스템을 통하여 반도체 패키지 생산 공정에 적용하면 생산관리를 원활하게 할 수 있고, 빠른 패키지의 불량 판정으로 생산의 효율성이 높아질 것으로 기대된다.

• 한국정밀공학회지
• /
• 제32권6호
• /
• pp.529-536
• /
• 2015

A defect could be generated in bolts for a use of oil filters for the manufacturing process and then may affect to the safety and quality in bolts. Also, fine defects may be imbedded in oil filter system. So it is very important that such defects be investigated and screened during the multiple manufacturing processes. Therefore, in order effectively to evaluate the fine defects, the FEM simulations were performed to make characterization in the crack detection of the bolts and the parameters such as number of turns of the coil, the coil size, applied frequency were calculated based on the simulation results. Simulations were carried out for the defect signal of eddy current probe. Exciter and receiver were utilized. In this paper, the FEM simulations were performed in both bobbin-type and pancake-type probe, both probes were optimized under Eddy current FEM simulations and the results of calculation were discussed.

• Smart Structures and Systems
• /
• 제22권4호
• /
• pp.481-493
• /
• 2018

Ultrasonic guided waves have attracted increasing attention for non-destructive testing (NDT) and structural health monitoring (SHM) of bridge cables. They offer advantages like single measurement, wide coverage of acoustical field, and long-range propagation capability. To design defect detection systems, it is essential to understand how guided waves propagate in cables and how to select the optimal excitation frequency and mode. However, certain cable characteristics such as multiple wires, anchorage, and polyethylene (PE) sheath increase the complexity in analyzing the guided wave propagation. In this study, guided wave modes for multi-wire bridge cables are identified by using a semi-analytical finite element (SAFE) technique to obtain relevant dispersion curves. Numerical results indicated that the number of guided wave modes increases, the length of the flat region with a low frequency of L(0,1) mode becomes shorter, and the cutoff frequency for high order longitudinal wave modes becomes lower, as the number of steel wires in a cable increases. These findings were used in design of transducers for defect detection and selection of the optimal wave mode and frequency for subsequent experiments. A magnetostrictive transducer system was used to excite and detect the guided waves. The applicability of the proposed approach for detecting and locating wire breakages was demonstrated for a cable with 37 wires. The present ultrasonic guided wave method has been found to be very responsive to the number of brokenwires and is thus capable of detecting defects with varying sizes.

• 한국기계가공학회지
• /
• 제10권6호
• /
• pp.128-133
• /
• 2011

In this study, the steel material for shipbuilding(LR-A class) was used, and FCAW was taken advantage of 3G attitude and they are welded by different welding ways. As a result of analyzing wave with welding monitoring system, the stable values are obtained which are the first floor(electronic current 164~182 A, voltage 24 V), the second floor(electronic current 174~190 A, voltage 22~25 V), the third floor(electronic current 158~188 A, voltage 22~25 V), and fourth floor(electronic current 172~184 A, voltage 22~25 V), at this time, the stable wave standard deviation and changing coefficient could be obtained. When the welding testing through nondestructive inspection was analyzed know defect of welding, there was no defect of welding in A, D, E, but some porosities in B, and slag conclusion near the surface in C, because the length of arc was not accurate, and the electronic current and voltage was not stable. After observing the change of heat affect zone through micro testing, each organization of floor formed as Grain Refinement, so welding part was fine, the distance of heat affect zone is getting wider up to change the values of the electronic current and voltage. As a result of degree of hardness testing, the hardness orders were the heat affect zone(HAZ), Welding Zone(WZ), and Base Metal(BM). When the distribution of degree of hardness is observed. B is the highest degree of hardness The reason why heat effect zone is higher than welding zone and base metal, welding zone is boiled over melting point($1539^{\circ}C$) and it starts to melt after the result of analysis through metal microscope, so we can know that delicate tissue is created at the welding zone. Therefore, in order to get the optimal conditions of the welding, the proper current of the welding and voltage is needed. Furthermore the precise work of welding is required.

• 한국융합학회논문지
• /
• 제9권3호
• /
• pp.53-59
• /
• 2018

본 논문에서는 스마트 공장에서 의사결정 모델을 이용한 순차 마이닝 기반 제조공정을 제안한다. 제안하는 모델은 소규모의 제조공정에서 순차 마이닝 의사결정 모델을 적용하여 제조 효율을 높이는 방법이다. 제조 단계 중 제품 제조 과정에서 나타나는 데이터를 입력 변수들로 구성하고, 시간당 제조량과 불량률을 출력 변수로 구성한다. t-검정을 통해 유의수준이 높은 변수만을 사용하여 GSP 알고리즘과 REPTree 알고리즘을 이용한 규칙과 모델을 생성한다. 의미있는 순차 규칙과 의사결정 모델은 정확도, 민감도, 특이성, 예측도를 통해 유의미함을 확인한다. 결과적으로, 실제 제조에 적용한 결과 불량률은 0.38%가 개선되었고, 시간당 제조량은 평균 1.89/h 증가되었다. 이는 소규모 제조 공정에서 데이터 마이닝 분석을 통한 제조 효율을 높이기 위한 의미있는 결과를 나타낸다.

• 한국기계가공학회지
• /
• 제18권9호
• /
• pp.44-51
• /
• 2019

Three types of samples with defects were measured by lock-in med-IR (infrared) thermography with various lock-in frequencies for different materials. The lock-in method can be used to detect defects when an external energy source is applied to the object, the non-uniformity of the incident thermal energy distribution is eliminated, and the camera's measurement cycle is synchronized with the load cycle of the incident energy source. For inspecting samples with defects, results of thermal images are analyzed when three types of materials, i.e., SM45C, STS316L, and AL6061 are tested and three lock-in frequencies, i.e., 0.08, 0.1, and 0.12 Hz are applied. In this study, the optimal lock-in frequencies were determined by comparing the results of each material and lock-in frequency measured using the mid-IR camera.

• 한국정보통신학회논문지
• /
• 제21권11호
• /
• pp.2037-2042
• /
• 2017

스마트 공장은 미리 입력된 프로그램에 의해 생산시설이 수동적으로 움직이는 공장 자동화 작업 방식과는 달리, 생산 설비 스스로 작업 방식을 결정하여야 한다. 생산 설비 스스로 작업 방식을 결정이라 함은, 이를테면 제조 현장에서 설비의 노후, 문제 발생 예측, 제품의 불량 검출 등과 같은 이상 징후가 발생할 시 이를 조기에 발견한 후 스스로 문제를 해결하는 것을 의미한다. 본 논문에서는 제조 현장의 제조 공정 이상 징후 감지를 위해 대기행렬을 이용한 제조 공정 모델링을 제시하고 해당 모델링에서 이상 징후를 기계학습 기술 중 하나인 SVM을 이용하여 이를 감지하도록 한다. 해당 대기행렬을 M/D/1을 사용하였으며, ${\mu}$, ${\lambda}$, ${\rho}$를 기반으로 컨베이어 벨트 제조 시스템을 모델링하였다. SVM을 이용하여 ${\rho}$의 변화량을 통해 이상 징후를 감지했다.