이현오

전광민

이기선

여창모

권백규

권오민

이진원

이인혁

유은섭

김태윤

배연주

김봉철

박상진

김지윤

이재선

이재철

전영준

박선아

The Engineering Information Fusion Lab, led by Professor Doohwan Mun, collaborates with LG Electronics on design automation and verification. It also engages in research and development cooperation with Hyundai Engineering, focusing on intelligent design automation.

문두환 교수가 이끄는 엔지니어링정보융합 연구실은 LG전자와 설계 자동화 및 검증 분야에서 협력한다. 현대엔지니어링과는 지능형 설계 자동화에 중점을 둔 연구 개발 협력을 수행한다.

Point Cloud Registration Using PCA and Hyperparameter Optimization

Enhancing Chromium Coating Thickness Estimation with Multi-head Attention LSTM and Data Augmentation

Hybrid Approach for Comprehensive Recognition of Line Objects Contained in High-Density Piping and Instrumentation Diagrams Using Deep Learning and Rules

Toward fully automated CAD-CAE integration through design feature recognition and small language models

Generative 3D Appearance Design: A Survey of Generation, Segmentation and Editing by Artificial Intelligence

Automated inspection of P&ID object recognition using deep learning

Replacing NURBS surfaces with analytic surfaces based on isocurve characteristics in B-rep models

Human and Humanoid in-the-Loop (HHitL) Ecosystem: An Industry 5.0 Perspective

Optimizing Image Format P&ID Recognition: Integrating Symbol and Text Recognition with a Single Backbone Architecture

Rule-based design verification for mechanical parts with dynamic rule subset selection

Graph Neural Network-based Method for Classifying Continuous Lines in Piping and Instrumentation Diagram

Inherent risks identification in a contract document through automated rule generation”, Automation in Construction, Vol. 172, 106044

DFGAT for recognizing design features from a B-rep model for mechanical parts”, Robotics and Computer-Integrated Manufacturing, Vol. 93, 102938

Operation status diagnosis of an underwater cutting robot using adaptive weighted parallel 1D-DenseNet”, International Journal of Precision Engineering and Manufacturing-SMART TECHNOLOGY, Vol. 3, pp. 7-16

BRepQL: Query language for searching topological elements in B-rep models”, Computers in Industry, Vol. 164, 104207

CNN-based weight estimation from point clouds obtained from walking breed sows”, Smart Agricultural Technology, Vol. 9, 100611

Relational descriptors for retrieving design features in a B-rep model using the similarity-based retrieval approach

Retrieval of CAD part models complying with design specification using a relational design rule-embedded BOM

Construction of Design Requirements Knowledgebase from Unstructured Design Guidelines Using Natural Language Processing

Rule-based continuous line classification using shape and positional relationships between objects in piping and instrumentation diagram

Hybrid MLP-CNN-based ground sink susceptibility prediction in urban area using underground pipe map

BRepGAT: Graph Neural Network to Segment Machining Feature Faces in a B-rep Model

Development of Customized Ankle-Foot-Orthosis using 3D Scanning and Printing Technologies

Simplification of 3D CAD Model in Voxel Form for Mechanical Parts Using Generative Adversarial Networks

Machining feature recognition using descriptors with range constraints for mechanical 3D models

Deep learning-based weight estimation using a fast-reconstructed mesh model from the point cloud of a pig

Extraction of Line Objects from Piping and Instrumentation Diagrams Using an Improved Continuous Line Detection Algorithm

Lightweight model-based weld line generation and its applications to support the construction of ships and offshore plants

Machine-learning-based ground sink susceptibility evaluation using underground pipeline data in Korean urban area

Use of asset administration shell coupled with ISO 15926 to facilitate the exchange of equipment condition and health status data of a process plant

3D Convolutional Neural Network for Machining Feature Recognition with Gradient- Based Visual Explanations from 3D CAD Models

End-to-end digitization of image format piping and instrumentation diagrams at an industrially applicable level

Deep learning-based digitalization of a part catalog book to generate part specification by a neutral reference data dictionary

Iterative offset-based method for reconstructing a mesh model from the point cloud of a pig

Dataset and method for deep learning-based reconstruction of 3D CAD models containing machining features for mechanical parts

Machining feature recognition based on deep neural networks to support tight integration with 3D CAD systems

Deep learning-based method to recognize line objects and flow arrows from image-format piping and instrumentation diagrams for digitalization

Reconstruction of primitive-shaped pipe elbows from a triangular mesh in ship outfitting model

Manufacturability Evaluation of Parts Using Descriptor-based Machining Feature Recognition

Robust generation of the delta volume for the damaged area of a part using the marching cubes algorithm to support additive manufacturing–based part maintenance

Deep learning-based recognition of symbols and texts at an industrially applicable level from high-density piping and instrumentation diagram images

Mesh-offset-based method to generate a delta volume to support the maintenance of partially damaged parts through 3D printing

Neutral model-based interfacing of 3D design to support collaborative project management in the process plant industry

Practical method for the fast generation of a CAM model for jet engine parts

A method of generating depth images for view-based shape retrieval of 3D CAD models from partial point clouds

Lifecycle management of component catalogs based on a neutral model to support seamless integration with plant 3D design

Deep-learning-based retrieval of piping component catalogs for plant 3D CAD model reconstruction

Multiobjective evolutionary optimization for feature-based simplification of 3D boundary representation models

A method to minimize the data size of a lightweight model for ship and offshore plant structure using part characteristics

Deep learning applications in an industrial process plant: Repository of segmented point clouds for pipework components”, JMST Advances, Vol. 2, No. 1, pp. 15-24

Semantics-aware adaptive simplification for lightweighting diverse 3D CAD models in industrial plants

ISO 15926–based integration of process plant life-cycle information including maintenance activity

Features recognition from piping and instrumentation diagrams in image format using a deep learning network

Part recognition-based simplification of triangular mesh models for ships and plants

Maintenance Framework for Repairing Partially Damaged Parts Using 3D Printing

B-rep model simplification using selective and iterative volume decomposition to obtain finer multi-resolution models

Part library-based information retrieval and inspection framework to support part maintenance using 3D printing technology

User-assisted integrated method for controlling level-of-detail of large-scale B-rep assembly models

Similarity comparison of original and remodeled plant 3D piping CAD models using quantitative evaluation metrics for offshore plants

Standardized exchange of plant equipment and materials data

오프로드 환경에서의 주행 가능 영역 추정을 위한 SalsaNext 기반 점군 분할 방법

3차원 지반모델링 기반의 지반함몰 위험 지반 레이어 개발 방법

합성 데이터와 텍스트-심볼 통합 검출을 활용한 이미지 형식 P&ID 인식 기법

P&ID 디지털화를 위한 DEXPI 기반 지능형 저작 시스템 개발

배관 및 기기 공종의 중립 형식의 플랜트 3D CAD 모델 가시화 시스템 개발

홀과 노즐을 고려한 플랜트 기기 스펙-카탈로그 데이터 번역 시스템 개발

3D 프린팅 기반 부품 유지보수 지원을 위한 제작 조건 검색 시스템 개발

허용 가능한 LOD의 상하한을 고려한 특징형상 3D CAD 조립체 모델의 단순화

DEXPI를 지원하는 지능형 공정 배관 계장도 가시화 시스템

플랜트 기자재 라이브러리 구축을 위한 3차원 파라메트릭 형상모델러

딥러닝과 이미지 프로세싱 기법을 활용한 이미지 형식 P&ID 내 객체 인식

플랜트 3D CAD 시스템과 중립 모델간의 배관 부품 스펙-카탈로그 데이터 번역 시스템 개발

하둡 및 스파크 기반 빅데이터 플랫폼을 이용한 선박 운항 효율 이상 상태 분석

ISO 15926 표준 기반 기자재 사양 시트 데이터 교환을 위한 후처리기의 개발

ISO 15926 기반 공정 플랜트 생애주기 데이터 가시화 플랫폼의 개발

ISO 15926 표준 기반 기자재 사양 시트 데이터 교환을 위한 전처리기의 개발

오픈소스 기반 빅데이터 플랫폼을 활용한 선박 운항 효율 예측 연구

플랜트의 3 차원 설계를 지원하는 중립 모델 기반 카탈로그 생성 시스템 개발

STL 형식의 3D 메쉬 모델을 OBJ 형식으로 변환하는 시스템 개발

형상 유사도 기반 피팅 검색을 위한 AutoCAD Plant 3D 플러그인 타입 시스템 개발

중립 모델과 플랜트 3D CAD 시스템간의 기자재 카탈로그 데이터 번역 시스템 개발

오픈소스 기반 빅데이터 플랫폼의 에너지 하베스터 최적설계 적용 연구

CAD 모델의 특징형상기반 단순화를 지원하는 확장형 시스템 개발

3D CAD 조립체 모델의 단순화를 위한 UG NX 기반 플러그인 타입 시스템 개발

3D 프린팅 기술을 활용한 부품 유지보수를 위한 분류체계 데이터 구조의 개발

ISO 15926 기반 공정 플랜트 설계, 제작, 및 시공 데이터 변환기의 개발

UG NX 기반 3D CAD 조립체 모델의 단순화 API 의 개발

기자재 라이브러리 구축을 위한 3D 형상, 사양, 및 포트 정합 시스템의 개발

iRINGTools를 활용한 ISO 15926 기반 기자재 참조 데이터 서버의 구축과 활용

시어핀스키 및 파스칼 프랙탈의 뼈 스캐폴드 설계에의 응용

Aveva Marine과 SmartMarine 3D 간의 해양 플랜트 3D 배관 CAD 모델 유사도 평가 시스템 개발

Aveva Marine과 SmartMarine 3D간의 해양 플랜트 3D 배관 CAD 모델의 배치모드 기반 비교 시스템 개발

운전자와 현장 조업자의 협동훈련을 위한 플랜트 훈련시스템 플랫폼 연구

ISO 15926 기반 공정 플랜트 3D 설계 정보 통합 플랫폼의 개발

부품 형상 정보 모델 기반의 자전거 편집설계 방법

ISO 15926 기반 플랜트 3D 설계 데이터 가시화를 위한 시스템 개발

KS 표준을 활용한 압력용기 설계 검증 시스템 프레임워크

대형 기계 설비의 사고 대응을 위한 훈련 시뮬레이터 프레임워크

ISO 15926 기반의 참조 데이터 라이브러리 편집기의 개발

특징형상 기반 기자재 3D CAD 조립체 데이터 간략화 시스템 개발

설계 문서 분석 장치 및 방법

3D 모델 단순화 장치 및 방법

객체 인식 시스템, 객체 인식 방법 및 객체 인식 방법을 실행시키도록 기록매체에 저장된 컴퓨터 프로그램

카탈로그 이미지의 데이터 추출 시스템 및 카탈로그 이미지의 데이터 추출 방법

기계가공 특징형상 인식 방법 및 이를 수행하기 위한 컴퓨팅 장치

파손 볼륨 계산 장치 및 방법

디지털 트윈 가상화 모델 구축을 위한 중립 모델 추출 시스템

형상 유사도 기반 이미지 도면 내 선 객체 인식 시스템 및 그 방법

기계가공 특징형상 인식 기반의 부품 제조성 검증 시스템 및 방법

딥러닝 기반 이미지 도면 내 선 객체 인식 시스템 및 그 방법

딥러닝 기반 학습 데이터 생성 방법 및 학습 데이터 생성 시스템

이미지 도면 내 객체 인식 장치

파손 부위의 전처리를 고려한 3D 프린팅 기반 부품의 부분 파손 유지보수 방법

도면 상에서 외곽선 및 표제 제거 방법을 포함하는 딥러닝 기반 학습 데이터 생성 방법 및 학습 데이터 생성 시스템

VR 모델 변환 시스템 및 이를 이용한 VR 모델 변환 방법

학습 데이터 생성 방법 및 학습 데이터 생성 시스템

3D 프린터를 활용한 부분 파손 부품의 유지보수를 지원하기 위한 메쉬 오프셋 기반의 델타 볼륨 생성 장치 및 방법, 그리고 3D 프린팅 기반 부품 유지보수 시스템

디지털 도면 제공 방법 및 디지털 도면 제공 시스템

부품의 부분 파손을 유지보수하기 위한 부품 검색 및 수리 장치와 방법, 그리고 3D 프린팅 기반 부품 유지보수 시스템

3차원 스캐닝을 통헤 획득된 점군 데이터 기반에서 깊이 이미지를 생성하는 장치 및 방법 및 이를 이용한 3 차원 객체 식별 방법

기자재 카탈로그 데이터 변환 시스템

3차원 스캐닝을 통해 획득된 점군 데이터를 기반으로 피팅을 모델링하기 위한 3 차원 모델링 장치 및 방법

3D 프린팅을 이용한 유지보수를 지원하는 부품 검색 및 검사 장치와 방법, 그리고 3D 프린팅 기반 부품 유지보수 시스템

3D 프린팅 기반 유지보수 지원을 위한 부품 데이터베이스 관리 장치 및 방법, 그리고 3D 프린팅 기반 부품 유지보수 시스템

경계 표현 기반 3차원 모델 단순화 장치 및 방법

질의 모델과 검색 대상 모델 간의 정밀도 차이를 고려한 모델 검색 장치 및 방법

최적 정밀도 결정을 통한 모델 단순화 장치 및 방법

기자재, 대형 기기 및 스키드 조립체를 지원하는 부품 카탈로그 정보 관리 장치 및 방법

형상 복잡도를 이용한 모델 간략화 장치 및 방법

기자재 정보 공유 시스템 및 방법

조립체 모델 비교 장치 및 방법

점군 데이터로부터 3차원 시설 배치 데이터를 생성하는 장치 및 방법

모델의 연결성을 보존하는 모델 간략화 장치 및 방법

상태 기반 3D 렌더링을 이용한 기기 모니터링 장치, 방법 및 시스템

조립체 모델링 데이터 간략화 장치 및 방법

조선해양 기자재의 3D CAD 단품 데이터의 간략화 방법

선박 내 호출 시스템

파라메트릭 정보를 갖는 3차원 CAD 모델의 모델링 데이터를 디지털 카탈로그의 형태로서 제공하기 위한 부품정보 시스템

Exchange of CAD part models based on the macro-parametric approach

A set of standard modeling commands for the history-based parametric approach

Feature-based simplification of boundary representation models using sequential iterative volume decomposition

Identification of topological entities and naming mapping for parametric CAD model exchanges

Simplification of feature-based 3D CAD assembly data of ship and offshore equipment using quantitative evaluation metrics

Deep-learning-based recognition of symbols and texts at an industrially applicable level from images of high-density piping and instrumentation diagrams

Stepwise volume decomposition for the modification of B-rep models

Integration of distributed plant lifecycle data using ISO 15926 and Web services

Representation and propagation of engineering change information in collaborative product development using a neutral reference model

Sharing product data of nuclear power plants across their lifecycles by utilizing a neutral model

Deep learning-based method to recognize line objects and flow arrows from image-format piping and instrumentation diagrams for digitization

Method to simplify ship outfitting and offshore plant equipment three-dimensional (3-D) computer-aided design (CAD) data for construction of an equipment catalog

A procedural method to exchange editable 3D data from a free-hand 2D sketch modeling system into 3D mechanical CAD systems

Knowledge-based part similarity measurement utilizing ontology and multi-criteria decision making technique

Toward standardized exchange of plant 3D CAD models using ISO 15926

Soonhung Han

Duhwan Mun

It is not possible to exchange parametric information of CAD models based on the current version of STEP. The design intent can be lost during the STEP transfer of CAD models. The Parametrics Group of ISO/TC184/SC4 has proposed the SMCH schema, which includes constructs for exchange of parametric information. This paper proposes a macro-parametric approach that is intended to provide capabilities to transfer parametric information including design intents. In this approach, CAD models are exchanged in the form of macro files. The macro file contains the history of user commands, which are used in the modeling phase. To exchange CAD models using the macro-parametric approach, the modeling commands of several commercial CAD systems are analyzed. Those commands are classified and a set of standard modeling commands has been defined. Mapping relations between the standard modeling commands and the native modeling commands of commercial CAD systems are defined. The scope of the current version is limited to parts modeling, not assemblies.

The current version of STEP standard cannot exchange the parametric information of CAD models. Only pure boundary representations that cannot be parametrically edited are transferable [Geometric Modeling: Theory and Practice (1997)]. There are two approaches for the exchange of design intents such as parameters, features, and constraints. The first is an explicit approach based on constraints between pre-defined parameters and features. The second is a procedural approach based on the sequence of operations issued to construct the models. The authors have previously proposed a macro-parametric approach [International Journal of CAD/CAM 2 (2002) 23], which is a variation of the procedural approach. In this approach, CAD models can be exchanged in the form of macro files, which include the history of modeling commands. To exchange CAD models using the macro-parametric approach, a set of …

A piping and instrumentation diagram (P&ID) is a key drawing widely used in the energy industry. In a digital P&ID, all included objects are classified and made amenable to computerized data management. However, despite being widespread, a large number of P&IDs in the image format still in use throughout the process (plant design, procurement, construction, and commissioning) are hampered by difficulties associated with contractual relationships and software systems. In this study, we propose a method that uses deep learning techniques to recognize and extract important information from the objects in the image-format P&IDs. We define the training data structure required for developing a deep learning model for the P&ID recognition. The proposed method consists of preprocessing and recognition stages. In the preprocessing stage, diagram alignment, outer border removal, and title box removal are performed. In the recognition stage, symbols, characters, lines, and tables are detected. The objects for recognition are symbols, characters, lines, and tables in P&ID drawings. A new deep learning model for symbol detection is defined using AlexNet. We also employ the connectionist text proposal network (CTPN) for character detection, and traditional image processing techniques for P&ID line and table detection. In the experiments where two test P&IDs were recognized according to the proposed method, recognition accuracies for symbol, characters, and lines were found to be 91.6%, 83.1%, and 90.6% on average, respectively.

When computer-aided design (CAD) models generated in the design phase are used for engineering activities such as engineering analysis, distributed collaborative design, and virtual prototyping, a process for simplifying the CAD models is needed. In this study, a feature-based simplification method of boundary representation (B-rep) models using sequential iterative volume decomposition is proposed. This method generates a feature-based model from a B-rep model by sequentially and iteratively applying the four volume decomposition methods (fillet, round, and chamfer decomposition; wrap-around decomposition; volume split decomposition; and cell-based decomposition). Then, feature-based simplification is applied to the generated feature-based model. To demonstrate the proposed method, a prototype system is implemented, and experiments with test cases are performed. Based on the experimental …

As collaborative design and configuration design gain increasing importance in product development, it becomes essential to exchange parametric CAD models among participants. Parametric CAD models can be represented and exchanged in the form of a macro file or a part file that contains the modeling history of a product. The modeling history of a parametric CAD model contains feature specifications and each feature has selection information that records the name of the referenced topological entities. Translating this selection information requires solving the problems of how to identify the referenced topological entities of a feature (persistent naming problem) and how to convert the selection information into the format of the receiving CAD system (naming mapping problem). The present paper introduces the problem of exchanging parametric CAD models and proposes a solution to naming mapping.

In the design process for ship outfitting and offshore plants, an equipment catalog database is compiled in order for shipyards to reutilize data effectively. However, the current procedure for building such a catalog causes wastage of time because the modelers in the shipyard must perform manual modeling of the 3D CAD data in order to decrease the size of 3D CAD data and adopt a different level of detail (LOD) depending on the purpose of its use. This problem arises because equipment suppliers are not willing to give all of their 3D CAD data to shipyards, out of fear of the loss of intellectual property. Moreover, the 3D CAD data of equipment suppliers have a high LOD, while a shipyard’s 3D CAD data have a relatively low LOD. Therefore, it is necessary to introduce an automated method to simplify the 3D CAD assembly data for equipment that is received from the equipment supplier. In addressing this problem …

Piping and instrumentation diagrams (P&IDs) are commonly used in the process industry as a transfer medium for the fundamental design of a plant and for detailed design, purchasing, procurement, construction, and commissioning decisions. The present study proposes a method for symbol and text recognition for P&ID images using deep-learning technology. Our proposed method consists of P&ID image pre-processing, symbol and text recognition, and the storage of the recognition results. We consider the recognition of symbols of different sizes and shape complexities in high-density P&ID images in a manner that is applicable to the process industry. We also standardize the training dataset structure and symbol taxonomy to optimize the developed deep neural network. A training dataset is created based on diagrams provided by a local Korean company. After training the model with this dataset, a recognition …

Recently, studies applying deep learning technology to recognize the machining feature of three-dimensional (3D) computer-aided design (CAD) models are increasing. Since the direct utilization of boundary representation (B-rep) models as input data for neural networks in terms of data structure is difficult, B-rep models are generally converted into a voxel, mesh, or point cloud model and used as inputs for neural networks for the application of 3D models to deep learning. However, the model’s resolution decreases during the format conversion of 3D models, causing the loss of some features or difficulties in identifying areas of the converted model corresponding to a specific face of the B-rep model. To solve these problems, this study proposes a method enabling tight integration of a 3D CAD system with a deep neural network using feature descriptors as inputs to neural networks for recognizing machining …

This study proposes an end-to-end digitization method for converting piping and instrumentation diagrams (P&IDs) in the image format to digital P&IDs. Automating this process is an important concern in the process plant industry because presently image P&IDs are manually converted into digital P&IDs. The proposed method comprises object recognition within the P&ID images, topology reconstruction of recognized objects, and digital P&ID generation. A data set comprising 75 031 symbol, 10 073 text, and 90 054 line data was constructed to train the deep neural networks used for recognizing symbols, text, and lines. Topology reconstruction and digital P&ID generation were developed based on traditional rule-based approaches. Five test P&IDs were digitalized in the experiments. The experimental results for recognizing symbols, text, and lines showed good precision and recall performance, with …

In process plants, 3D computer-aided design (CAD) plant models are frequently generated via reverse engineering using point cloud data. Generating a 3D model from scan data consists of point cloud collection, preprocessing, and modeling. The process of 3D modeling to create a plant 3D CAD model from a registered point cloud consists of grouping similar point clouds into several segmented point clouds, identifying the components represented by each segment, selecting catalogs for the components, and placing them into 3D design space. The core of a 3D modeling process is to identify components represented by the segmented point clouds. This study proposes a deep learning-based method to retrieve catalogs for piping components to support the reconstruction of a plant 3D CAD model from point clouds. A prototype catalog retrieval system is implemented based on the proposed method, and the …

During product design, the modification of computer-aided design (CAD) models is frequently required. However, modifying a boundary representation (B-rep) model, which is a typical type of CAD model, is difficult and time consuming. To address this problem, we propose a method for modifying B-rep models. In the proposed method, a B-rep model is decomposed into simple volumes by stepwise volume decomposition. A pseudo feature tree called the composition tree is generated with the decomposed simple volumes. A user can modify the B-rep model by transforming or deleting constituents of the composition tree and then replaying the updated composition tree. To demonstrate the proposed method, a prototype system was implemented, and experiments with test cases are performed. Based on the experimental results, we verified that B-rep models could be easily modified using the proposed method.

Three-dimensional (3D) computer-aided design (CAD) model reconstruction techniques are used for numerous purposes across various industries, including free-viewpoint video reconstruction, robotic mapping, tomographic reconstruction, 3D object recognition, and reverse engineering. With the development of deep learning techniques, researchers are investigating the reconstruction of 3D CAD models using learning-based methods. Therefore, we proposed a method to effectively reconstruct 3D CAD models containing machining features into 3D voxels through a 3D encoder–decoder network. 3D CAD model datasets were built to train the 3D CAD model reconstruction network. For this purpose, large-scale 3D CAD models containing machining features were generated through parametric modeling and then converted into a 3D voxel format to build the training datasets. The encoder–decoder network …

Considering the financial, safety, and environmental risks related to industrial installations, it is of paramount importance that all relevant lifecycle information is readily available. Parts of this lifecycle information are stored in a plethora of computer systems, often scattered around the world and in many native formats and languages. These parts can create a complete, holistic set of lifecycle data only when they are integrated together. At present, no software is available that can integrate these parts into one coherent, distributed, and up-to-date set. The ISO 15926 standard has been developed, and in part is still under development, to overcome this problem. In this paper, the authors discuss a prototype of an ISO 15926-based data repository called a façade, and its Web services are implemented for storing the equipment data of a nuclear power plant and servicing the data to interested organizations. This prototype …

As modular production becomes increasingly widespread in globalized manufacturing industries, many components constituting a final product are being developed and produced by collaborating part suppliers who have the ability to design their own parts by themselves without aid from the original equipment manufacturer (OEM). In this collaborative product development, the important aspect to expedite engineering changes is that engineering change information should be represented precisely in a designer-friendly form and shared among participating companies in an effective manner. However, all part suppliers and an OEM typically do not use the same computer-aided design (CAD) system and they are reluctant to share their CAD data with other cooperating companies owing to the policy of protecting corporate intellectual property. These circumstances make it difficult for collaborating companies to …

Many public and private Korean organizations are involved during the lifecycle of a domestic nuclear power plant. Korea Plant Engineering Co. (KOPEC) participates in the design stage, Korea Hydraulic and Nuclear Power (KHNP) operates and manages all nuclear power plants in Korea, Doosan Heavy Industry and Construction Co. manufactures the main equipment, and a construction company constructs the plant. Even though each organization has its own digital data management system and obtains a certain level of automation, data sharing among organizations is poor. KHNP obtains drawings and technical specifications from KOPEC in the form of paper. This results in manual re-work of definitions, and errors can potentially occur in the process. In order to establish an information bridge between design and operation and maintenance (O&M) phases, a generic product model (GPM), a data model from …

As part of research on technology for automatic conversion of image-format piping and instrumentation diagram (P&ID) into digital P&ID, the present study proposes a method for recognizing various types of lines and flow arrows in image-format P&ID. The proposed method consists of three steps. In the first step of preprocessing, the outer border and title box in the diagram are removed. In the second step of detection, continuous lines are detected, and then line signs and flow arrows indicating the flow direction are detected. In the third step of post-processing, using the results of line sign detection, continuous lines that require changing of the line type are determined, and the line types are adjusted accordingly. Then, the recognized lines are merged with flow arrows. For verification of the proposed method, a prototype system was used to conduct an experiment of line recognition. For the nine test P&IDs, the average precision and recall were 96.14% and 89.59%, respectively, showing high recognition performance.

The construction of an equipment catalog is necessary in ship outfitting and offshore plant design. We investigated the present status of equipment catalogs in shipyards and revealed several requirements for the catalogs, which are manually created and time-consuming. We defined the requirements by analyzing the construction procedure of the equipment catalog and conducted interviews with shipyard employees. In addition, problems with conventional equipment catalog construction are described, and a new procedure for the construction of an equipment catalog is introduced. By analyzing shipyard requirements, criteria for simplification (including volume, ports, and the outer boundary) are defined. Further analysis of technological factors for simplification is performed, and the results of implementing the simplification system are described. The proposed system is verified using three test cases used on site.

In the concept development phase, a designer wants to rapidly create a product’s overall shape and user interfaces by making simple sketches, known as ‘thumbnail sketches’, to evaluate ideas and possibilities. Free-hand 2D sketch systems are regarded as a computerized tool for making thumbnail sketches. After the concept development phase, subsequent editing of the 3D data reconstructed from a free-hand 2D sketch with a 3D mechanical CAD system in the detail design phase is indispensable because inaccurate dimensions are inherent in a free-hand 2D sketch. For this reason, we present a new method to translate 3D data reconstructed from a free-hand 2D sketch into an editable form that reflects design intent so that the translated data can be directly used in 3D mechanical CAD systems. The feasibility of the proposed method has been demonstrated through experiments with prototype systems.

When existing parts are re-used for the development of a new product or business-to-business transactions, a method for searching parts from a database that best meet user’s requirements is essential. The core of a part search method is to measure the similarity between parts’ specifications and the user’s input data in an efficient manner. In this paper, the authors suggest a new method for part similarity measurement using ontology and multi-criteria decision making (MCDM) technique and discuss its technical details. This method ensures interoperability with existing engineering information management systems, represents part specifications in a formal manner, and has generality in search procedure. A case study with ejector pins has also been conducted for the demonstration of the proposed method.

Plant three-dimensional (3D) computer-aided design (CAD) models typically consist of logical configuration, equipment specifications and ports, and 3D shapes. Because 3D CAD models are used as master information throughout a plant’s entire lifecycle and many stakeholders are involved in such lifecycle, providing a method for sharing plant 3D CAD models among various stakeholders is very important. Standard 15926 from the International Organization for Standardization (ISO 15926) is a family of standards that is intended to support the sharing and integrating of all information during the life of a process plant. Therefore it is important for ISO 15926 to support plant 3D CAD models. In order to address this issue, this study investigates a standardized method to exchange plant 3D CAD models using ISO 15926. Information requirements regarding plant 3D CAD models are established, and then ISO 15926 …

EIF Lab at ME, KU

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Point Cloud Registration Using PCA and Hyperparameter Optimization

Enhancing Chromium Coating Thickness Estimation with Multi-head Attention LSTM and Data Augmentation

Hybrid Approach for Comprehensive Recognition of Line Objects Contained in High-Density Piping and Instrumentation Diagrams Using Deep Learning and Rules

연구실 보유 특허

대학별 입시끈

우리 연구실 모집

교수님 소개

문두환

연구실 키워드

알럼나이가 간 회사

연구실 지원 방법

대우 조건

연도별 논문 인용수

저널 & 학회 논문 출판 수

연구실 논문 목록

Point Cloud Registration Using PCA and Hyperparameter Optimization

Enhancing Chromium Coating Thickness Estimation with Multi-head Attention LSTM and Data Augmentation

Hybrid Approach for Comprehensive Recognition of Line Objects Contained in High-Density Piping and Instrumentation Diagrams Using Deep Learning and Rules

연구실 보유 특허

최근 3년간 연구실적 높은 연구실

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