• Design & Manufacturing
• /
• 제15권1호
• /
• pp.48-56
• /
• 2021

The quality of products produced by injection molding process is greatly influenced by the process variables set on the injection molding machine during manufacturing. It is very difficult to predict the quality of injection molded product considering the stochastic nature of manufacturing process, because the process variables complexly affect the quality of the injection molded product. In the present study we predicted the quality of injection molded product using Artificial Neural Network (ANN) method specifically from Multiple Input Single Output (MISO) and Multiple Input Multiple Output (MIMO) perspectives. In order to train the ANN model a systematic plan was prepared based on a combination of orthogonal sampling and random sampling methods to represent various and robust patterns with small number of experiments. According to the plan the injection molding experiments were conducted to generate data that was separated into training, validation and test data groups to optimize the parameters of the ANN model and evaluate predicting performance of 4 structures (MISO1-2, MIMO1-2). Based on the predicting performance test, it was confirmed that as the number of output variables were decreased, the predicting performance was improved. The results indicated that it is effective to use single output model when we need to predict the quality of injection molded product with high accuracy.

• Design & Manufacturing
• /
• 제15권4호
• /
• pp.24-31
• /
• 2021

In this study, an artificial neural network model was constructed to convert CAE analysis data into similar experimental data. In the analysis and experiment, the injection molding data for 50 conditions were acquired through the design of experiment and random selection method. The injection molding conditions and the weight, height, and diameter of the product derived from CAE results were used as the input parameters for learning of the convert model. Also the product qualities of experimental results were used as the output parameters for learning of the convert model. The accuracy of the convert model showed RMSE values of 0.06g, 0.03mm, and 0.03mm in weight, height, and diameter, respectively. As the next step, additional randomly selected conditions were created and CAE analysis was performed. Then, the additional CAE analysis data were converted to similar experimental data through the conversion model. An artificial neural network model was constructed to predict the quality of injection molded product by using converted similar experimental data and injection molding experiment data. The injection molding conditions were used as input parameters for learning of the predicted model and weight, height, and diameter of the product were used as output parameters for learning. As a result of evaluating the performance of the prediction model, the predicted weight, height, and diameter showed RMSE values of 0.11g, 0.03mm, and 0.05mm and in terms of quality criteria of the target product, all of them showed accurate results satisfying the criteria range.

• 산업경영시스템학회지
• /
• 제40권1호
• /
• pp.105-113
• /
• 2017

Network externality can be defined as the effect that one user of a good or service has on the value of that product to other people. When a network externality is present, the value of a product or service is dependent on the number of others using it. There exist asymmetries in network externalities between the online and traditional offline marketing channels. Technological capabilities such as interactivity and real-time communications enable the creation of virtual communities. These user communities generate significant direct as well as indirect network externalities by creating added value through user ratings, reviews and feedback, which contributes to eliminate consumers' concern for buying products without the experience of 'touch and feel'. The offline channel offers much less scope for such community building, and consequently, almost no possibility for the creation of network externality. In this study, we analyze the effect of network externality on the competition between online and conventional offline marketing channels using game theory. To do this, we first set up a two-period game model to represent the competition between online and offline marketing channels under network externalities. Numerical analysis of the Nash equilibrium solutions of the game showed that the pricing strategies of online and offline channels heavily depend not only on the strength of network externality but on the relative efficiency of online channel. When the relative efficiency of online channel is high, the online channel can greatly benefit by the network externality. On the other hand, if the relative efficiency of online channel is low, the online channel may not benefit at all by the network externality.

• 대한산업공학회지
• /
• 제29권2호
• /
• pp.157-164
• /
• 2003

The amount of information increases rapidly when working in a distributed environment where multiple collaborative partners work together on a complex product. Today's PDM (product data management) systems provide good capabilities regarding the management of product data within a single company. However, taking into account the variety of systems used at partner sites in an engineering environment one can easily imagine problems regarding the interoperability and the data consistency. This paper presents a concept to improve the workflow management using the parameters network. It shows a parameter driven engineering workflow that is able to manage engineering task across company boarders. We introduce a mechanism of workflow management based on the engineering parameters and an architecture of the distributed workspace to apply it within a PDM system. For a parameter mapping between CAD and PDM system we developed an XML-based CATIA data interface module using CAA.

• 대한안전경영과학회지
• /
• 제6권2호
• /
• pp.187-197
• /
• 2004

The recycling cell formation problem means that disposal products are classified into recycling product families using group technology in their end-of-life phase. Disposal products have the uncertainties of product condition usage influences. Recycling cells are formed considering design, process and usage attributes. In this paper, a new approach for the design of cellular recycling system is proposed, which deals with the recycling cell formation and assignment of identical products concurrently. Fuzzy ART neural networks are applied to describe the condition of disposal product with the membership functions and to make recycling cell formation. The approach leads to cluster materials, components, and subassemblies for reuse or recycling and can evaluate the value at each cell of disposal products. Disposal refrigerators are shown as an example.

• 산업기술연구
• /
• 제29권B호
• /
• pp.89-94
• /
• 2009

The dyeing sludge is the major waste generated in Banwol & Sihwa Industrial Complex. The Purpose of this study is to develop BAT (Best available technique) for the treatment and recycling of dyeing sludge. The dyeing sludge was carbonized and the product was tested physical properties and chemical chracterizations and also analyzed chemical compositions. From the test results we expect that the products can be used as adsorbent for the removal of order in the poultry farm and cattle shed. The feasibility of other methods such as manufature of RDF and cement etc. were also studied.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2006년도 춘계학술대회 논문집
• /
• pp.609-610
• /
• 2006

This paper introduces a methodology for construction of ontology-based product knowledge Map. For CPC(Collaborative Product Commerce) environment, engineering application of ontology has been studied . However, there are no generic and comprehensive methodologies for ontology construction yet because of such problems: dependency on experience of ontologist and domain experts and insufficiency of detail stages or rules. To solve those problems, we propose a methodology to construct ontology from engineering documents in semi-automatic. We use middle-out strategy and term's axioms, sub-definitions, to build ontology map. 5-turple ontology structure, semantic network and First order logic (FOL) are used for ontology definition in this study.

• International Journal of Computer Science & Network Security
• /
• 제22권1호
• /
• pp.319-323
• /
• 2022

The information research system continues to be developed and directed at leading research National Institute of Technology (ITN) Malang in accordance with the Research Strategic Plan of ITN Malang. One of them is a computer system in a complete integrated facility management activity, such as this research scheme. The purpose of this research is to combine and integrate people, places, product, processes and technology. All of them are integrate existing organizational factors into a more effective, simplifying of complex processes, identifying and scheduling, notes, decision makers and more. This research was conducted in stages by design with a structured model stage for 3 (three) years (focus on humans, products and processes), research on Integration Facility Management: Interface Coordination in human resources and product management have been completed on 2019 and 2020. While the focus of research this year is to obtain an integrated facility management Interface Coordination in Process Management.

• 무역학회지
• /
• 제46권3호
• /
• pp.227-245
• /
• 2021

This study aims to examine how entrepreneurs' international entrepreneurial orientation and digital orientation affect business networks, innovative product development, and internationalization performance in a digital environment. For this purpose, data were collected from the CEOs of 192 domestic start-up venture companies. The causal relationship between the variables was analyzed through confirmatory factor analysis and structural model analysis using AMOS(18.0 version) for the collected data. It was confirmed that international entrepreneurial orientation and digital orientation have a positive effect on business networks. And the business network was found to have a positive effect on innovative product development and internationalization performance

• 디지털융복합연구
• /
• 제15권4호
• /
• pp.181-190
• /
• 2017

최근 가습기살균제 사건을 비롯하여 휴대폰, 유아용 기저귀 등 생활용품의 안전사고가 빈번히 발생하고 있다. 이러한 사고로부터 소비자를 보호하기 위해서는 제품 안전관리가 필요하며, 제품의 안전성 정도를 평가할 수 있는 제품 리스크 평가 도구가 필요하다. 본 논문은 한국소비자원의 제품 사고관련 위해정보를 바탕으로 제품 리스크를 평가할 수 있는 시스템인 RAS(Risk Assessment System)를 구축하였다. RAS는 사고관련 정보를 분석하는 위해정보 분석시스템과 이 시스템으로부터 도출된 정보를 활용하여 리스크를 평가하는 리스크 평가시스템으로 구성되어 있다. 리스크 평가과정에서 제품 리스크에 영향을 미치는 인과관계를 반영한 베이지안 네트워크 기반의 확률적 기법을 적용하였다. RAS를 사용하여 어린이 제품 33품목에 대해 평가를 실시했으며 EU RAPEX의 RAG의 평가결과와 비교해 보았다. 그 결과 본 연구의 RAS의 결과는 전반적으로 EU RAPEX RAG의 평가 결과에 비해 낮은 수준을 보임을 알 수 있었다. 추후과제로는 사고영향척도 입력값의 주관성 저감, 위해정보 분석시스템과 리스크 평가시스템의 연동 등을 들 수 있다.