• Title/Summary/Keyword: Manufacturing Industries

Search Result 1,812, Processing Time 0.024 seconds

Development of Environmental Responsibility Index for the Manufacturing Industry by Emergy Analysis (Emergy 분석법에 의한 제조업의 환경친화성지수 개발)

  • Je, Yun Mi;Lee, Seong Mo
    • Journal of Environmental Science International
    • /
    • v.13 no.4
    • /
    • pp.349-357
    • /
    • 2004
  • Emergy is a measure of the processes required to produce something expressed in units of the same energy form. Emergy based indices can provide insights into the thermodynamic efficiency of the process, the quality of its output, and the interaction between the process and its surrounding environment. However, in an industrial system, the inputs are mostly nonrenewable, renewable energy source is nearly zero, ultimate purpose is pursuit of profits in economic activity. In study, we present two indices based on emergy - EEE(Ecological Economic Efficiency) and ERI(Environmental Responsibility Index). The EEE is taken into account real value of product in market economy. The ERI is shown to be a function of the net yield of the economy, its ‘load’ on the environment and ecological economic efficiency. Manufacturing industry of Korea produced the 30% of total GDP in 2001. We applied these indices to manufacturing industry for environmental management and further sustainable industry. As a results, the highest ERI is 0.34 in recycling industries, the lowest ERI is 0.01 in coke, refined petroleum products which is dominated by ELR. The higher ERI, the more friendly to environment. The suggested indices help us understand relative contributions of various alternatives in company's production and consumption activity, and provide a tool of decision-making for the rearrangement of future industries. Furthermore, they contribute to environmental friendly operation and consumption.

Development of a System for Selecting High-Quality Mold Manufacturing NC Data Using Evaluating the NC Data (NC 데이터 정량화를 통한 고품질 사출금형 NC 가공데이터 선정 방안)

  • Heo Eun-Young;Kim Bo-Hyun;Kim Dong-Won
    • Journal of the Korean Society for Precision Engineering
    • /
    • v.23 no.4 s.181
    • /
    • pp.99-108
    • /
    • 2006
  • Since mold industries are regarded as belonging to three types of bad business, capable young people are reluctant to work in this field. The industries are hard to employ skilled workers who have much experience and knowledge On the mold manufacturing. Thus, effective CAM systems are required for unskilled workers to create process plans and NC data for the manufacturing, and process plans play important roles in the downstream manufacturing processes, such as NC machining, polishing, and final assembly. This study proposes a decision support system that facilitates unskilled workers to easily select high quality NC-data, as well as to increase productivity. The proposed system is assumed to follow a CAM operation scenario that consists of next three steps: 1) identifying several process plans and enumerating feasible unit machining operations (UMOs) from material and part surface information, 2) creating all feasible NC-data based on UMOs using a commercial CAM system, 3) selecting the best NC data among the feasible NC data using four screening criteria, such as machining accuracy, machining allowance, cutting load, and processing time. A case study on the machining of a camera core mold is provided to demonstrate the proposed system.

An Analysis on the Forecasting Demand and Supply of Regional Industrial Labor for Customized Nurturing Human Resource: Focused on Manufacturing Industry in Chung-Nam Province (맞춤형 인력양성을 위한 지역 산업인력 수급분석: 충남지역 제조업을 중심으로)

  • Jung, Hae Yong
    • Journal of Korea Society of Digital Industry and Information Management
    • /
    • v.7 no.2
    • /
    • pp.147-159
    • /
    • 2011
  • In this paper the demand and supply of labor are forecasted over the next 10 years for customized nurturing human resource focused on Manufacturing Industry in Chung-Nam Province. Despite that the industrial structure is rapidly changing, industrial labors are nurturing on the basis of past industrial structure. This research is conducted for reducing mismatched labors throughout forecasting human resources until 2020. As a practical approach, the BLS Methodology is partially utilized. And the previous researches and official statistics data are reviewed. In conclusion, this study presents that more human resources on Manufacturing Industry than other Industries will be needed in Chung-Nam province. In details, it shows that there will be required more Industrial labors for strategic industries for examples, Audio and Video related industry, and Car related industry which is propelling by overall local government. In additions, policy implications are developed by analyzing current status and forecasting the labor demand and supply in the Chung-Nam Manufacturing sector.

Dynamic Yield Improvement Model Using Neural Networks (신경망을 이용한 동적 수율 개선 모형)

  • Jung, Hyun-Chul;Kang, Chang-Wook;Kang, Hae-Woon
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.32 no.2
    • /
    • pp.132-139
    • /
    • 2009
  • Yield is a very important measure that can expresses simply for productivity and performance of company. So, yield is used widely in many industries nowadays. With the development of the information technology and online based real-time process monitoring technology, many industries operate the production lines that are developed into automation system. In these production lines, the product structures are very complexity and variety. So, there are many multi-variate processes that need to be monitored with many quality characteristics and associated process variables at the same time. These situations have made it possible to obtain super-large manufacturing process data sets. However, there are many difficulties with finding the cause of process variation or useful information in the high capacity database. In order to solve this problem, neural networks technique is a favorite technique that predicts the yield of process for process control. This paper uses a neural networks technique for improvement and maintenance of yield in manufacturing process. The purpose of this paper is to model the prediction of a sub process that has much effect to improve yields in total manufacturing process and the prediction of adjustment values of this sub process. These informations feedback into the process and the process is adjusted. Also, we show that the proposed model is useful to the manufacturing process through the case study.

Shape Optimization for Lightweight of the Line Center for Processing Complex Shape Parts (복합형상 부품 가공용 라인센터의 경량화를 위한 형상 최적화에 관한 연구)

  • Park, Do-Hyun;Jeong, Ho-In;Kim, Sang-Won;Lee, Choon-Man
    • Journal of the Korean Society of Manufacturing Process Engineers
    • /
    • v.20 no.8
    • /
    • pp.86-92
    • /
    • 2021
  • As interest and demand for high value-added industries, including the global automobile and aerospace industries, have increased recently, demand for line centers with excellent performance that can respond to the production system for producing high value-added products is also rapidly increasing. A line center improves productivity based on the installed area using a multi-spindle compared to a conventional machining center. However, as the number of spindles increases, the weight increases and results in structural problems owing to the heat and vibration generated by each spindle. Therefore, it is necessary to improve machining precision through the structural improvement of the line center. This study presents research on the stabilization design of the line center through structural stability analysis through structural analysis to develop a compact multi-axis line center. An optimization model of the line center has been proposed to improve the processing precision and increase the rigidity by performing weight reduction based on the structural analysis results.

Leverage and Bankruptcy Risk - Evidence from Maturity Structure of Debt: An Empirical Study from Vietnam

  • NGUYEN, Thi Thanh;KIEN, Vu Duc
    • The Journal of Asian Finance, Economics and Business
    • /
    • v.9 no.1
    • /
    • pp.133-142
    • /
    • 2022
  • This study examines the relationship between debt maturity structure and bankruptcy risk. There are various studies of leverage's effect on bankruptcy risk. Debt maturity, however, has not received the attention it deserves, especially in emerging markets with a high degree of information asymmetry. Using Vietnamese listed company data and various estimations, we find that leverage is positively associated with the likelihood of default. Importantly, short-term leverage shows a significantly positive effect on bankruptcy risk, while long-term leverage does not show significant results. The findings highlight that rollover risk firms are exposed to when using short-term debt increases bankruptcy risk. Meanwhile, firms do not cope with this risk in case of long-term debt adoption. High information asymmetry in emerging markets may be the main reason for the difference. The result is robust for subsamples of firms in different financial conditions, in concentrated and competitive industries, as well as for manufacturing and non-manufacturing companies. We also find that firms in a better financial situation and concentrated industries experience a higher short-term leverage effect than their counterparts. We, however, do not find a significant difference in the impact between manufacturing and non-manufacturing companies. This paper is among the first to examine the relation between debt maturity and bankruptcy risk in Vietnam.

Development of a injection molding automation system of busbar insert for the electric vehicle (전기 자동차 부스바 인서트 사출 자동화 시스템 개발)

  • Jong-Su Kim
    • Design & Manufacturing
    • /
    • v.18 no.2
    • /
    • pp.35-40
    • /
    • 2024
  • Injection molding is a process widely used across various industries for molding plastics, and it is the most commonly applied process in root industries utilizing molds. Among the different types of injection molding, insert injection molding, where busbars are used as inserts, is increasingly being applied in the electric vehicle industry. However, currently, the insert injection molding process is manually performed, with workers placing insert components by hand before injection molding. This results in issues related to productivity, safety, and quality. Additionally, there is a growing demand for automation of such production lines due to hazardous working conditions, economic difficulties in the manufacturing industry, and the decline in the labor force caused by an aging population. This study focuses on the application of an automated system for the insert injection molding process used in electric vehicles. The development of an automated system for the transport and insertion of insert components, as well as the inspection and stacking processes after injection, has resulted in over a 25% improvement in productivity and more than a 27% reduction in defect rates.