淡江大學機構典藏:Item 987654321/100195
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62830/95882 (66%)
Visitors : 4051822      Online Users : 991
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/100195


    Title: Optimal ordering policy for an economic order quantity model with inspection errors and inspection improvement investment
    Other Titles: 考慮檢查程序發生錯誤且得以投資資金改善檢查程序的經濟訂購量模型之最適訂購策略
    Authors: L. Y. Ouyang;C. H. Su;C. H. Ho;C. T. Yang
    Contributors: 管理科學學系暨研究所
    Keywords: 存貨;不良品;檢查錯誤;檢定力;投資資金;Inventory;Defective products;Inspection error;Power of the test;Capital investment
    Date: 2014-12-01
    Issue Date: 2015-02-05 12:28:11 (UTC+8)
    Abstract: The rise of consumer rights has caused businesses to focus increasingly on product
    quality. The inability of businesses to identify defective items before selling them
    results in higher return costs, decreased sales revenue, damaged reputations, and
    decreased competitiveness. This study examines the economic order quantity (EOQ)
    model in which the retailer discovers defective goods among received products.
    Although retailers conduct quality inspections, the inspection process is imperfect. We
    assume that Type I and Type II inspection errors occur during product quality
    inspection and that the market demand rate is sensitive to Type II inspection errors. To
    improve inspection, the retailer invests capital to decrease Type II inspection errors.
    This study investigates the optimal order quantity and the power of the test to
    maximize total profit per unit time. Mathematical analysis is used to show the optimal
    solution exists. An algorithm is then developed to calculate the optimal solution.
    Finally, numerical examples demonstrate the solution process and sensitivity analysis
    with respect to major parameters is carried out.
    Relation: International Journal of Information and Management Sciences 25(4), pp.317-330
    DOI: 10.6186%2fIJIMS.2014.25.4.3
    Appears in Collections:[Department of Management Sciences] Journal Article

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML10View/Open
    The Service Marketing Analysis by Using Six Sigma Management Approach.pdf2969KbAdobe PDF14View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback