دانلود مقاله ISI انگلیسی شماره 43798
ترجمه فارسی عنوان مقاله

اطلاعات صنعتی - یک رویکرد مبتنی بر هوش کسب و کار به منظور افزایش مهندسی ساخت و تولید در شرکت های صنعتی

عنوان انگلیسی
Industrial Intelligence - A Business Intelligence-based Approach to Enhance Manufacturing Engineering in Industrial Companies ☆
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
43798 2013 6 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Procedia CIRP, Volume 12, 2013, Pages 384–389

ترجمه کلمات کلیدی
اطلاعات کسب و کار - مدیریت مرحله بلوغ - تقاضای اطلاعات - ویژگی های فن آوری -
کلمات کلیدی انگلیسی
Business Intelligence; Maturity Stage Management; Information Demand; Feature Technology.
پیش نمایش مقاله
پیش نمایش مقاله  اطلاعات صنعتی - یک رویکرد مبتنی بر هوش کسب و کار به منظور افزایش مهندسی ساخت و تولید در شرکت های صنعتی

چکیده انگلیسی

Flexibility, resource efficiency, and time-to-market are key success factors for industrial enterprises. Essential settings are set during early phases of product development as well as manufacturing. In later product lifecycle phases, the responses from the market (e.g. complains or the amount of damage cases) show the maturity stage of the products. Quality methods like TQM or EFQM pursue the goal to permanently learn from this information. Therefore it is necessary to have an adequate information supply. This article focuses on this problem in the context of maturity stage management in manufacturing engineering. The research therefore first identifies a huge gap between the theoretically discussed information supply, based on encompassing data bases, and the real existing heterogeneous IT landscapes, which have grown in history. On basis of empirical findings, industrial businesses lack in concepts that put them in a position of adequate information supply. Therefore, a generic Business Intelligence concept, developed through research activities, seems to be a promising approach. It is thus possible to combine information from product features and manufacturing information with the traditional dimensions of managerial analysis, in order to identify impacts of engineering decisions on the product lifecycle.