کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
710140 892102 2016 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Towards quantified measures of Agility for Production Line Information Systems (PLIS)
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مکانیک محاسباتی
پیش نمایش صفحه اول مقاله
Towards quantified measures of Agility for Production Line Information Systems (PLIS)
چکیده انگلیسی

The agility in enterprise information (EIS) and business intelligence (BI) systems is summarized as content and structural agility due to changing business requirements. We argue that production lines are key enablers in organizational agility and any hostile and drifting behaviour could turn potential opportunities into losses besides the fact that an agile EIS is well integrated. There are many ISs developed to control and monitor the drifting behaviour of production lines like fault detection and classification (FDC), statistical process control (SPC) and automation systems. These offer excellent detection mechanisms against known drifts; however, real challenge lies in carrying out root-cause analysis for unknown drifts. Therefore, in this paper we propose a new category of IS for production lines as agile PLIS, capable to control, detect, assess and predict the potential drifts for proactive measures. The definition of an agile IS for production line is proposed with quality attributes selected from literature, ISO 91261 software quality standard and specificities of the production line. Further, generic measures of production line agility as local (LAI) and global (GAI) agility indices are proposed to measure the agility drifts for a production line. The agility in an IS is built and not designed; therefore, we also present a compliance matrix of most widely used information system architectures (ISA) against proposed agile PLIS with quality attributes. This paper concludes by validating the proposed quantified measures of agility for agile PLIS using data from reputed semiconductor manufacturer.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: IFAC-PapersOnLine - Volume 49, Issue 12, 2016, Pages 562–567
نویسندگان
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