Conference paper Open Access

Using Business Analytics for Decision Support in Zero Defect Manufacturing of Composite Parts in the Aerospace Industry

Helmut Zörrer; Robert Steringer; Sebastian Zambal; Christian Eitzinger


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    <subfield code="d">28-30 August, 2019</subfield>
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    <subfield code="a">9th IFAC Conference on Manufacturing Modeling, Management, and Control</subfield>
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    <subfield code="n">Modeling and Data Analytics for Zero Defect Manufacturing</subfield>
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    <subfield code="a">Robert Steringer</subfield>
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    <subfield code="a">Sebastian Zambal</subfield>
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    <subfield code="a">Using Business Analytics for Decision Support in Zero Defect Manufacturing of Composite Parts in the Aerospace Industry</subfield>
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    <subfield code="a">Zero-defect manufacturing of composite parts in the aerospace industry</subfield>
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    <subfield code="a">&lt;p&gt;&lt;strong&gt;Abstract:&lt;/strong&gt; In multi-staging manufacturing environments, more than necessary reworking at an early stage can prevent costly defects at later stages. One goal of the EU research project ZAero (Zero-defect manufacturing of composite parts in the aerospace industry) is to generate precious feature data by implementing an inline quality control for the manufacturing process of carbon fibre components of aircraft. However, for each feature detected by ZAero&amp;rsquo;s inline quality control, operators must decide whether or not to rework that feature. Additional reworking of non defects can reduce expensive defects in later stages, but the increased effort should not have a significant impact on production. To help operators make the right decisions, an extensible hybrid decision support system (DSS) is proposed, which combines a software application that visualizes 3D-based process-specific feature data and supports the execution of rework decisions with web-based business analytics dashboards. The dashboards visualize data generated by part flow simulation experiments for various rework strategies, as well as valuable data from a manufacturing execution system (MES). The proposed DSS can be easily customized to integrate additional data treasures from the ever-increasing amount of data in the industrial sector.&lt;/p&gt;</subfield>
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