|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|382985||660799||2016||11 صفحه PDF||سفارش دهید||دانلود رایگان|
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• Augmented Reality (AR) systems could improve performance of manufacturing processes.
• AR systems are characterized by high technological complexity.
• Their effective application in the manufacturing requires methods integrating technological and process based metrics.
• A multi-criteria model is proposed to evaluate the feasibility of AR system application.
Augmented Reality (AR) systems in last few years show great potentialities in the manufacturing context: recent pilot projects were developed for supporting quicker product and process design, as well as control and maintenance activities. The high technological complexity together with the wide variety of AR devices require a high technological skill; on the other hand, evaluating their actual impacts on the manufacturing process is still an open question. Few recent studies have analysed this topic by using qualitative approaches based on an “ex post” analysis – i.e. after the design and/or the adoption of the AR system - for evaluating the effectiveness of a developed AR application. The paper proposes an expert based tool for supporting production managers and researchers in effectively evaluating a preliminary ex-ante feasibility analysis for assessing quantitatively most efficient single AR devices (or combinations) to be applied in specific manufacturing processes. A multi-criteria model based on Analytic Hierarchy Process (AHP) method has been proposed to provide decision makers with quantitative knowledge for more efficiently designing AR applications in manufacturing. The model allows to integrate, in the same decision support tool, technical knowledge regarding AR devices with critical process features characterizing manufacturing processes, thus allowing to assess the contribution of the AR device in a wider prospective compared to current technological analyses. A test case study about the evaluation of AR system in on-site maintenance service is also discussed aiming to validate the model, and to outline its global applicability and potentialities. Obtained results highlighted the full efficacy of the proposed model in supporting ex-ante feasibility studies.
Journal: Expert Systems with Applications - Volume 63, 30 November 2016, Pages 187–197