Model-based engineering for the integration of manufacturing systems with advanced analytics
المؤلف | Lechevalier, David |
المؤلف | Narayanan, Anantha |
المؤلف | Rachuri, Sudarsan |
المؤلف | Foufou, Sebti |
المؤلف | Lee, Y. Tina |
تاريخ الإتاحة | 2021-09-08T06:49:44Z |
تاريخ النشر | 2016 |
اسم المنشور | IFIP Advances in Information and Communication Technology |
المصدر | Scopus |
الرقم المعياري الدولي للكتاب | 18684238 |
الملخص | To employ data analytics effectively and efficiently on manufacturing systems, engineers and data scientists need to collaborate closely to bring their domain knowledge together. In this paper, we introduce a domain-specific modeling approach to integrate a manufacturing system model with advanced analytics, in particular neural networks, to model predictions. Our approach combines a set of meta-models and transformation rules based on the domain knowledge of manufacturing engineers and data scientists. Our approach uses a model of a manufacturing process and its associated data as inputs, and generates a trained neural network model as an output to predict a quantity of interest. This paper presents the domain-specific knowledge that the approach should employ, the formal workflow of the approach, and a milling process use case to illustrate the proposed approach. We also discuss potential extensions of the approach. IFIP International Federation for Information Processing 2016. |
راعي المشروع | The research in this paper was supported by National Institute of Standards and Technology?s Foreign Guest Researcher Program, and Cooperative Agreement No. 70NANB14H250. |
اللغة | en |
الناشر | Springer New York LLC |
الموضوع | Data analytics Manufacturing process Meta-model Neural network Predictive modeling |
النوع | Conference Paper |
الصفحات | 146-157 |
رقم المجلد | 492 |
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