An Artificial Intelligence-Based Digital Twin Approach for Rejection Rate and Mechanical Property Improvement in an Investment Casting Plant
Source abstract
Abstract
The manufacturing process carried out in the investment casting industry suffers from problems similar to other production processes. In addition, the high requirements of the customers and the industries that require these parts mean that high quality standards must be met. If those requirements are not achieved, this leads to the rejection of the manufactured parts. Therefore, given the current technology revolution (i.e., Industry 4.0) and the possibilities offered by tools such as digital twins and artificial intelligence, it is possible to work on a generation of intelligent systems that can reduce and even avoid these problems. Therefore, this study proposes the creation of a digital twin based on artificial intelligence to work on proactively identifying problems before they happen and, if they are detected, launch an optimization process that offers corrective actions to solve them. More specifically, this work focuses on the analysis of the manufacturing process (definition, KPI extraction, capture, distribution, and visualization), the creation of a base system for the integral management of process optimization, and experiments developed for determining the best method for making predictions. Additionally, we propose a recommender system to (i) avoid the appearance of porosities and (ii) keep the elongation of the parts in the ranges desired by the customer.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Digital Transformation in Industry · Additive Manufacturing Materials and Processes · Manufacturing Process and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Azterlan Member of Basque Research Team Alliance (BRTA), Aliendale Auzunea 6, 48200 Durango, Spain
EIPC Research Center, AIE, Torrekua 3, 20600 Eibar, Spain
Funding
European Union
References (78)
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