SHION (Smart tHermoplastic InjectiON): An Interactive Digital Twin Supporting Real-Time Shopfloor Operations

Hermawati, Setia; Lawson, Glyn

Abstract

Injection molding is widely used to produce plastic components with large lot size. However, guaranteeing consistency and quality of parts in injection molding is challenging. Failures occur due to variation during injection cycles. Thus, real-time detection of failures will have a high impact on quality and productivity. This article is focused on Smart tHermoplastic injectION (SHION), a cloud-based Digital Twin supported by AI-based control of process parameters. Process parameters and their interrelationship with quality failure were studied and used to generate models for real-time prediction of part quality. Two injection manufacturing lines in industry were chosen for data acquisition, implementation, and validation of the Digital Twin. While SHION successfully predicted faulty products in real time, adoption of traditional Cloud-centric Internet of Things approaches poses unforeseen practical challenges such as exposure to risk of losing data due to network issues and prohibitive cost of regularly transferring a large amount data to Cloud services.

Citation

Hermawati, S., & Lawson, G. (2022). SHION (Smart tHermoplastic InjectiON): An Interactive Digital Twin Supporting Real-Time Shopfloor Operations. IEEE Internet Computing, 26(3), 23-32. https://doi.org/10.1109/MIC.2020.3047349

• Journal Article Type: Article
• Acceptance Date: Dec 21, 2020
• Online Publication Date: Dec 24, 2020
• Publication Date: 2022-05
• Deposit Date: Jan 15, 2021
• Publicly Available Date: Jan 20, 2021
• Journal: IEEE Internet Computing
• Print ISSN: 1089-7801
• Electronic ISSN: 1941-0131
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 26
• Issue: 3
• Pages: 23-32
• DOI: https://doi.org/10.1109/MIC.2020.3047349
• Keywords: Data models , Solid modeling , Real-time systems , Cloud computing , Digital twin , Predictive models , Plastics
• Public URL: https://nottingham-repository.worktribe.com/output/5227780
• Publisher URL: https://ieeexplore.ieee.org/document/9306796
• Additional Information: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.