Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Industrial and Systems Engineering | en_US |
| dc.contributor.advisor | Lee, Carman (ISE) | en_US |
| dc.creator | Sit, Kwok Hung | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/13626 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Adopting digital twins in job allocation and scheduling for low-volume high-mix production | en_US |
| dcterms.abstract | Social technologies have transformed lifestyles and spending patterns, driving a rising desire for unique, personalized products. This trend presents a significant challenge for manufacturing industry facing shorter product lifecycles, less standardized designs, smaller order quantities, and more frequent changes in production planning. As a result, the manufacturing industry is transitioning from mass production to a Low-Volume-High-Mix (LVHM) model. The growing number of smaller, urgent orders due to market trends and New Product Introductions (NPI) further complicates the integration of these sporadic orders into regular production batches without compromising overall efficiency. LVHM allows manufacturers to integrate product customization and smaller batch production into a cohesive manufacturing system, enhancing adaptability and agility. Efficient job allocation is crucial in this context to address these challenges and maintain production output while ensuring a high return on investment (ROI) for production equipment and systems. This research study proposes the Digital Twin-based Production Management System (DTPMS) based on the operation of Surface-Mounting-Technology (SMT) production lines. The DTPMS defines the physical space, system interface, and virtual space, enabling quick response to different scenarios and achieving a consistent 100% fulfilment rate for small orders (SOF). Simulation analysis demonstrates that the DTPMS enhances Overall Equipment Efficiency (OEE) to a high level around 80% in unpredictable and dynamic production situations. A case study conducted in a real-life production environment confirms the viability and effectiveness of the proposed system, resulting in improved production performance. Moreover, the proposed system tackles the research objectives by bridging the research gap in enhancing production output without jeopardizing the small order shipments. Simultaneously, it empowers the New Product Introduction (NPI) and fosters research and development initiatives towards the conclusive phase of commercialization. | en_US |
| dcterms.extent | 1 volume (unpaged) : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2024 | en_US |
| dcterms.educationalLevel | Eng.D. | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 8112.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 11.94 MB | Adobe PDF | View/Open |
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