| Project Reference: | ITP/042/18LP |
| Project Title: | Machine Learning and Analytics for Supply Chain Service Automation |
| Hosting Institution: | LSCM R&D Centre (LSCM) |
| Abstract: | The basic components of a supply chain include supplier, manufacturer, distributor,retailer, and shopper. In particular, manufacturers often involve many procedures that require much hand-eye coordination. Such manual procedures are very labor-intensive,tedious, and often slow. As speed is critical to modern supply chain, robotic process automation is a promising solution to those procedures. An effective integration and management of the supply chain components help to reduce cost, increase production, address labor shortages, avoid human errors, and improve customer service. In this respect, employing new machine learning vision technologies in supply chain automation will be helpful. This project aims to develop machine learning based computer vision tools to automate some manufacturing and quality control procedures that require much tedious hand-eye coordination. Specifically, we will develop novel computer vision and robotic technologies for the following procedures: a. Skeleton detection for sample collection process, e.g., toy; b. Target localization based on multi-scale multi-viewpoint feature descriptors for process application, e.g., glue dispensing; c. Application area identification using various imaging modalities. This project has been defined by a present need of local industry. With a number of new technologies incorporated into different stages of the supply chain, the overall productivity will be greatly increased. |
| Project Coordinator: | Dr Ka Lun Fan |
| Approved Funding Amount: | HK$2.78M |
| Project Period: | 01 Sep 2018 - 30 Aug 2019 |
