FLAIR:2024制造業GPT和智能微工廠:香港如何引領全球制造業的未來白皮書(英文版)(20頁).pdf

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FLAIR:2024制造業GPT和智能微工廠:香港如何引領全球制造業的未來白皮書(英文版)(20頁).pdf

1、WHITE PAPERSWOTSTRENGTHSWEAKNESSESOPPORTUNITIESTHREATSProduct DevelopmentMaintenance and Repair Quality Control and Assurance Logistics and Supply Chain Planning and Scheduling ProductionProcesses Avoid creative block Reduce researching tasks and documentation No-code solutions with natural language

2、 interface Creation of code snippets,debugging and automated documentation Design improvements Automated requirement Engineering Guiding and copiloting of Maintenance Services by junior/inexperienced personnel(recommendation systems)Learning and training support GPT-supported training of detection/s

3、egmentation models in quality control(zero/few-shot)Recommendation systems for root-cause analysis of defects Goods inspection(inbound&outbound)Automating customer care LLM-based vision systems Factory layout planning Machine selectlon Drafting standard operating procedures(SOP)Reduce tedious docume

4、ntation Minimize needed expertise in problem-solving Reduction of language barrier Reduce ramp-up time for quality inspection Co-piloting root-cause analysis and quality improvement Root-cause analysis Seamless interface for track and trace Improving warehouse management Super catalyst for highly-fl

5、exible robots Advanced interface for planning activities Avoid creative block for design processes Language interface for operation dashboards Reduce ramp-up time DepartmentImprovement PotentialsExamplesHigh ImpactMedium ImpactProduct DevelopmentMaintenance and Repair Quality Control and Assurance L

6、ogistics and Supply Chain Planning and Scheduling ProductionProcesses Avoid creative block Reduce researching tasks and documentation No-code solutions with natural language interface Creation of code snippets,debugging and automated documentation Design improvements Automated requirement Engineerin

7、g Guiding and copiloting of Maintenance Services by junior/inexperienced personnel(recommendation systems)Learning and training support GPT-supported training of detection/segmentation models in quality control(zero/few-shot)Recommendation systems for root-cause analysis of defects Goods inspection(

8、inbound&outbound)Automating customer care LLM-based vision systems Factory layout planning Machine selectlon Drafting standard operating procedures(SOP)Reduce tedious documentation Minimize needed expertise in problem-solving Reduction of language barrier Reduce ramp-up time for quality inspection C

9、o-piloting root-cause analysis and quality improvement Root-cause analysis Seamless interface for track and trace Improving warehouse management Super catalyst for highly-flexible robots Advanced interface for planning activities Avoid creative block for design processes Language interface for operation dashboards Reduce ramp-up time DepartmentImprovement PotentialsExamplesHigh ImpactMedium ImpactAuthors

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