Jetting of epoxies and other materials is going to change the way people do dispensing. For thelast twenty years, dispensing has evolved from merely pushing fluid through a needle to a highly automatedproduction proce...Jetting of epoxies and other materials is going to change the way people do dispensing. For thelast twenty years, dispensing has evolved from merely pushing fluid through a needle to a highly automatedproduction process. Controlling fluid deposition, needle positioning and dispensed volume accuracy hasdramatically improved in recent years. Additionally, speed has increased while software has simplified operationalcontrol. Now jet dispensing fluids has become practical and it is going to have as large an impact on theelectronics assembly industry that Ink Jet printing has had in the office / home environment.展开更多
The Made in China 2025 initiative will require full automation in all sectors, from customers to production. This will result in great challenges to manufacturing systems in all sectors. In the future of manufacturing...The Made in China 2025 initiative will require full automation in all sectors, from customers to production. This will result in great challenges to manufacturing systems in all sectors. In the future of manufacturing, all devices and systems should have sensing and basic intelligence capabilities for control and adaptation. In this study, after discussing multiscale dynamics of the modern manufacturing system, a five-layer functional structure is proposed for uncertainties processing. Multiscale dynamics include： multi-time scale, spacetime scale, and multi-level dynamics. Control action will differ at different scales, with more design being required at both fast and slow time scales. More quantitative action is required in low-level operations, while more qualitative action is needed regarding high-level supervision. Intelligent manufacturing systems should have the capabilities of flexibility, adaptability, and intelligence. These capabilities will require the control action to be distributed and integrated with different approaches, including smart sensing, optimal design, and intelligent learning. Finally, a typical jet dispensing system is taken as a real-world example for multiscale modeling and control.展开更多
文摘Jetting of epoxies and other materials is going to change the way people do dispensing. For thelast twenty years, dispensing has evolved from merely pushing fluid through a needle to a highly automatedproduction process. Controlling fluid deposition, needle positioning and dispensed volume accuracy hasdramatically improved in recent years. Additionally, speed has increased while software has simplified operationalcontrol. Now jet dispensing fluids has become practical and it is going to have as large an impact on theelectronics assembly industry that Ink Jet printing has had in the office / home environment.
基金partially supported by a GRF project from RGC of Hong Kong China (City U: 11207714)+2 种基金a SRG grant from City University of Hong Kong China (7004909)a National Basic Research Program of China (2011CB013104)
文摘The Made in China 2025 initiative will require full automation in all sectors, from customers to production. This will result in great challenges to manufacturing systems in all sectors. In the future of manufacturing, all devices and systems should have sensing and basic intelligence capabilities for control and adaptation. In this study, after discussing multiscale dynamics of the modern manufacturing system, a five-layer functional structure is proposed for uncertainties processing. Multiscale dynamics include： multi-time scale, spacetime scale, and multi-level dynamics. Control action will differ at different scales, with more design being required at both fast and slow time scales. More quantitative action is required in low-level operations, while more qualitative action is needed regarding high-level supervision. Intelligent manufacturing systems should have the capabilities of flexibility, adaptability, and intelligence. These capabilities will require the control action to be distributed and integrated with different approaches, including smart sensing, optimal design, and intelligent learning. Finally, a typical jet dispensing system is taken as a real-world example for multiscale modeling and control.
