Sponsor(s)
National Science Foundation
Contributor(s)
Ming Leu
Remote Video
Submitted by Anonymous on September 1st, 2021
Submitted by Ming Leu on June 18th, 2021
Submitted by Ming Leu on June 7th, 2021
Submitted by Zhaozheng Yin on April 8th, 2020
Submitted by Zhihai He on January 10th, 2020
Submitted by Zhaozheng Yin on February 18th, 2019
An effective way for manufacturers to tackle and outpace the increasing complexity of product designs and ever-shortening product lifecycles is to effectively develop and assist the workforce. Yet the current management of manufacturing workforce systems relies mostly on the traditional methods of data collection and modeling, such as subjective observations and after-the-fact statistics of workforce performance, which has reached a bottleneck in effectiveness.
Submitted by Zhaozheng Yin on January 22nd, 2019
Sponsor(s)
National Science Foundation
Contributor(s)
Zhaozheng Yin
Ruwen Qin
Ming C. Leu
Zhihai He
Remote Video
Submitted by Zhaozheng Yin on January 9th, 2018
While U.S. manufacturers are investing tremendous efforts and resources to regain the power and growth of manufacturing, they are confronted by a set of critical and challenging issues on the workforce.
Specifically, (1) lack of workforce with advanced training and skills; (2) need for rapid, smart, and individualized training to achieve workforce agility; and (3) on-the-job personal assistance to improve worker performance, safety and comfort.
Submitted by Zhaozheng Yin on November 29th, 2017
Submitted by Zhaozheng Yin on November 15th, 2017