Motion time study is employed by manufacturing industries to determine operation time.An accurate estimate of operation time is crucial for effective process improvement and production planning.Traditional motion time...Motion time study is employed by manufacturing industries to determine operation time.An accurate estimate of operation time is crucial for effective process improvement and production planning.Traditional motion time study is conducted by human analysts with stopwatches,which may be exposed to human errors.In this paper,an automated time study model based on computer vision is proposed.The model integrates a convolutional neural network,which analyzes a video of a manual operation to classify work elements in each video frame,with a time study model that automatically estimates the work element times.An experiment is conducted using a grayscale video and a color video of a manual assembly operation.The work element times from the model are statistically compared to the reference work element time values.The result shows no statistical difference among the time data,which clearly demonstrates the effectiveness of the proposed model.展开更多
By combining laboratorial experiments,theoretical analysis and mathematical model,theeffect of sediment motion on transport-transformation of heavy-metal pollutants is studied. (1)Previous studies on adsorption-desorp...By combining laboratorial experiments,theoretical analysis and mathematical model,theeffect of sediment motion on transport-transformation of heavy-metal pollutants is studied. (1)Previous studies on adsorption-desorption of heavy-metal pollutants by sedimentparticles are systematically summarized.Based on this summary,subjects that need to be furtherstudied are put forward. In rivers most heavy-metal pollutants concentrate on sediment particles.In order tocontrolling water pollution aused by heavy-metal pollutants following topics should beemphasized:studies on the effect of suspended matter and deposit on transport-transformation of展开更多
基金This work is jointly supported by the SIIT Young Researcher Grant,under a Contract No.SIIT 2019-YRG-WP01the Excellent Research Graduate Scholarship,under a Contract No.MOU-CO-2562-8675.
文摘Motion time study is employed by manufacturing industries to determine operation time.An accurate estimate of operation time is crucial for effective process improvement and production planning.Traditional motion time study is conducted by human analysts with stopwatches,which may be exposed to human errors.In this paper,an automated time study model based on computer vision is proposed.The model integrates a convolutional neural network,which analyzes a video of a manual operation to classify work elements in each video frame,with a time study model that automatically estimates the work element times.An experiment is conducted using a grayscale video and a color video of a manual assembly operation.The work element times from the model are statistically compared to the reference work element time values.The result shows no statistical difference among the time data,which clearly demonstrates the effectiveness of the proposed model.
文摘By combining laboratorial experiments,theoretical analysis and mathematical model,theeffect of sediment motion on transport-transformation of heavy-metal pollutants is studied. (1)Previous studies on adsorption-desorption of heavy-metal pollutants by sedimentparticles are systematically summarized.Based on this summary,subjects that need to be furtherstudied are put forward. In rivers most heavy-metal pollutants concentrate on sediment particles.In order tocontrolling water pollution aused by heavy-metal pollutants following topics should beemphasized:studies on the effect of suspended matter and deposit on transport-transformation of
