Steel beam welding at a construction site is challenging due to the increasing thickness of steel members in today's buildings. In order to achieve high quality welding and resolve the problem caused by the shortage of skilled welders, robotic systems are in high demand. We have proposed a practical robotic system for steel beam welding, specifically designed for working on H‐shaped column structures that are known to be the most difficult structures for automation.
This paper introduces the r-learning (robot -learning) system that utilizes robotic interactions to personalize instructions for individual children. A child who is not familiar with using an educational tool to study could learn readily from educational contents through various interactions with a robot which is based on the behavior control. The contents which are chosen according to a child's learning data extracted by analysis from human-robot interaction data could lift the educational effectiveness. An r-learning scenario is designed by using Petri net to handle exception occurred in a learning process. The robot contents maker and the Open API for operating a robot are described as management utilities for a personalized r-learning system.
In order to control a process that has short production cycle and where the product type and specifications change often with conventional shewhart control charts such as and control charts, a new control chart must be applied every time the parameters change . As this is a very inefficient method in terms of the cost and time, CV control chart using coefficient of variation statistics was developed. As CV control chart reflects only the current sample data on control chart, it can be useful when there is a significant change in process. However, it does not respond sensitively to a process that has subtle change or requires a high control level. CV-EWMA control chart was researched to monitor small shifts in CV. This study proposes a way to improve accuracy and precision of population parameter estimation of conventional CV-EWMA control chart and applied it to a control chart before analyzing its performance. As a result, the accuracy and precision of conventional CV-EWMA control chart has been improved and it was verified that the proposed control chart is a proper control chart to control small shifts of CV.
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