ABSTRACT
The outbreak of the Covid-19 pandemic in recent years and the epidemics of infectious diseases that have occurred around the world over the years, there are problems of lack of medical supplies and difficulties in personnel scheduling. Intelligent medical transportation through modern technology is an effective means to solve this problem. AGV(Automated Guided Vehicle) transportation and UAV(Unmanned Aerial Vehicle) transportation are important ways for intelligent transportation of medical materials. This paper investigates semantic segmentation as a key technology for AGV transport and UAV transport. This paper compares other traditional semantic segmentation networks, and at the same time considers the characteristics of all-weather, all-terrain, and complex transportation of materials in medical transportation, and proposes SSMMTNet(Semantic segmentation of medical material transportation Net). Among them, we propose a Scaling Transformer Block that can extract depth features of point clouds to enrich contextual information. At the same time, the network is validated on the benchmark Semantic3D dataset, obtaining 71.5% mIoU and 90.6% OA. © 2022 IEEE.
ABSTRACT
The Fourth Industrial Revolution or Industry 4.0 is extremely relevant and important in manufacturing for several reasons. Failing to adopt the technology of the Fourth Industrial Revolution can cause organizations to fall behind, as their operations are not digitized enough in benchmarking competitors. A major industry as bicycle manufacturing needs to be transformed into a digital factory in order to keep up with the evolving technology. The objectives of this research are in designing a 3D digital mock up and Augmented Reality (AR) for bicycle frame production in the form of digital factory for increasing production capability by decreasing the break-even point whilst avoiding Covid-19 contraction using Tecnomatix Plant Simulation and Unity 3D programs. This research constructed three alternative digital factory layouts that are designed by using a 3D simulation program. The risk of Covid-19 contraction points and the three layouts of cost per unit are analyzed. The results show that the break-even point of the first to the third layouts with Automated Guided Vehicle (AGV) are 26,580, 26,322 and 25,354 units respectively. The result of the risk about Covid-19 contraction points from the first to the third layout with AGV are 21,272, 2,872 and 0 points respectively. This means the most appropriate layout for bicycle frame production is the third layout due to the best break-even point that can significantly avoid Covid-19 contraction. The benefit of this research is to integrate a 3D digital mock up, AR and Cobot including AGV to assist the resilience of operations with a dynamic industrial environment. © 2022 King Mongkut’s University of Technology North Bangkok. All Rights Reserved.
ABSTRACT
Because of the outbreak of COVID-19, “contactless distribution” will become the main direction of future medical logistics and transportation. In order to realize the distribution mode, the hospital drug delivery AGV is designed, including structure design and control system design. The structure design adopts induction line pilotage, wheel structure of three row-six wheel and double-wheel differential driving structure, and uses 3D software for structure modeling. The design of the control system adopts fuzzy control to adjust AGV wheel speed to realize the automatic deviation correction function when AGV is running, and the simulation of the automatic deviation correction control system is carried out. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Hospitals play an important role in the development of the country. Every hospital staff plays an essential role in their work. If hospitals are overcrowded, patients feel so difficult to meet doctors and all staff facing the same issue. If it satisfies, the hospital facing another of hygiene. It is very important to concentrate everything to develop our nation. ROS and path planning-based robot is used in the hospital environment for all the staff members, especially nurses to complete their tasks quickly. A mini type robot is developed for monitoring the patient physical condition and deliver the tablets to the patients in time. Robots collect the whole data by themselves and send the data to doctors and nurses. A server is maintained for collecting the data. A doctor can access the data even doctors are unavailable. Data are registered in a common platform to view anyone according to that doctors can follow treatment for their patients. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.