ABSTRACT
In this paper, an autonomous mobile robot (AMR) that delivers food to patients in hospitals during COVID-19 pandemic situation was proposed. AMRs are one of the tools that can minimize direct physical contact between healthcare worker and patients to prevent infection. As some of the hospital logistic tasks are handled by the AMRs, more manpower can be distributed to more important tasks. This is a capstone project developed by a group of students from the Faculty of Engineering, at UCSI University. The project was completed with a concept design, a virtual prototype, and computer simulation of the robot. © 2021 IEEE.
ABSTRACT
Aim: To analyze the role of the logistics support services in nosocomial infection control during emergency periods, with a focus on job responsibilities including the organization of vehicle parking, supply of hospital meals, washing of medical bedding and clothing, disposal and management of medical sewage and waste, elevator services, disinfection of air conditioning systems, disinfection and cleaning of ambulances, management of hospital buildings, storage of sterilization supplies, reception and delivery of oxygen cylinders and protection of staff health as examples. Methods: The adjustment and optimization of the emergency support system and working mode as part of hospitals' response to major public emergencies were summarized, and the vital supporting role of the logistics support services in nosocomial infection control was analyzed. Results: The logistics support services played a crucial role in ensuring the high-performance operations of the hospitals and control of nosocomial infections, resulting in the excellent outcome of "zero infection" among hospital staff. Conclusion: Establishing a safe, flexible and efficient system for the logistics support services is important in ensuring an effective response by hospitals to health emergencies.
ABSTRACT
The unexpected crisis posed by the COVID-19 pandemic in 2020 caused that items such as face shields and ear savers were highly demanded. In the Barcelona area, hundreds of volunteers employed their home 3D-printers to produce these elements. After the lockdown, they had to be collected by a reduced group of volunteer drivers, who transported them to several consolidation centers. These activities required a daily agile design of efficient routes, especially considering that routes should not exceed a maximum time threshold to minimize drivers' exposure. These constraints limit the number of houses that could be visited. Moreover, travel and service times are considered as random variables. This logistics challenge is modeled as a stochastic team orienteering problem. Our main performance indicator is the collected reward, which should be maximized. This problem is solved by employing a biased-randomized simheuristic algorithm, which is capable of generating high-quality solutions in short computing times. © 2021 IEEE.