ABSTRACT
Since the 11th of March 2020 when the World Health Organization declared the novel COVID-19 outbreak a global pandemic, it registered officially over 5 million deaths worldwide. According to the course of the pandemic, governments encouraged best practices and then ruled out temporary restrictions on daily lives. In this scenario, non-essential labor-intensive sectors were forced to put on hold operations producing massive temporary layoffs. In gradually restoring the economic activities, governments passed several laws to passively mitigate the pathogen transmission in indoor working environments. However, several COVID19-related injuries were filled by manufacturing companies. According to the outlined conditions, this paper proposes an original and advanced hardware and software architecture to prevent the COVID19 transmission in indoor production environments. The aim is to increase the safety of whichever indoor productive workplace through a contact tracing approach. Indoor positioning systems due to their ability to accurately track the movement of tagged entities compose the hardware part. For this purpose, human operatives are equipped with adequate wearable sensors. Raw data acquired are properly mined through advanced algorithms to quantitatively assess the degree of safety of any working setting. Indeed, having as a reference the epidemiological evidence the software part defines an innovative risk index along two correlated dimensions. While the first defines the risk of any worker getting infected during the shift, the other one expresses the degree of COVID19-safety of the shop floor defined by the displacements of the anchors. Benefitting from these targeted and quantitative hints, plant supervisors may redesign the production settings to lower the chances of COVID19 infection. This innovative digital framework is validated in a real case study in the North of Italy which performs manual mechanical processing for the automotive industry.
ABSTRACT
COVID-19 pandemic caused several million deaths worldwide since the beginning of 2020. One of the most effective activities to contrast its diffusion is the execution of mass testing campaigns to track the virus spread. To design an efficient logistic system for such purpose, it is important to correctly plan the clinic layout and size the medical resources involved in the swab testing campaign, to avoid long patient queues or personnel underutilization. This paper describes the development of an original logistics simulation model to support the planning and design of clinics for the walk-in mass testing campaign against COVID-19 performed by South Tyrol Health Agency in just one weekend in November 2020 which involved more than 350’000 citizens. The developed model represents the targeted physical system considering all the different phase of such healthcare process. Furthermore, the duration of the multiple process phases is statistically distributed according to a large dataset collected during the COVID-19 testing campaign for touristic operators conducted in September and October 2020 in South Tyrol. The simulation model virtually evaluates the swab testing clinics with different parameters to determine the best scenario to be implemented. It concerns the number of medical resources allocated, the necessary clinic spaces and the time spent inside the clinic by each patient. The obtained results suggest that the so-defined configuration is distinguished by an average throughput of 8.8 minutes per patient. This clinic prototype has been replicated and set-up all over South-Tyrol territory to reach the targeted number of tested citizens. Indeed, 362’050 people were effectively tested from 20th to 22nd November 2020 leveraging 184 clinics and about 1400 healthcare co-workers, both medical and non-medical personnel. 3’615 Covid-positive people were detected and the virus transmission index of this Province fell from 1.22 to 0.74 just in the following 2 weeks. © 2021, AIDI - Italian Association of Industrial Operations Professors. All rights reserved.
ABSTRACT
The health emergency connected to the spread of the COVID-19 epidemic worldwide has caused a substantial suspension of the vast majority of face-to-face work activities that characterize manufacturing companies. The gradual reduction of new infections achieved thanks to the lockdown has brought attention to the topic of how "restarting" the activities into work environments, which must be carried out guaranteeing health security and avoiding the kick-off of a new phase of expansion of the disease due to contacts in the workplace. On the other hand, this moment of "forced renewal" could be the best opportunity to accelerate and implement the innovative technologies fostered for "Industry 4.0" because of the significant socioeconomic changes that it promises to bring. This paper presents a contact tracing framework based on an inexpensive and non-intrusive wearable sensor able to provide positioning data along with cardinal directions and orientation. A mixed ultra-Wide Band/Bluetooth, UWB/BLE, approach permits to know the operators' accurate position and orientation. Their interactions during working activities can be regulated by a tool that suggests the implementation of social distancing measures for contagion reduction.