Pilati F, Sbaragli A, Nardello M, Santoro L, Fontanelli D, Brunelli D
Departement of Industrial Engineering - University of Trento, via Sommarive 9, 38123 Trento (Italy).
Procedia CIRP. 2022;107:1588-1593. doi: 10.1016/j.procir.2022.05.195. Epub 2022 May 26.
Since the 11 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.
自2020年3月11日世界卫生组织宣布新型冠状病毒肺炎（COVID-19）疫情为全球大流行以来，全球官方登记的死亡人数已超过500万。根据疫情发展过程，各国政府鼓励采取最佳做法，随后取消了对日常生活的临时限制。在这种情况下，非必要的劳动密集型行业被迫暂停运营，导致大量临时裁员。在逐步恢复经济活动的过程中，各国政府通过了多项法律，以被动地减少室内工作环境中的病原体传播。然而，一些制造公司面临了几起与COVID-19相关的工伤事故。根据上述情况，本文提出了一种原创且先进的软硬件架构，以防止COVID-19在室内生产环境中传播。目的是通过接触者追踪方法提高任何室内生产场所的安全性。室内定位系统因其能够准确跟踪被标记实体的移动而构成硬件部分。为此，人工操作人员配备了适当的可穿戴传感器。采集到的原始数据通过先进算法进行适当挖掘，以定量评估任何工作环境的安全程度。实际上，软件部分以流行病学证据为参考，沿着两个相关维度定义了一个创新的风险指数。第一个维度定义了任何工人在轮班期间被感染的风险，另一个维度则表示由锚点位移定义的车间COVID-19安全程度。受益于这些有针对性的定量提示，工厂主管可以重新设计生产设置，以降低COVID-19感染的几率。这种创新的数字框架在意大利北部的一个实际案例研究中得到了验证，该案例为汽车行业进行手动机械加工。
