The role of Artificial Neural Network in the covid-19 era to support manufacturing Industry resilience

The Covid-19 pandemic has impacted, and in some cases disrupted, the global value chains thus causing a widespread interruption of operations and shortages of raw materials. As a snowball, in a globally interconnected world, such problems have been gradually amplified while moving downstream the majority of supply chains. Both academia and consulting institutions have provided guidelines and suggestions to support companies to overcome the challenges they were facing. In this research, the authors have clustered 3 main areas of interest in response to the issue abovementioned, namely: 1) Approach to activities, 2) Supply Chain (SC) enhancement and 3) Digitalization. Hence, these clusters have been detailed into solutions to be adopted that support companies in achieving a resilient network. In particular, the authors have focused on how Artificial Neural Networks (ANNs) may support manufacturing firms to solve the challenges they faced throughout the pandemic. Hence, this research aims at proposing an updated framework about the state-of-the-art of Artificial Neural Network applications in manufacturing, proposing twelve fields of application to support operations. These algorithms must be integrated with seven technologies, which are: Industrial Analytics, Additive Manufacturing (AM), Process Management, Advanced Automation, Cloud Manufacturing (CM), Industrial Internet of Things (IIoT), Advanced Human Machine Interface (HMI), and Digital Twin (DT) and related applications. Finally, the research aims at suggesting a prioritization of the solutions to be introduced within manufacturing companies, identifying smart manufacturing technologies as priorities in building a more resilient network, all stand out Additive Manufacturing, Digital Twin and Industrial Internet of Things.