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14 SMT007 MAGAZINE I JULY 2020 5G) to enable a real-time contextual under- standing and the monitoring of the manufac- turing operation and environment, the smarter decisions we are able to make [3] . Manufacturing Workforce Unlike other industry sectors, manufacturing takes the physical presence of skilled and well- trained workers. However, some functions can be performed in remote work (or work-from- home). One of the advantages of remote work is removing the geographical barriers in hiring and allowing employers to seek the best skilled workers regardless of where that talent resides. A recent survey by IBM Institute for Business Value found that more than 75% of respon- dents would like to continue working remotely at least occasionally, while more than half want it to be their primary way of working after the coronavirus crisis ends [4] . When asked what it is about remote work that has worked well, according to the Wall Street Journal, the top three on the list were: no commute, reduced meetings, and fewer distractions [5] . It is expected that the development and deployment of emerging technologies will accelerate. As 5G is becoming more avail- able and more reliable for advanced connec- tivity, innovations in how we work to achieve the maximum efficiency and output—includ- ing work-from-home—will become a part of COVID-19 catalyzed remote work, and the required social-distancing has prompted the need for more sophisticated ways to monitor factory operations, including the deployment of data management and analytics in a "further and faster" manner. One of today's deficiencies in deploying the leading technologies as effective tools, such as AI, is the lack of a relevant and sufficient data- base. AI requires a vast amount of data to func- tion as desired. Accordingly, preparing AI to facilitate manufacturing operations by initiat- ing a "data" program to collect, clean, manage, and use the data is also increasingly important. Data tells the story! Data capabilities as tools to remotely mon- itor factories, provide a clearer view of oper- ations, equipment performance and main- tenance, allowing the operation to speed up production, reduce waste, and avoid downtime by quickly identifying maintenance and pro- duction issues. By identifying and extracting relevant data sets to feed into artificial intelli- gence, we will gain the ability to predict pro- duction and supply-chain problems. With the use of AI, factories are able to go from reactive analytics, reporting on what happened, to pro- actively analyzing what might happen, and the suggested actions to take. The better we are at leveraging the emerging technologies (AI in conjunction with IoT and