## 1 Introduction  
### Evolution of Network Technologies  
Over the last decade, the manufacturing industry has been undergoing a digital transformation known as \"Industry 4.0\". Cloud, artificial intelligence (AI) and machine learning, new connectivity technologies (5G, Wi-Fi 6, etc. ), Internet of Things (IoT) and sensor technology, digital twins, and robotics are all contributing to the digitization of manufacturing [1]. Most manufacturers strive to increase efficiency and productivity. Most businesses aim for a 3% increase in productivity year over year. Thus, operational equipment effectiveness (OEE) is an important performance metric that assesses the efficiency of a production line by weighing three factors to produce an overall score: availability, performance, and quality. Additionally, three important challenges that manufacturers are facing in the volatile global marketplace are summarized as follows:  
* Global competition: as revenues from the traditional model of selling products are squeezed, manufacturers must find ways to become more efficient on a continuous basis in order to compete at lower prices or adopt new business models. * New consumer trends: consumers are increasingly expecting \"on-demand\" products that are fully customizable, putting pressure on manufacturers to reduce cycle times and create unique products while maintaining efficiencies. * Skills shortages in the workforce: the introduction of new technologies necessitates the acquisition of new skills, and the manufacturing industry is struggling to attract new talent, with an estimated 2.4 million unfilled positions (or 15% of the total workforce) in the US alone by 2028 [2]. Improving efficiency is the key to addressing the challenges. To that end, technology will be a key driver by enabling rapid digital transformation. Data can help make better decisions, but the real benefits will come from developing new business and operating models. The four pillar technologies that will help in driving efficiency are big data, analytics, connectivity and management [3]. While most people agree that better use of data can lead to better decision-making, there are still barriers to overcome. Manufacturers, for example, are facing interoperability issues. By extension, this issue is caused by the lack of tools and methods for easily connecting machines, tools and plants, and, most importantly, to aggregate data across silos in a consistent manner. On the other hand, a new generation of mobile communications is realized approximately every ten (10) years, as is illustrated in Figure 1. More details for the evolution of network technologies is listed hereafter [4; 5]:  
* 1G-voice call: the 1G mobile network was put into use in the early 1980s. It has voice communication and limited data transmission capabilities. * 2G-message passing: in the 1990s, the 2G mobile network improved voice quality, data security, and data capacity and provided limited data capabilities through the use of GSM (global system for mobile communications) standard circuit switching. * 3G-multimedia, text, internet: the first commercial 3G service was introduced in 2003, including mobile internet access, fixed wireless access, and video calling. * 4G-real-time data, car navigation, video sharing: 4G was launched in 2008, making full use of all IP networking and relying entirely on packet switching. Its data transmission speed is 10\(\times\) compared with 3G network. * 5G-is the most recent generation of mobile technology, and it differs from previous generations in that it is not simply a speed increase over 4G. It is more flexible than previous generations of cellular technology because it is software-based. Customers will be able to use different characteristics of 5G tailored to meet the requirements of specific applications, rather than one network that fits all. * 6G-is the next generation of mobile technology also known as \"Next G\", which is still under development.