When Charles Chaplin filmed Modern Times back in 1936, he brilliantly portrayed the revolutionary “efficiencies” of modern industrialization that characterized the Industry 2.0 era. The use of electricity, mass manufacturing, continuous assembly lines, and hundreds of workers loading, operating and unloading the machines marked the industrial revolution. At the time, process automation was nonexistent, the quality was unpredictable, efficiency was weak, and health and safety conditions were less than desirable.

With Process Automation, robots, and IT, the world entered the Industry 3.0 era, which was characterized by significant improvements in productivity, efficiency, quality, and safety. Sensors, Control Systems, and Automatic Control Valves produced substantial operational improvements across all industries. Process Optimization came later to provide yet another boost in productivity, quality, and predictability.

As microprocessors, memories, and batteries became smaller, more powerful and affordable, more intelligence has been built into industrial field devices, such as sensors and valves, as well as on machines. Besides, the emergence of potent Edge and Cloud computing, the Internet of Things and advanced industrial networks, have enabled the capture, sharing, and analysis of massive amounts of data. This data is then analyzed and processed by Artificial Intelligence (AI) applications supported by Augmented Reality (AR) representations.

"Smart Factories will be able to monitor machine capacity, throughput, efficiency, and quality across the supply chain"

The transformation of (the once) stand-alone field devices and machines into interactive members of the factory eco-system and the effective use of data for more efficient operations mark the beginning of the Industry 4.0 era and the Smart Factory. The benefits and progress that Industry 4.0 will drive will span over every single aspect and area of a Smart Factory. Manufacturing processes and Supply Chain will experience tremendous incremental improvements as the result of transforming the plants into intelligent networks of cybernetic physical systems that share with robust computer systems to drive tighter control and more creative and effective decisions and actions.

The Smart Factory

Smart Factories will operate much more efficiently, with tighter quality control, fewer accidents, and pollution, and the manufacturing lines will be more flexible. Non-manufacturing industries like power generation will also benefit from better turbine condition predictability, remote monitoring, and smart grids.

Uptime: Maximizing uptime and minimizing downtime have been significant concerns in the industry for years. Machineprotection and monitoring have been around for some time but have not been effective at accurately predicting when a failure would occur. It is only now that by using data, statistical models, correlations, inference, and artificial intelligence that the maintenance team can come close to predicting machine failure and act ahead by preparing the maintenance crew and ordering
all necessary parts in advance of the planned shutdown. The use of Augmented Reality assists the repairmen in performing the repairs faster than before. The overall result is an increase in productivity, safety, and production predictability with a positive impact on the customer waiting for the goods.

Supply Chain: Until now, manufacturers have counted with robust systems for production forecasting, production planning, and delivery. However, their ability to track the performance of manufacturing production throughout the whole supply chain has remained a problem. Smart Factories will be able to monitor machine capacity, throughput, efficiency, and quality across the supply chain. As well as having the ability to benchmark productivity among machines, site and processes.

The human factor: In smart factories, many tasks currently carried out by humans will switch to machines, sensors, actuators, and computers. The employees will be responsible for higher level functions and will require a different skill set going forward. This should attract millennials who seek job opportunities where computer science, manufacturing, and IoT play together. Coordinated execution between IT and OT to ensure that both departments goals and objective remain aligned and synergistic will be a must.

Services: Some market analysts of the Industry 4.0 era have characterized the IIoT products as the “vehicle to sell services.” It is already common in the wind energy market, for example, to see third-party service companies remotely monitoring thousands of wind turbines to provide alarms, information, and advice to the operators about the condition of each turbine.

Manufacturers of industrial equipment such as compressors, turbines, generators or pumps, to name few, are already working to develop condition monitoring, predictive maintenance, and performance monitoring services to offer to their customers.

New business models such as “Uptime as a Service” will be accepted mainly in the future, creating new revenue streams for OEMs and specialized service independent companies.

Enablers of the Smart Factory
Effective use of the data: The AI systems use the vast amounts of data from sensors across the plant to resolve specific issues or applications in the smart factory. How that data is used will have a significant impact on the benefits to be obtained. Until now, as much as Industry 4.0 represents the next industrial revolution, the industry is merely scratching the surface in terms of all the potential the IIoT and AI can offer, and we will see truly significant results in the years to come. A considerable number of companies are running IIoT pilot applications toexperiment and learn how to handle so much data, to correlate data to events, to develop and fine-tune the algorithms according to their needs, and even to decide where the data will be stored and processed (the device, the Edge or the Cloud). We should see that, between 2020 and 2021, there will be a proliferation of larger IoT applications.

Sensors and Computational power: Smaller, lower cost and more different sensors can be installed on almost any machine, actuator, valve or motor, along with all necessary electronics. Dozens of well- established companies and start-ups continue to develop sensors of all different type of variables

There is an explosion of software application to predict machine lifetime, assist with spare parts, repairs, and life cycle management. This trend will continue as machine makers use more and more data and intelligence. Mobile device apps to monitor assets will provide additional value.

Security: Security is, undoubtedly, the most pressing concern in any IIoT project. The numerous hacking attempts, some with success, on industrial sites cannot be ignored, and only with an extremely robust, hacker-proof technology will the industry invest heavily in IIoT.

Integration of platforms: For any IIoT application to deliver the results and benefits sought, it is essential the all the systems which collect, transmit, store, analyze and use the data be all integrated, including ERP, CRM, and MMI.

5G: 5G next-generation wireless network technology is set to be commercially available in 2020. It is anticipated to be much faster than 4G, have lower latency and better coverage. These capabilities will allow substantial amounts of data transfer in seconds, providing an ideal platform for IIoT applications.

In summary, the Smart Factory, which is an outcome of the application of the IIoT, AI, AR, Edge, and Cloud Computing, will drive the new industrial revolution of the Industry 4.0. A connected plant, which connects to its machines, to the customers, to the suppliers, and the whole internet. A vast ecosystem is continuously learning and evolving. A scenario only possible until recently in the science- fiction movies, quite an impressive evolution from Chaplin’s Modern Times.