As industries move toward greater automation of production, the idea of fully automated factories and production facilities is gaining more and more public attention. Although it is still a provocative idea of the future that would cause numerous discussions and societal breakdowns, fully automatic factories or fully autonomous factories, also known as lights-out factories, or even unmanned factories, represent in reality the use of a series of applications with the help of AI in order to bring the discrete production systems as far as possible to a state of autonomy and automation that does not require the presence of a human. Essentially, this goal would be achieved with the help of the connectivity of the control centre and one or more factories around the world, through networked sensors managed by AI, using the Internet of Things (IoT) and cloud-based technology. All of this would be managed by a single system that would remotely intervene in cases of disruption of production processes or security. SCADA systems in power distribution or railway control systems already function much in this way. The market is estimated to grow by 13.5% yearly by 2030, and this time Asia-Pacific is the leading region in adopting this new technology.
Are we reaching the unmanned smart manufacturing?
We can say that step by step we are really getting closer to this type of production, since part by part of the production processes are increasingly being replaced by automatic elements. And the ideal case is so-called lights-out production, where figuratively "lights can be turned off in the factory" because production and control are carried out without people entering the plant, in which case light is unnecessary and energy is saved. However, what is important in terms of management and software here is not the automation of the production process itself, which is the subject of the procedures of the factory itself, but the automatised monitoring process.
The fundamental function of any WMS is to record elements such as the arrival and departure of each inventory item, as well as the location of the inventory item - in which warehouse it is located, in which hall, in which part of the hall and on which shelf, and so on.
Unmanned factories should work in a more or less autonomous way, and respond to external disturbances such as a change in temperature outside the working range, a change in humidity, a change in the time for making an element, and the like, in real time, in an intelligent and human-like way. These external disturbances can go as far as a machine failure, system crash, power outage, storm, flood, lightning strike or other natural disasters, in which case the system would recognise the parameters, and according to them recognise the events that caused them and consequently take adequate measures.
In this present phase, until unmanned factories are reached, by using software solutions for remote monitoring of sensors and production facilities, managers and production controllers in this kind of factory management will control the data not in the factories themselves, by reading sensors, but by accessing data in the cloud, and react to possible disturbances and malfunctions, if the system itself does not reach equilibrium.
Over time, such a digital learning factory becomes such a factory that can be tailor-made and reprogrammed to meet the production needs of each client, and the manufacturing knowledge base becomes additive in time.
What is the value of a management system in smart manufacturing?
Fortune Business Insight says that the market size of Smart manufacturing itself was 277.81 billion USD in 2022, and that it will grow to 310.92 billion in 2023 and that the growth projections are estimated to 754.1 billion in 2030, which is a CAGR of 13.5% during the period 2023-2030, and this is an extremely fast-growing market.
North America and Europe are not leading the game here, but the smart manufacturing industry is in the hands of Asia-Pacific with a 36.33% share in 2022.
Precedence Research has somewhat more modest, but almost equally spectacular forecasts, and claims that the global smart factory market size is expected to hit around USD 321.98 billion by 2032, growing at a CAGR of 9.52% from 2023 to 2032.
Therefore we can be sure that the automated control systems will have a market value that corresponds tightly with the smart manufacturing market value.
What is the advantage of adopting this technology?
If the reading of the sensors and the decision to initiate the reaction are not made by humans, they can be sent to other tasks, such as quality control (with retraining), and productivity would be increased, while costs would decrease, including the costs of maintaining the physical parameters in the environment, noise, light and air quality, heating, all the way to the general abolition of lighting systems since this technology will effectively render them obsolete.
Systems that would do this automatically are programmed to monitor all sensors at all times, which is an impossible task from the human side.
Also, some of the benefits are the precise determination of the life of equipment based on the assessment of use and wear of parts, costs reduction caused by failures that lead to loss of income, waste reduction and identification of defects that are transferred to product before defective products leave the production area and even reach the quality control area.
We can also reduce downtime when replacing/repairing reactive equipment or unexpected production stoppages, reduce the cost of external cleaning services by preventing large spills of raw materials, improve efficiency and profitability by minimising unnecessary maintenance costs, enable currently unavailable diagnostics through richer data sets to be rapidly analysed by AI in the cloud. This includes software tools for root cause analysis and predictive analytics for improved process efficiency, as well as obvious, real-time visibility into the manufacturing process.
If the system is programmed to make human-like decisions with AI, instead of simple and automatically pre-programmed decisions (in which scenario the humans are still necessary), the safety is increased.
Why adopt this concept?
There are several clear advantages for early adopters: reduction of human errors, improved efficiency, better and faster performance of repetitive tasks without human fatigue and errors, cost savings, improved safety, addressing issues proactively by remote sensor-reading before accidents occur, increased flexibility, enabling rapid changes in case of changes in market requirements, and enhanced quality control. All these savings in time and money cumulatively create a better position in the market and a competitive advantage for the company that adopts the concept before others.
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