How Predictive Maintenance And The Internet of Things Are Shaping The Smart Manufacturing Companies

Oct 25

The Internet of Things (IoT) is a significant concept for companies that a specific word variant has been defined for the industrial sector: the industrial Internet of Things (IIoT). According to recent studies, the smart factory market will exceed 200 billion dollars by 2022. Its growth is stimulated by innovations such as IoT and big data, which means pushing productivity and profitability to new levels. It is a turning point that will benefit everyone, from producers to consumers.

Among the many declinations of the IIoT, the manufacturing one generates considerable benefits, from improved productivity and greater safety of the labourers up to the management of quality and inventories. Among these, predictive maintenance is often minimized when compared to all others.

Here are some of the benefits that can derive from predictive maintenance:

• Prevention of hardware crashes


The IoT-enabled production equipment uses integrated sensors and advanced algorithms to perform predictive analysis and reveal problems before they occur. This not only reduces downtime to a minimum, but predictive attention is given to data, which significantly reduces the time spent identifying the problems, speeding up any preventive maintenance strategy. It also provides engineers with the ability to plan and repair when the machine is offline and inactive.

Some automotive companies (like GM) are using IoT sensors to monitor the temperature before painting new cars. If the environment is excessively cold or extremely hot their equipment will immediately be damaged and will not function properly. Other manufacturers use automated notification sensors to identify performance drops, unexpected bottlenecks or potential hazards.

• Enhanced product quality and customer care


Goods manufactured ready for shipment or distribution are subject to damage also due to sudden machine failures. If an assembly robot or a CNC (computer numerical control) machine stops in the middle of production those specific pieces and the raw materials that compose them are immediately wasted. But the situation is even worse if these machines do not work properly, because they may cause serious problems. In addition to providing the customer with a lower quality product, some defects could also cause health problems.

Some heavy construction companies are quickly embracing the IoT. As a result, their customers and partners enjoy many tangible benefits, including fuel cost savings, much higher equipment uptime and greater profitability. It is a winning situation for all those involved because companies improve their image, customers improve how they allocate their resources and consumers end up paying less for services in general.

• Optimization of the maintenance cycle


Predictive analysis often shows which machines or parts require constant attention, which allows technicians to supply their tools and spare parts inventory, when necessary. This saves even more time, money and space. In some cases, machines can also perform self-maintenance. This further improves their efficiency by eliminating the need for certain types of technicians, making much faster and more punctual the maintenance routine.

• Strengthening of workplace safety


Another important benefit of predictive maintenance is its direct impact on worker safety. Equipment that is not adequately maintained or machines subject to malfunctions without warning represents a serious risk to the health and safety of production workers. Such circumstances can cause serious problems for workers. Furthermore, from a business point of view, they also cause damage in terms of time, productivity and profitability. Unexpected events of this type may require the entire enterprise to stop until the problem is correctly resolved.

These are just five ways that predictive maintenance with the IoT could change the manufacturing industry. During the times you could discover even more advantages that today are even difficult to imagine.

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