The use of IoT technologies in industrial maintenance management enables the scheduling of necessary interventions to minimize production breakdowns.

With the help of preventive and predictive maintenance, it becomes possible to achieve significant benefits in terms of cost reduction and industrial production efficiency by minimizing maintenance interventions.

Are you eager to learn more about the potential of maintenance management from a 4.0 perspective? Read on!

What are predictive and preventive maintenance?

In recent times, there has been growing interest in the market regarding the adoption of predictive, preventive or condition-based maintenance software. These technologies are revolutionising the industry and radically changing the way companies manage and maintain their industrial plants.

Thanks to maintenance software, companies can constantly monitor the condition of their equipment, predict faults and malfunctions, and plan maintenance work quickly and efficiently.

Everyone talks about preventive and predictive maintenance, but few know their benefits and, above all, the differences between the two. Let’s explore them together.

Predictive maintenance is one of the most widely used technologies in Industry 4.0. It enables the prevention of failures before they occur and the development of optimisation strategies based on the collected data.

Preventive or planned maintenance, on the other hand, is performed on the basis of predefined scheduled intervals, while condition-based maintenance is carried out after a decline in the condition of the monitored machinery has been observed.

Italy towards maintenance in the era of Industry 4.0

Italian companies are starting to implement preventive and predictive maintenance techniques as part of their Industry 4.0 strategy, but the deployment of these technologies varies by sector and company size.

Large Italian companies, such as those in the automotive, mechanical engineering, or power generation industries, are already using IoT technologies for predictive and preventive maintenance, thereby achieving efficiency, reliability and cost reduction benefits. 

However, many Italian SMEs are still struggling to implement these technologies due to high costs and a lack of technical expertise, which makes the process of data collection and analysis complicated. 

But what are the main reasons why companies decide to adopt predictive maintenance techniques? There are several underlying motivations, including the need to avoid downtime and production losses, to increase production efficiency, to decrease component replacements and to improve overall production quality.

Fig.1 Reasons to use predictive maintenance

How to improve industrial plants’ efficiency?

Maintenance management is increasingly important to maximize production efficiency and minimize costs, which is why many companies decide to invest in predictive/preventive maintenance software.

Predictive and preventive maintenance software is essential for determining when maintenance is needed in order to reduce breakdowns and downtime. This allows for addressing various needs, such as:

  • Minimizing unexpected downtime
  • Reducing false rejects
  • Improving the productivity and performance of both legacy and modern machines across different plants.

Zerynth and Safetykleen: the combination of IoT and parts washing

In collaboration with Safetykleen, a company with strong experience in the industrial washing and surface treatment sector, Zerynth proposes a solution for real-time machinery monitoring and predictive/preventive maintenance in order to schedule timely maintenance interventions, and avoid machinery downtime, minimizing unnecessary interruptions.

With the Zerynth/Safetykleen solution, companies can reduce energy consumption by around 40% and improve machinery performance by 15% through reduced downtime. If you would like to learn more, here is the link to the white paper written in collaboration with Safetykleen.

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About the Author: Alice Benozzi

Alice Benozzi
Alice is part of Zerynth’s marketing team. She has a degree in Marketing Management and is passionate about digital innovations. She likes creating new content for social networks and blogs. In her free time she loves to travel.

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