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With Orchestra to fail-safe Production

Predictive maintenance is one of the most commonly used form of use cases in the age of Industry 4.0 – and an important step towards the smart factory and IoT. The maintenance of machines and factories should never no longer be limited to preventing failures of a production level. Advanced analyses and the anticipation of faults stretch the maintenance intervals, increase the uptime of a machine and thus the productivity of factories go up to 20% in the ideal case. The enormous added value that can be generated by predictive maintenance is versatile and extremely relevant economically.

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Predictive Maintenance:
Explanation and Examples


Predictive Maintenance is the term for anticipatory (= predictive) maintenance and servicing.  All the machine and process data is taken into account in real time. Such as service life, wear, load, external circumstances, and empirical values.


Based on this, measures are suggested, planned, and implemented before damage occurs – but not before the intervention is necessary.  Consequential damage is also prevented by Predictive Maintenance. In short, machines are repaired in good time before they break down.


This Predictive Maintenance is based on the evaluation of process and machine data and also uses valuable data on Overall Equipment Effectiveness and Condition Monitoring.  So, the first step is to make production data from machines and factories available.


In Industry 4.0 Predictive Maintenance, data is enriched into valuable information and used to forecast future maintenance cycles to proactively maintain factories and avoid downtime.


With Orchestra Predictive Maintenance software, you harness the power of data and get the optimal running machine that never stops.

Why Predictive Maintenance and Planning are important for successful production

Classic maintenance cycles according to fixed intervals with static procedures are no longer up to date – they are error-prone and can cause high costs or, in the worst case, failures. Preventive Maintenance provides companies with advanced insights: What will happen and when?

Let your data flow

To implement Predictive Maintenance in the best possible way, it’s necessary to process huge amounts of data on the status of individual machines and systems as well as significant environmental parameters such as humidity and temperature. Under certain circumstances, this data is available in a multitude of different formats and protocols.


To cope with the flood of data, an essential task is to incorporate human knowledge and experience into the technical implementation.

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Fabrik im Daten Dschungel mit Fluss

Challenges of Industry 4.0 for Predictive Maintenance

  • Large amounts of data must be collected, provided, and analyzed.
  • Plant-specific knowledge must be consulted.
  • Data must be interpreted correctly.
  • Knowledge from different disciplines (IT, engineering) must be combined to enrich data and generate information from it.

The technical infrastructure (data integration) as well as the professional expertise for this is provided by the industrial software from soffico: The Orchestra Industrial Suite.

Werksmitarbeiter installiert Technik

Disadvantages & Advantages of Predictive Maintenance – When is it worthwhile?

If you don’t shy away from the initial “Big Data” flood in your production and are ready to evaluate it with professional Data Analysis into valuable information and knowledge about your own production processes, you will secure huge production advantages for yourself:

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Predictive Maintenance avoids unplanned downtime or machine failures caused by defective machines and equipment.

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Maintenance personnel can also be deployed more effectively thanks to Predictive Maintenance.

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The procurement of spare parts becomes more plannable for a company and is automated when required – this minimizes organizational effort and storage costs.

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Ultimately, productivity is also improved: With the help of the data obtained, processes and the performance of the company’s own factory and machinery can be optimized.

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The Predictive Maintenance approach thus saves costs compared to routine or time-based preventive maintenance strategies because maintenance is only performed when it is necessary – but in a timely manner to prevent failures.

Success and Benefits of the Maintenance Strategy in figures:

10 – 20%

extended uptime

5 – 10%

reduced maintenance costs

20 – 50%

less planning effort for maintenance

Predictive Maintenance with soffico:
Your Data Provider for Reliable Predictive Maintenance

You have decided to increase the service life of your equipment in the long term through timely maintenance? Our Orchestra Alerting / Monitoring System informs responsible personnel about the measures to be taken – immediately and automatically.

Orchestra enables Industry 4.0

But with industrial software from soffico, you get much more: Orchestra not only delivers relevant data from your machines and forms the right integration architecture for your fail-safe production – but we also have our experts support you in semantic interpretation on site to translate the data from your machines into profitable information.

Our low-code middleware software, the Orchestra Industrial Suite, ensures that the data is always reliably, and available in the right place. We provide your Predictive Maintenance system with the data that your experts know they need.

Straight to the Solution

Orchestra for OT

Get all the other Benefits of Orchestra as well: 


Future proofing

Data security

Transparency & data sovereignty

Investment protection

Stability & Reliability


Do you have questions?

We are happy to help you with a personal discussion.

Talk to our Experts

Sarah Blomeier. Ihr Ansprechpartner für alle Themen rund um Orchestra.