The time for industrial IoT is now – how to collect and interpret relevant data?

The internet of things (IoT) and Industry 4.0 are more than hyped-up marketing terms, however oversaturated they may be at this point. We can be certain that industrial operators are expected to better exploit data for the competitive advantage alone.

The digital transformation of industry has introduced immense opportunities for collecting data, and IoT solutions allow data to be collected from nearly all stages of production processes. Data goes beyond just figures – it is fuel for decisions, maintenance and optimisation.

So how can we make sure that data is useful for your company’s management and the key persons throughout your organisation? And how can IoT be used to achieve a competitive advantage? Read more in this article.

The challenge for industrial companies is less the acquisition of data and more how to be agile in its use throughout the different departments of the organisation.

As artificial intelligence advances, IoT solutions can go beyond tracking figures and open up opportunities for control, management and optimisation. It follows that your organisation’s departments should have good lines of communication.

For IoT purchases, your organisation should consider the following as early as possible: 

• What data is desirable to collect and for whose needs?
• Can the data be communicated reliably between IT and OT?
• How is your organisation’s information security?

We can also help you with your initial specification – our experts support the implementation of IoT solutions all the way from the design stage.

Common IoT solutions include remotely read energy meters, for example, but the largest implementations form complex control system.

Savings and optimisation

• Saving energy with IoT is becoming the rule, not the exception. Here the key components are remote monitoring and real-time energy consumption measurement.
• The process industry can use the additional data to optimise production and save costs thanks to higher plant efficiency.
• Advances in machine learning and artificial intelligence bring new opportunities for product development and optimisation.

Maintenance

• Preventive maintenance. Machine components may show early signs of wearing out, which can be used to prevent expensive repairs.
• Easier maintenance. Machines can be monitored and operated remotely, and the cause of a fault may be discovered instantly, avoiding an unnecessary service call.
• Real-time data on deviations in consumption, for example, expedites maintenance tasks.

Completely new business opportunities

• Machines can be commissioned remotely, which is especially valuable in international operations.
• Supplying machines as a service is increasingly common and adds a competitive advantage. 
• Manufacturers can collect valuable data about machine use for further development, updates, and more. In addition, the data can also indicate abuse, which helps determine responsibility and resolve warranty cases, for example.
• The end customer benefits from a direct view into the workings of their machine or device. 

Further reading:

The opportunities and challenges of the internet of things are intertwined: enormous volumes of data are collected, but how can we refine it into something useful?

The following can help you exploit data:

• Data visualisation. Once visualised, data is easily transferred to any device from computers to smart watches, including websites and browser-based web services.
  Correctly targeted data views for different groups from management to maintenance. Field workers do not need the same data as executives, for example.
  Machine learning opportunities. First, we have to understand a machine’s normal operation to then detect deviations that could indicate a need for maintenance and how best to handle it. Here our experience of the machine’s operation and the organisation’s internal dialogue are key: what data are we looking for?
• Combining data from different sources. For example, if the devices in a factory hall come from 20 different manufacturers, each manufacturer probably has their own protocol for collecting data, so the data should be collected flexibly without creating an excessive workload. In many cases, this can be done by compiling the data into one whole, which could even be defined as a company standard for future purchases.
• We provide solutions for collecting and compiling data from different devices and transferring the data through gateway devices. The data can also be transferred externally with the proper remote connections and information security.
• Data-based analysis of machine operating conditions and functioning.  Data about the ways and conditions in which a machine is used can be useful for product development. Real-world usage data allows machinists and manufacturers to improve the performance and reliability of their machines.

When talking about the opportunities of IoT, one of the major trends is the Machines as a Service or MaaS model. It is estimated that by 2030, most machines will be purchased on a subscription basis instead of as conventional deliveries. 

In the MaaS model, the buyer pays a monthly fee that includes maintenance, servicing and monitoring for the machine. The advantages are lower risks and capital costs with a higher certainty of machine reliability. The origins of the MaaS model lie in consumer sales where streaming services are replacing conventional products.

For machine manufacturers to reap the benefits of this sales transformation, they should look to IoT solutions. Remote control, update capability and operational flexibility are expected by default from machine manufacturers in the future.

It is also important to understand customer needs and how their organisation can use data, for example. Therefore, Industry 4.0 not only transforms device sales, but also enhances customer service.

The use of IoT in industry is becoming commonplace, but now the challenge is producing data that is suitable for the different levels of each organisation.

• Exploiting vast data volumes requires advanced analysis services and data visualisation.
• Artificial intelligence is improving analytics, preventive maintenance, self-regulation, and custom experiences, but may involve ethical and information security challenges.
• The potential of IoT solutions in process industry can be found in process optimisation, performance improvements, and energy savings.
• The smart Machines as a Service model is transforming the future of machine manufacturing.

Custom IoT solutions for your industrial company

Would you like to use data safely and effectively? 

We provide a full range of software and other tools for deploying and using the industrial internet. Our service combines deep knowledge of machines and mechanical engineering with IT expertise.

• IoT consultation. We are a partner to industrial companies of all sizes who wish to exploit the opportunities created by IoT in their business.
• Secure remote connection solutions with MB Connect Line products. Learn more:  Secure Remote Access MB connect line.
• Data collection and compilation via gateway devices for transfer to cloud services and more. Learn more: Redlion -ratkaisut ja ohjelmistoratkaisut.
• Data visualisation, analysis and imports to any platform with Iconics solutions. Learn more:  Iconics.com ja tiedon visualisointi.

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