Newsletter
5/2021
Efficient maintenance using digital support tools
What are the preconditions for successful application, and how will decision-making change?
Digitalisation and Industry 4.0 are on nearly everyone’s agenda throughout the cement industry. Particularly in the field of maintenance a huge number of different digital support tools can be found. Smart sensors and software tools are able to provide insights into equipment and its data like never before, and applications are also capable of predicting future occurrences. But using them is not simply a matter of “Plug-and-Play”. In order to really improve efficiency in maintenance and reduce costs, these tools need to be embedded into the plant’s maintenance strategy. On the one hand, preconditions like data availability need to be fulfilled, while on the other hand decision-making needs to be reformed with respect to the new tools available.
The condition of each piece of equipment in a plant can be monitored in every detail from anywhere in the world. Drones can take you into the depths of your kiln or your cyclone without any safety risks (Fig. 1). Anomalies that humans would most probably never have detected inside the process and machine data are automatically sensed by AI-based tools. Critical equipment failures are already predicted long before they occur, and the availability of the required spare parts is automatically checked. This vision of a “brave new world” in maintenance sounds almost too good to be true. So will digitalisation really change the way maintenance is organised in the cement industry?
![csm_Fig1_cr_db6d65a6fa.png](https://api.ecra-online.org/fileadmin/user_upload/csm_Fig1_cr_db6d65a6fa.png)
Figure 1: Drones can enable safe access, even to the inside of equipment
(Photo © Flyability)
Reliable data infrastructure
Data from many different sources such as process, machine, laboratory and of course maintenance data is currently digitised and interconnected for automated and efficient processing. A first and relatively simple way to increase efficiency through digitalisation is therefore to implement workflows with a high degree of automation based on this data. This may sound simple, but providing data from different sources, such as sensor data, spare part information or data on the availability of staff is just as difficult as ensuring connectivity across the whole plant. Powerful digital support tools only deliver their added value if the data infrastructure is available and reliable enough.
Preconditions for application
Although we talk about “digital tools”, these cannot just be simply plugged in, but need to be carefully integrated into the plant’s environment. The correct and sustainable storage of data is one of the key challenges of digitalisation. Digital tools providing new data need to be connected to one side of a data storage solution, whilst data-based tools need to be connected to the other side. But what is the right way to store data in between? What information is required besides an actual measurement and its timestamp? There is a need for machine-readable meta-data containing information on the data quality, the plant and equipment structure, the type of sensors and their calibration and ranges. There are many solutions for the gathering and evaluation of data. But many of these “black boxes” do not provide any insight into the data itself. Ownership of data and the possibility to share data efficiently through standardised interfaces is essential for the application of different digital tools in cement plants.
Data quality cannot however only be ensured by standards and storage. Required sensors need to be installed, calibrated and maintained. Alarms need to be set according to the specifications of the installed equipment, and they need to be updated anytime the equipment is changed. Finally, database information such as stock availability of spare parts also needs to be maintained. This requires time and effort. All the ‘brave new world’ benefits therefore come with a price to pay.
Data-driven decisions
Technically embedding tools into the plant’s data structures, ensuring data quality and directing alarms into the central control room or into the offices of the maintenance department is only half of the journey. The big question is how the provided data, and in particular alarms are handled from this point onwards. Ultimately, the software cannot fix the mechanical problem.
An example: A bearing is monitored with sensors for temperature and vibration. Both parameters increase slowly but steadily. An alarm is displayed on the CCR screen, on the maintenance manager’s tablet or an outsourced contractor’s. Will the alarm simply just be acknowledged? Who is responsible and who has which authority when such an alarm occurs? Will someone inspect the equipment? And will the relevant part be exchanged prior to a possible failure? There are no simple answers to these questions. It depends on the priority and system relevance of the machine. Furthermore, the availability of qualified maintenance staff (Fig. 2), the special tools required, spare parts and the downtime due to repair need to be taken into account.
![JUSX210816lhe.png](https://api.ecra-online.org/fileadmin/user_upload/JUSX210816lhe.png)
Figure 2: Software isn’t everything: Qualified maintenance staff are still required for repairs and on-site measurements
Digital tools will not automate decision-making. But they can provide more time for preparation, especially when possible failures can be detected before they actually occur. How to deal with alarms and how to integrate information from digital tools into decision-making and operating procedures needs to be defined before application. Once a system is bypassed and alarms are ignored, it will step by step lose acceptance and may soon be switched off. It is therefore essential that the staff involved can see the benefits so that they start working with the system and also invest the time necessary to keep it running.
Conclusion
Digital support tools show great potential for improve maintenance in the cement industry and reducing costs. But before these tools can be applied, the preconditions – technical and organisational – as well as their integration into decision-making processes need to be reviewed. Real acceptance and actual integration into decision-making can only be built up through reliable and trustworthy applications. And reliability requires high data quality and updated settings right from the start. On this basis, many tools have already proven to be successful.
But despite all the great tools available, one should never underestimate the power of human “sensors” and natural intelligence. By going into the plant, watching, listening and going with your instincts, many problems and their root causes can be detected very efficiently. It is therefore still necessary to find the right balance between digitally supported and “old-school” maintenance.