With the Fourth Industrial Revolution, many small companies and start ups appear with much more affordable, much cheaper technology and start deploying data collection architecture in all types of large, medium and small companies and start providing services to companies that previously could not afford it.
In this second installment of the interview with Diego Galar, expert in Industrial Preventive Maintenance, Professor of Condition Monitoring at Luleå Tekniska University in Sweden, and senior researcher at Tecnalia, we delve into the changes that technology has brought in the world of maintenance not only at the level of processes and organization but also at the level of new business models. If you have not read the first part of this interview, in which we talk about the evolution of Industrial Preventive Maintenance, you may be interested in reading it. here
The pace has changed in the sense that 25 years ago a telecommunications engineer profile was rare in maintenance and now it is rare not to have Telecommunications Engineers or Data Scientists. The profile in the Industrial Preventive Maintenance plants has changed and the business model has also changed a lot.
In general, in society we do not want to do Industrial Preventive Maintenance. When we buy an asset, we want to buy the function of the asset and have someone else take care of the maintenance. And this makes all the sense in the world, because assets have evolved a lot, they are complex assets and a company, no matter how big it is, cannot have specialized Industrial Preventive Maintenance personnel in all the technologies on the market.
For example, when you buy an electric turbine, it is logical that the manufacturer carries out the maintenance, because he is the one who knows the equipment, who provides the spare parts and also now with the connected industry, he is the one who can monitor the turbine in real time. And this is not new, turbines for example have always been closely monitored, as well as aircraft engines. It has been the manufacturers Rolls Royce or General Electric who have taken over the Industrial Preventive Maintenance. What has changed is that this business model, which was not extended to the rest of the assets, has now been extended.
At the individual level, we see it when we buy cars in the form of leasing or renting, we want a courtesy car so as not to lose the value of the asset's function. What we do not want is to be aware of Industrial Preventive Maintenance because it takes time away from our core business.
And in this sense, I remember a phrase of the then president who said President of General Motors in the 1990s, It was a premonitory phrase of what was going to happen later on. At the time, General Motors had more than 800 maintenance staff. I remember that in a factory we could have 8 - 10 types of programmable controllers and you had to have programmers for the 8 and 10 types of controllers and if you had Siemens, Matsushita or Omron PLCs it was a mess.
Now we see business models where you buy final welding hours and you don't buy the ABB robot, and it is quite normal that this maintenance as a service model has its place and maintenance goes back to the manufacturer. And this is where I am finding the change in both the business model and technologies.
It is not the same to deploy technologies to the end user, who does not want the machine to stop, as it is to deploy technologies from the design and manufacturing concept to make that asset more reliable, more predictable and also remotely monitorable.
In this case the pace has changed and will change even more, the heads of Industrial Preventive Maintenance will eventually be managers of insurance, contingency policies and will not be technologists and manufacturers will be the ones to provide the embedded technology when the time comes.
Diego Galar Pascual
Until recently data was gold and now we don't say data is gold but information is gold, I have a lot of data but you have to know how to dig into the data to extract information. And in this sense we have seen many companies come to the surface that have come to replace or complement what the big companies used to do.
The industrial landscape used to be very simple. We had the big OT operators and the big IT operators. At the OT level we had the big automation players such as Siemens, AB, etc... and then the big IT players at the Industrial Preventive Maintenance level, which were the big CMMS manufacturers, the IBMs of Maximo or other suppliers, and between them they shared the market.
However, with the Fourth Industrial Revolution, many small companies and start-ups are coming up with much more affordable, much cheaper technology and are starting to deploy data collection architecture in all kinds of large, medium and small companies and are starting to provide services to companies that could not afford it before.
When you talk about an Emerson or a Siemens, in general these big companies talk to other big companies and SMEs were left out of this digital game. Now, however, with the advent of Industry 4.0 , access to technologies has been democratised. An IoT device is affordable and cloud analytics is affordable and you can afford to do a lot of things.
In other words, there are many companies that don't want to buy hardware or software and what they want is to have their data read. They pay to be alerted when their machine has a problem, so suddenly there are a lot of small companies providing this type of service, and it has radically changed the landscape.
Companies do not have a traditional single supplier serving all technology but have a miscellaneous model supplier of different hardware, software and services.
However, we must also bear in mind that there has been an attempt to create open architectures that have not managed to take off, in my opinion, because the large companies continue to maintain their market shares in a very important way. They have continued to keep the client captive and this has meant that services for SMEs have often not been developed as well as they could have been. One exception, or an initiative that I like very much, is the German initiative GAIA-X in which a cloud with accessible services for SMEs has been developed.
All this constellation of companies that have come to help a lot to the Industrial Preventive Maintenance teams, have changed a lot the business models in the sense that the companies now do not sell the asset but the service and therefore have to change their financial model. Let's remember that a leasing model is not a sales model and at a financial level it is a very painful model.
When you sell a train, for example, you get paid a few million euros, when it is a leasing model, the initial investment is yours and you recover it little by little. It is a financially painful model that requires a tremendously robust Industrial Preventive Maintenance, from design and manufacturing. That is to say, to sensor much more your asset in design because the penalty clauses that you have in your leasing are very harmful if the asset breaks down from time to time.
So a lot has changed in the business in the sense that large manufacturers have also surrounded themselves with many small companies and new business models, which help them in the reliability of these assets that are commissioned through renting or leasing.
I would say that the model has become very fragmented, we now have a lot of service providers, hardware, software, data and information, in addition to the big companies, and this means that companies have much more choice, although for me both open standards and total democratisation have not been a success so far, because I think that many SMEs have not yet had the opportunity to access the great advantages offered by 4.0 technologies.
If you were interested in this installment of the interview, we encourage you to read the third part of the interview on Predictive Maintenance in the Cognitive Industry