Machine Upgrading 4.0 – Breathing new life into your machinery: Challenges and opportunities

Machine Upgrading 4.0 – Breathing new life into your machinery: Challenges and opportunities

Nowadays, many companies are using industrial machines or installations that are several decades old. Often, these machines have not yet reached the end of their useful life, but they also no longer meet the current state-of-the-art in terms of intelligence or functionality. At some point, the question might come up: “Are we going to upgrade this machine or are we going to replace it?” As there are plenty of reasons to upgrade a machine, we want to demonstrate in this article that upgrading an old, outdated machine can be an interesting solution. Reasons for upgrading instead of replacing your machinery are:

  • Costs: Replacing a machine is typically more expensive than upgrading a machine.
  • Reliability: A new machine is not always better.
  • Training: People are used to operate the current machine. A new machine requires much more training.
  • Physical installation: Sometimes, machines are deeply integrated in a system or building, which makes it physically hard to replace it.
  • Environmental: Upgrading your machinery could avoid additional scrap that comes with a replacement.

Digital transformation in detail

The digital transformation of a machine in an upgrading process consists of different steps:

  1. Sensors: You need sensors that provide you with data to measure the necessary properties.
  2. Connectivity: You need to be able to access data that, often, are available on different locations.
  3. Visualisation: This provides insight in what is actually happening.
  4. Understanding: Why are the changes that you see happening?
  5. Prediction: When can I expect that changes will happen?
  6. Adaptation: How can I make an automated smart decision, keeping in mind that certain elements in the machine’s environment will change.

Key driving technologies behind any digital transformation are Data Analytics & AI and Digital Twins, which are all technologies that Flanders Make is actively working on.

Compressed air installation

CASE: GRADUAL DIGITAL UPGRADE OF A COMPRESSED AIR NETWORK

The Flanders Make co-creation office in Lommel is equipped with a 20-year-old industrial compressed air network that we use for testing and validating setups, climate chambers, fire shutters and general machinery such as tire changers, central trapping points, etc. However, over the years, several issues about this network have been reported. For instance, the air quality suffers from solid particles, moisture and oil. There also have been several maintenance issues such as leaks, pollution of filters, repairs, malfunctions, etc. In summary, we have an energy-consuming network that sometimes fails, causing problems to end users. To solve this, we decided to implement a gradual digital upgrade of our compressed air network.

1. Get your costs right: Collecting data

To start this process, we performed a cost-benefit analysis. For a simple case, you can simply look at the Return On Investment (ROI), or, on a longer term, at the Life Cycle Costs (LCC) or Total Cost of Ownership (TCO).

Gathering these cost data is often time-consuming and difficult as your machine might be 25 years old and you need to figure out not only the initial costs, but also operating costs, service costs, costs for training, for maintenance, software, spare parts, documentation, tools, disposal etc. All these costs must be taken into account, as this will result in a better analysis and, thus, a better decision. Luckily, most of the costs are often determined by only a few cost drivers.

It requires commitment to make an accurate cost-benefit analysis. Knowledge is often not stored in files, but in the heads of people that were involved in the purchasing or maintenance of the machine. Getting an accurate view on the costs can be challenging and is often not that straightforward. However, it is very important to be able to determine an appropriate upgrading scenario.

In general, you could say that there are 3 sources that you can use as input for your cost-benefit analysis:

  1. Expertise: For instance, someone’s experience with the number of machine inspections or the original purchase cost.
  2. Historical data: Costs that can be traced back in logbooks or administration, e.g. repairs, maintenance, downtime costs.
  3. Operational data: Costs related to the actual use of the machine, think of energy consumption, consumption profile, leakage, etc.

In our compressed air network case, we identified 3 main cost drivers:

  • Purchase cost:
    • We could easily determine this cost through the original invoices.
  • Maintenance cost: Determining the maintenance cost was a bit harder but we were able to do so as follows:
    • Maintenance and repairs: using old invoices in the maintenance logbook
    • Recurrent inspections: talking to our facility manager who was involved in different inspections and did regular inspections himself. Both the cost of inspections and his working hours had to be included.
    • Downtime cost: over the years, we experienced several breakdowns. To solve these, we rented a temporary replacement compressor. These costs also had to be included.
  • Energy cost:
    • The energy consumption was unknown. The main challenge was to get an estimate of the system’s energy consumption. Unfortunately, we did not have sufficient data to estimate the energy cost.

UPGRADE 1: ADDING SENSORS

Based on our cost-benefit analysis, we’ve defined three upgrading scenarios:

  1. No upgrading
  2. Upgrading the machine
  3. Purchasing a new machine

As we did not have any operational data to complete the cost-benefit analysis, we chose for an initial upgrade by adding extra sensors to get a better understanding of the end users’ operation. In this way, we would be able to obtain a better understanding of how our compressed air network is being used. The installed sensors included:

  • Current and voltage sensors to measure power consumption.
  • Pressure, temperature and flow rate sensors near the end users in the network.

After the installation of the sensors, we could start gathering data. Using a software framework, we pushed data through a MQTT broker to an influx database, where we stored the data. Subsequently, we used and managed these data through a Node-RED software layer, a low-code programming environment that allows to easily connect different data sources and to set thresholds, for instance.

Dashboard

These data were then sent to a dashboard that visualises the statistics of all different end users within our facility over a certain period. Pretty soon, the data in our dashboard led us to the following conclusions:

  1. Around 70% of the costs was associated with energy.
  2. We had a rather high idle consumption (around 10k€/year), mainly due to leaks in the network.
  3. We saw alternating periods of demand for compressed air. There were long periods with a very low demand, alternated by short periods with a very high demand.
  4. Finally, we have infrastructure that requires pressure all the time, so shutting the compressor down in low-demand periods is not an option.

UPGRADE 2: CHANGING THE PRE-SETS

Gathering, visualising and analysing these data was only the starting point. With the new insights about the energy consumption and usage profiles of the compressed air users, we were now able to perform a more accurate cost-benefit analysis to determine the most appropriate second machine upgrading iteration. Besides sealing existing leaks, we considered three different upgrading scenarios:

  1. No upgrading
  2. Upgrading scenario 1: Changing the active pressure pre-sets based on the end users’ operation and needs
  3. Upgrading scenario 2: Adding a small compressor for days with a low demand

By comparing these three options using a cost-benefit analysis tool that we had developed (including worst-case vs. best-case figures), we could estimate the costs up to 2025. The results were as follows:

  • No upgrading:
    • By 2025: k€19.3/year
  • Changing active pressure pre-sets:
    • By 2025: k€16/year
  • Adding a small compressor
    • By 2025: k€14.1/year

Kostoverzicht upgrades

Adding a small compressor would result in the lowest annual cost, but this solution would currently require a higher investment. Therefore, we decided to opt for the second scenario and implement active pressure pre-sets depending on the end users’ operation.

Lowering the pressure

The compressor was initially always running at a high pre-set pressure value. However, as this was only necessary in the short peak periods where demand was higher, an overall lower pressure would be a better choice. By gathering the pressure pre-sets over a one-year period, we saw that in 83% of the time a low pressure pre-set would be sufficient for our end users. In addition to lower energy costs, lowering the pressure would also cause less leakages. Therefore, we used an external interface to lower the pressure pre-sets in low-demand periods from 8 bar to 6.5 bar.

Overzicht vraag naar perslucht

HOW MUCH ENERGY DID WE SAVE WITH OUR UPGRADES?

As around 70% of our costs are energy-related, it was important to focus on lowering the energy consumption of our compressed air network. We achieved a lower consumption by:

  1. Sealing all leaks in our compressed air network: this reduced the energy consumption by 11 to 15%.
  2. Adapting the pressure pre-sets based on the end users’ operation: this reduced the energy consumption by 13 to 18%.

With these – all in all quite simple – measures, we were able to reduce the energy consumption of our compressed air network by 25 to 30%, resulting in a saving of +/- €4200/year by 2025.

Conclusions

If you have a similar case or are working with older machinery, it might be worthwhile to think about machine upgrading. If you consider this, we advise to:

  1. Start with a cost-benefit analysis;
  2. Involve your organisation in assessing the operational process: Getting the correct numbers is difficult. Good, educated guesses can come from any layer within your organisation. Also make sure you don’t forget the hidden costs!
  3. Follow a gradual digital upgrading approach. This will help you to:
    1. Get insights into your operations;
    2. Identify major cost drivers and opportunities;
    3. Reduce operating costs or enable new functionalities

Do you also want to give your machines a second life?

Would you like more information about Machine Upgrading or the possibilities for your application? Let us know!

Ted Ooijevaar, Onderzoeksingenieur

Ted Ooijevaar is a Monitoring Technology Domain Lead and Senior Research Engineer at Flanders Make since 2015. In this role he defines, leads and performs industry-driven applied research and development to support companies in the manufacturing industry. Ted received a PhD degree in field of Mechanical Engineering from the University of Twente and has special expertise in the field of sensing and monitoring, signal processing and data analytics, dynamics and mechanics, modeling and experimental testing.