Tag: predictive maintenance

a futuristic factory floor, highlighting the seamless integration of artificial intelligence and the Internet of Things within manufacturing
Supply Chain, sustainability

Revolutionising Manufacturing: AI + IoT = The Sustainable Factory of Tomorrow

In the rapidly evolving landscape of modern manufacturing, the convergence of artificial intelligence (AI) and the Internet of Things (IoT) is not just a trend—it’s a transformative movement. As host of the Sustainable Supply Chain Podcast, I’ve had the privilege of engaging with leading voices in this revolution. A recent discussion with Bryan Merckling, CEO of Thinaer, offered profound insights into how AIOT (the amalgamation of AI and IoT) is redefining efficiency, reducing waste, and paving the way for a more sustainable manufacturing industry.

The AIOT Advantage

The power of AIOT lies in its ability to make manufacturing processes smarter and more connected. By integrating AI’s predictive analytics with IoT’s network of sensors and devices, manufacturers can achieve unprecedented levels of operational efficiency. For instance, predictive maintenance, powered by AIOT, can forecast equipment failures before they occur, significantly reducing downtime and maintenance costs. According to a study by Deloitte, predictive maintenance can decrease maintenance costs by up to 10% and increase equipment uptime by up to 20%.

Moreover, AIOT enables real-time tracking and monitoring of assets, from raw materials to finished products. This visibility not only enhances supply chain efficiency but also contributes to a substantial reduction in waste. By precisely tracking inventory and production processes, companies can minimize overproduction and surplus inventory, two major sources of waste in manufacturing.

A Leap Towards Sustainability

Perhaps the most compelling aspect of AIOT is its potential to drive sustainability in manufacturing. The industry, historically known for its significant environmental footprint, is under increasing pressure to adopt greener practices. Here, AIOT emerges as a potentially powerful solution. By optimizing energy use and reducing waste, AIOT technologies can significantly lower the environmental impact of manufacturing operations.

One striking example shared by Merckling involves the use of energy-efficient sensors that monitor and optimize energy consumption across manufacturing facilities. These sensors can lead to a considerable reduction in energy waste, aligning manufacturing practices with sustainability goals. Additionally, the advent of battery-less sensors, powered by ambient energy, marks a significant step towards reducing the environmental burden of sensor technology itself.

The Road Ahead

The journey towards a sustainable manufacturing sector powered by AIOT is both exciting and challenging. Implementing these technologies requires not just significant investment but also a cultural shift within organizations. Manufacturers must embrace innovation and be willing to experiment with new approaches to production and operations management.

The potential rewards, however, justify the effort. Beyond operational efficiency and sustainability, AIOT can enhance product quality, improve worker safety, and open new avenues for innovation. As the technology matures, we can expect to see even more creative uses of AIOT, further cementing its role in the future of manufacturing.

A Call to Action

For industry professionals, the message is clear: the time to act is now. The convergence of AI and IoT offers a unique opportunity to reshape manufacturing for the better. It’s an opportunity to drive efficiency, foster sustainability, and create a more resilient and flexible supply chain.

If you’re intrigued by the possibilities of AIOT in manufacturing and keen to delve deeper into this topic, I encourage you to listen to the full episode of the Sustainable Supply Chain Podcast with Bryan Merckling. Gain insights from a leader working in this space, and discover how your organization can work towards a smarter, greener future.

In embracing AIOT, we’re not just transforming manufacturing; we’re taking a significant step towards a more sustainable world. Let’s lead the charge together.

Safety First sign
Digital Supply Chain

AI is Revolutionising Safety: How AI and Tech are Saving Lives in the Industrial World

In the latest episode of my Digital Supply Chain podcast, I had the privilege of speaking with Maurice Liddell, a principal with BDO Digital. This was not just another conversation about AI and technology; it was a deep dive into how these powerful tools are transforming safety and operational efficiency in workplaces today.

One of the most riveting parts of our conversation was when Maurice painted a vivid picture of how technology could prevent life-threatening accidents. Imagine a foundry worker, falling off a scaffolding towards a vat of molten metal. Now imagine if AI could dynamically deploy a safety net to catch that worker in real-time. Sounds like something out of a science fiction movie, right? But it’s not—it’s the future of industrial safety, and it’s closer than you think.

Maurice also raised some thought-provoking questions about ethical considerations when deploying AI. He said, “We have to be conscious about the information that we’re feeding [AI] and making sure that we are not introducing our own biases into it.” It’s a pertinent point, especially when AI models are being used to make hiring decisions and other critical organizational moves.

Another highlight was discussing the role of large language models like ChatGPT. “These models can speak not just English, but any language you throw at it pretty much, making workers in diverse environments feel more comfortable,” Maurice added. As someone who was pleasantly surprised to see ChatGPT respond to my message in Irish, I couldn’t agree more!

What made this episode truly special was Maurice’s insight that safe workers help maximize profits. He dismantled the false dichotomy between safety and profitability, urging companies to invest in technology not just to prevent incidents but to enable predictive and preventative maintenance. It’s not “people or profits,” it’s “people for profits,” and AI technology is a core component that can help make it happen.

To wrap up, if you’re passionate about AI, committed to creating safer, more efficient workplaces, or just a curious mind looking to know where the future is headed, then you won’t want to miss this episode.

If you enjoyed this episode, please consider following the podcast and sharing it with others who may be interested. And as always, if you find the podcast of value, and you’d like to help me continue to make episodes like this one, you can go to the podcast’s Support page and become a Digital Supply Chain podcast Supporter for less than the cost of a cup of coffee!

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Thank you!

Kuka manufacturing robot
Internet of Things (IoT)

How the Internet of Things Can Make Your Manufacturing Business More Sustainable

The Internet of Things, often abbreviated as IoT, refers to the network of physical devices, vehicles, home appliances, and other items that are embedded with electronics, software, sensors, actuators, and connectivity which enable these objects to connect and exchange data.

The Industrial Internet of Things, or IIoT, is a specific application of the Internet of Things that pertains to the manufacturing sector. In recent years, sustainability has become an important issue for manufacturers as consumers increasingly seek out products that have been made sustainably and with minimal impact on the environment.

Fortunately, the IIoT can help manufacturers reduce their environmental impact and become more sustainable. Here’s how:

  1. Collecting Data to Increase Visibility and Transparency Across the Value Chain
    The first step to becoming more sustainable is to have visibility and transparency across the entire value chain. This means understanding where your raw materials come from, how they are sourced, how they are used in your manufacturing process, what happens to your finished products after they are sold, etc. In order to gain this visibility and transparency, manufacturers must collect data at every stage of the value chain. This data can be collected manually or automatically through sensors and other digital technologies. Once this data is collected, it can be analyzed to identify areas where your company can become more efficient and reduce waste.
  1. Connecting Machines to Improve Efficiency
    One way that manufacturers can use the IIoT to become more sustainable is by connecting their machines together in order to improve efficiency. For example, if one machine is idling while another machine is overloaded, this presents an opportunity to optimize production by redistributing work among the machines. By connecting machines together and using data analytics to optimize production in this way, manufacturers can avoid wasting energy and resources.
  2. Using Renewable Energy Sources
    Another way that manufacturers can use the IIoT to become more sustainable is by using renewable energy sources such as solar or wind power instead of traditional sources such as coal or natural gas. While renewable energy sources may have been more expensive in the past, advances in technology have led to a decrease in cost while simultaneously increasing efficiency. As a result, many manufacturers are making the switch to renewable energy sources in order to reduce their environmental impact.
  3. Implementing Predictive Maintenance Schedules
    Predictive maintenance is a type of maintenance that is performed before problems occur. This is in contrast to traditional preventive maintenance which is performed on a regular schedule whether or not problems exist. By using predictive maintenance schedules based on data collected by sensors, manufacturers can avoid unexpected downtime due to equipment failures. In addition, predictive maintenance can help extend the lifespan of equipment which leads to fewer replacement cycles and less waste over time.

The IIoT offers many opportunities for manufacturers to become more sustainable businesses. By collecting data across the value chain, connecting machines together for improved efficiency, using renewable energy sources wherever possible, and implementing predictive maintenance schedules; manufacturers can reduce their environmental impact while simultaneously improving their bottom line. As consumers increasingly seek out sustainable products, there has never been a better time for manufacturers to take advantage of these opportunities presented by the IIoT .

Italy's Fecciarossa 1000 high speed train
Internet of Things (IoT)

Italy’s train operator invests big in IoT

TrenItalia has invested €50m in an Internet of Things project which it expects to cut maintenance costs by up to €130m anually, to increase train availability, and improve customer satisfaction ratings.

There is a lot of hype around the Internet of Things (IoT) these days, so it is refreshing to see an IoT story with some real traction (terrible pun, sorry!).

TrenItalia, the primary train operator in Italy, and SAP had a big launch event recently to announce a partnership whereby TrenItalia are using SAP’s IoT technology to help manage the maintenance of the TrenItalia fleet.

TrenItalia operates around 8,000 trains per day, which is in itself, no mean feat. However, it wanted to make its service even more efficient so it looked to the Internet of Things to help.

Historically maintenance on trains was scheduled based on how long the train was in service, how many kilometers it had travelled, or if a failure ocurred, and as a consequence many times the maintenance happened before it was needed.

Trains have had sensors installed for some time now, however typically they wrote their data to log files which were examined at the journey’s end. With the new Dynamic Maintenance Management solution (DMMS), TrenItalia is deploying sensors on all its trains to report back detailed data on the trains’ performance in realtime. The data is used to track where the trains are, to schedule maintenance when it is actually needed, and to increase the safety, and reliability of the entire locomotive fleet.

The trains have between 500-1,000 sensors capable of generating up to 5,000 data points per second measuring variables like motor temperature, line voltage, and braking effort. This data is transferred to TrenItalia’s 6 terabyte in-memory database, and can be stored ultimately in their 1 petabyte cloud storage facility.

The cost of the project to TrenItalia is €50m, which may sound like a lot, but according to TrenItalia CIO Danilo Gismondi, they expect the solution to save them between €104m – €130m per annum (8 – 10% savings in the annual maintenance budget of €1.3bn). There are also savings of an estimated €10-€20m from not having to pay fines and penalties to customers and regulators associated with train failures and delays.

Apart from the financial savings, other benefits of the solution include:

  • a reduction in the unplanned unavailability of trains (leading to a 5-8% increase in train availability)
  • a reduced stock of spare parts
  • a reduction in the amount of time locomotives spend in maintenance and
  • a realtime look into the status of the entire TrenItalia fleet with the ability to be alerted to issues on any one individual locomotive before problems arrive

At €50m, this is a significant outlay for TrenItalia, but they are now battling against competitors on many fronts (air travel, buses, and even ride-share schemes like Uber). Knowing this, a big motivator for TrenItalia’s undertaking the project was to increase customer satisfation ratings. As TrenItalia CEO Barbara Morgante put it

Customers have to choose us because we’re better than others

The transformative nature of the Internet of Things should not be underestimated. With this one solution TrenItalia is saving over €100m a year, it is increasing the safety and reliability of its trains, and it is providing a better service for its customers.