The wonderful thing about community is knowing you’re not alone. Knowing that people like you are going through the same things that you are. And that there’s hope.
In the first of a series of spotlight interviews, our Community Lead, Paul McMillan, caught up with SMDH community member Tiago Teixeira.
A chartered engineer by background, data is firmly on Tiago’s mind. And, whilst he’s brimming with excitement about the potential for data, he knows the challenges SMEs face. The absence of decent data collection systems and the data skills gap can make things tricky.
But that hasn’t held Tiago and his business back. He’s confident that by working together as a community, upskilling employees and embracing the potential of data, SME manufacturers can use data to unlock incredible opportunities for growth and success.
I’m Tiago Teixeira - a Chartered Engineer with the Institute of Materials, Minerals & Mining, with a background in materials science, specialising in data-driven decision-making and leading impactful engineering projects.
I began my academic journey at the Engineering school of the University of Porto in Portugal, where I specialised in Materials Engineering. My master's thesis, developed at Castle Precision in Glasgow, Scotland, focused on the practical application of Lean Manufacturing in SMEs.
Professionally, my path has been varied. I started as a Researcher with Edinburgh Complex Fluids Partnership at the School of Physics in Edinburgh. From there, I moved to Micross Components as a Materials & Project Engineer. For the past five years, I've been with Impression Technologies Ltd (ITL), working as a Senior Engineer – Process Technology for the last two. In this role, I've concentrated on data analysis, process improvement, and leading key engineering projects to support the development of HFQ technology, a specialised hot forming aluminium process.
This position has allowed me to refine my skills in SQL, Python, and statistical modelling, applying them to real-world challenges. One of the significant projects at ITL was our digital transformation initiative. With support from Made Smarter West Midlands, I led ITL's first digital transformation project. This project aimed to enhance our data analysis capabilities, standardise data collection across our processes, and provide better insights for process improvement. The success of this project not only improved our data analytics but also set the stage for developing machine learning applications from our data to support our technology's growth.
To further my skills in data, I've started a Level 7 course in Artificial Intelligence and Data Science. I've always been passionate about data analytics and data science, and I'm excited to continue learning in this area.
Outside of work, I enjoy spending time with my dog. I've also recently started learning the piano, though I must admit, solving engineering problems still feels a bit more familiar!
Digital transformation throws up a couple of challenges for SMEs. The first is the lack of strong data collection systems. Many manufacturing businesses expand without initially focusing on a data strategy. It’s an aspect that’s often overlooked in the early stages of setting up. So, when businesses want to get into digital manufacturing, they realise they don’t have the access to their data, not enough data or lack high-quality data.
This means businesses need to invest in data infrastructure, data collection systems and implementation of new processes. Following that, there’s a skills gap. Engineers, while excellent in their domain, often aren’t familiar with data science. Meanwhile, many software engineers and data scientists might not have the minimum engineering knowledge to deliver these projects. So, there is a real demand for engineers who can cover both areas, that are capable of leading multidisciplinary teams to deliver digital manufacturing solutions.
Addressing these challenges requires the industry to foster greater collaboration and to actively seek advice from expert groups and communities. Upskilling engineers is critical, and initiatives like Made Smarter are pivotal in driving this change. Communities like this one play a vital role, offering platforms where we can share experiences, debate challenges, and collectively learn.
It is crucial for us to demystify digital manufacturing. While these projects often come with significant costs, businesses don’t need to overhaul every department simultaneously. When considering digital solutions, two guiding principles should be at the forefront: “keep it small” and “plan for the future”. Small, strategic investments can yield significant benefits, especially when data is collected from critical stages of the process. However, it’s equally essential to consider future data needs.
Solutions should be scalable, allowing businesses to expand organically without the need to rebuild their systems with every step they take. This highlights the importance of crafting a robust data strategy that is in sync with a company’s business goals.
As a Senior Engineer at Impression Technologies Limited (ITL), I was responsible for delivering our shift towards digital manufacturing. We’ve recently completed setting up our foundational data infrastructure. This first phase saw changes implemented on our shop floor, from the installation of track and trace systems to integrating equipment with our data capture PLCs. Additionally, we developed the required infrastructure to centralise all this data into a database that is continually updated in real-time, laying the groundwork for our next steps in data science and the continuous development of our core technology.
Our attention is now turning to how we can leverage our enhanced data capabilities to support projects that delve deeper into the Hot Form Quench (HFQ) technology that ITL pioneered. The idea of integrating advanced data analytics tools to refine the HFQ process is incredibly engaging. This is a particularly exciting time at ITL as we further navigate our data-centric journey.
I’ve recently started a government-funded Level 7 course in Artificial Intelligence and Data Science. Spanning 24 months, this course provides an in-depth look into Machine Learning and AI. It’s a challenging programme but has been invaluable in helping me build on my understanding of machine learning tools and explore more advanced methods. If you’re not quite ready for such a commitment, the Smart Manufacturing Community offers an excellent starting point. Here, you can read about real-world engineering challenges and connect with IT providers who you can potentially guide and collaborate with you. Additionally, I would suggest checking out blogs like ‘Towards Data Science’ which regularly posts short and insightful articles on data science topics.
I joined The Smart Manufacturing Community to connect with others in the field, share what I know, and learn more about industry trends. To me, communities are vital. They encourage teamwork, shared learning, and help all of us grow together.
As a Senior Engineer at ITL, I’ve been at the forefront of our digital transformation journey, delivering foundational changes in data infrastructure and actively working on the integration of advanced analytics tools. Through this experience, I can offer insights into the practical aspects of implementing digital solutions in an SME context. My experience delivering track and trace systems, PLC integration, and centralising data can be helpful for members seeking guidance in similar domains. Beyond technical advice, I’m keen to share our learnings about project management, stakeholder engagement, and aligning technology projects with broader business objectives.
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