Smart manufacturing: what really matters when making it ‘smart’?

Posted on 20 Mar 2024 by The Manufacturer

Smart manufacturing represents a pivotal shift in the manufacturing sector, driven by the urgent need for digital transformation. It's not merely an option but a necessity for manufacturers to adapt to survive and thrive. Damien Fellowes, Manufacturing Practice Lead EMEA – Stibo Systems explains more.

If manufacturers don’t adopt it, it is certain their competitors will. This evolution is marked by the integration of advanced technologies, particularly focusing on the management and utilisation of data to enhance efficiency, reduce costs and improve production processes.

The imperative for smart manufacturing

The adoption of smart manufacturing practices is driven by the potential to significantly improve operational efficiency and cost savings. This is the top goal according to many surveys across the sector. Benefits include reduced machine downtime, optimised inventory utilisation, increased throughput, enhanced forecasting accuracy and improved labour efficiency. Failing to embrace these advancements risks falling behind competitors who are leveraging these technologies to gain a competitive edge.

Understanding smart manufacturing

Smart manufacturing signifies the integration of data-centric technologies in manufacturing processes, marking the transition to Industry 4.0. This evolution, characterised using the Internet of Things (IoT), artificial intelligence (AI) and machine learning (ML), is rooted in the historical progression of industrial revolutions, from steam power to electricity, and then to digital technology. Now, the focus is on leveraging data through connectivity and advanced computing capabilities.

Core technologies and their implications

  1. The Internet of Things (IoT): IoT technology connects equipment and devices to the internet, enabling real-time data collection and analysis. This facilitates predictive maintenance, quality control, supply chain optimisation and more, through sensors and connected machines.
  2. Artificial intelligence and machine learning: AI and ML play crucial roles in interpreting vast amounts of IoT-generated data, automating complex tasks and uncovering insights that inform decision making and operational improvements. Insights, when combined with external public data like known regional delays, pandemics or political uncertainty, can enable an optimised decision based off all information – not just within the walls of a factory.
  3. Edge computing: By processing data closer to its source, edge computing reduces latency and accelerates decision making. It allows devices like smart cameras to analyse data in real-time, enabling immediate actions without relying on cloud-based processing.
  4. 5G networks: The deployment of 5G technology is essential for the real-time data processing demands of IoT, supporting faster speeds, reduced latency and enhanced capacity for numerous applications.
  5. Robotic process automation (RPA): RPA uses software bots to automate routine tasks, significantly reducing errors and increasing efficiency in manufacturing processes.
  6. Digital twin technology: Digital twins create virtual replicas of physical systems, allowing for simulation, analysis, and optimisation of processes and products in a virtual environment.
  7. Augmented reality (AR): AR enhances real-world interactions by overlaying digital information, offering significant benefits in training and maintenance through visual instructions and guidance.
  8. Cloud technologies: Cloud platforms support the storage, management, and analysis of the vast data generated by IoT, facilitating scalable and cost-effective data handling.

The crucial role of data management

Effective data management is the cornerstone of successful smart manufacturing initiatives. Master data management (MDM) addresses the challenge of siloed data by providing a unified platform for data governance, ensuring high-quality data and facilitating its effective use across the organisation. This is essential for leveraging IoT data, as understanding sensor data requires comprehensive knowledge of the assets being monitored. Without this governed and trusted data, then the effectiveness and ROI of any technology is lost. Even AI is limited if it’s only fed bad data at its core.


As manufacturers navigate the transition to Industry 4.0, the focus should be on identifying the specific data needed to be mastered, governing its accuracy in a centralised system by business level users, and sharing it so dependent workflows can efficiently harness it.

The integration of smart manufacturing technologies not only future-proofs businesses but also drives substantial improvements in efficiency, productivity, and competitiveness. The journey towards smart manufacturing is not without its challenges, but providing the data is trusted at its foundation, the benefits it offers make it an essential path for manufacturers aiming to excel in the digital age.

Get the eBook: Industry 4.0 success starts with a solid foundation.

Stibo Damien Fellowes has over 20 years of experience in the manufacturing and engineering sector, starting in product design.

His passion for addressing industry challenges led him to solution provision, working with organisations like Autodesk and Microsoft.

Now, with Stibo Systems, he leverages master data management to help manufacturers thrive in volatile markets.

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