Can automation solve the manufacturing paradox?

By now, neither Industry 4.0 nor the smart factory need any introduction. We all know they offer great opportunities to increase competitiveness through new technologies. However, if you walk into an average factory these days, there is still a very high chance you’ll find outdated systems, error-prone manual work and operators scribbling things down on paper. Despite vast amounts of technology that have become accessible, many manufacturers are still dealing with yesterday’s problems. The question is, why? 

 

Lagging in digital transformation 

 

After the third industrial revolution, factories moved into a phase of automated production that focused on capital-intensive machines and robots. These relieved workers of physical labour and boosted productivity. Since that revolution was so successful, manufacturers have started to myopically focus on operational technology (OT), neglecting the opportunities of information technology (IT). 

 

And what opportunities they are! Going into Industry 4.0, manufacturers can digitise production processes and streamline their operations. There is a vast amount of new IT solutions available, ranging from artificial intelligence and machine learning to augmented reality, digital twins, the internet of things, machine vision, robotic process automation, AMR, virtual reality and more.  

 

It’s a lot to take in, and going digital can easily become a challenge. In its 2021 Quality Emerging Technology Roadmap, research firm Gartner identified 31 emerging technologies that paint the picture of the smart factory. The stream of new tech continues flowing: state-of-the-art devices and systems are invented faster than most factories can deploy them. 

 

Faced with the overwhelming task of choosing, it’s understandable that many manufacturers are struggling to determine what would work best for their factory. Or even where to begin. There is even confusion as to how technology differs per manufacturing type. Discrete manufacturing for instance, seems much more focused on machine vision, while for process manufacturing, sensors and IoT appear to be more relevant. 

 

What happened to “start with the basics”? 

 

More often than not, digital transformation is used as a synonym for looking at the most advanced “toys”, such as the technologies mentioned above. But that’s skipping way ahead.  

 

Investing in the most advanced tech makes sense only after digitising core processes first. For example, manufacturers using a paper- or spreadsheet-based approach to collect data don’t have the capability of turning that data into insights. Picking advanced technology such as IoT, edge computing or AI, they won’t see immediate improvements. Instead, this will add an additional stream of data that most likely won’t lead to progress.  

 

In fact, in its 2021 Quality Emerging Technology Roadmap, Gartner classified AI, machine learning, predictive analytics, augmented reality and digital twins as high risk. Other technologies mentioned in the report are much more embedded in existing processes and are therefore better candidates for digitisation.

 

The manufacturing paradox 

 

Despite the discrepancies that we see these days – factories working with both outdated systems and high tech – manufacturing has been an example for many other industries for decades. For instance, Kanban boards, invented by Toyota, spread to IT and software teams and through the Agile movement even into banks and insurance companies.  

 

While there are indeed exemplary cases, there are even more examples of manufacturing not leveraging what it already has. Take statistical process control (SPC) for example. SPC rivals both the statistical foundations and benefits of AI and ML. It has been around for almost a century, yet the data gathering for these advanced and proven methods is done on paper and Excel sheets. Sadly, as SPC sits in the quality control domain, it is often overlooked as a potential spearhead for digital transformation. 

 

This highlights once more that while there is not one way to start with digitisation, there are many gains in starting with the basics. Manufacturing leadership must embrace and promote digitisation and create an achievable roadmap for it. 

 

Six important takeaways

 

So, can automation solve the manufacturing paradox? We believe it can as long as manufacturers cover their bases. Here are six important takeaways that will help in your decision-making:

• Hire people that are digitally savvy, and empower them to lead digitisation projects
• Digitise the data you already have but cannot really use right now
• Quality management is a great place to start, with electronic quality management systems and manufacturing execution systems as its technological pillars
• Once you’ve covered your bases, you can expand 
• Remember to choose tech that’s inclusive and can benefit everyone from shop floor to boardroom
• Connect your data to clear KPIs and stimulate a culture of continuous improvement

---

 

To find out more, please visit the AlisQI website.

 

---

 

By Otto de Graaf, CMO and Co-founder AlisQI