How machines, data and humans can lead the new manufacturing era

We are in the midst of the 4th industrial revolution, and data is consuming the world. Technology, marketing, and finance are among the sectors where AI and data have dominated innovation and transformation. The purpose of these forces is rarely to replace humans. The development of applications that can release humans from repetitive tasks or allow them to make intelligent decisions occurs from time to time. Even in the most sophisticated sectors, people will not go anywhere. We will continue to rely on humans (at list) in manufacturing, production lines, supply chains, and logistics. It takes time for industries to change. Humans are needed when context and diversity are high.?

There is, however, a dramatic difference between manufacturing today and twenty years ago. Digital transformation, no-code platforms, cloud infrastructure, data-driven decisions, and artificial intelligence are already improving many processes. Today, frontline production employees can be empowered and given the tools they need to be successful. In the next decade, employees will be able to achieve more and be freed from repetitive tasks thanks to the innovations that will dominate the industry.?

There are winds of change blowing outside. Even though the world might be facing a recession, technology still dominates the world (and the S&P 500). Software will undoubtedly continue to change the way we interact, make, build, operate, and supply. There has always been a slow adoption in the manufacturing sector, and margins and savings have dominated innovation - but we are ready for a dramatic change, the fourth if you will.?

The people in your factory can be connected via apps, their work can be digitalized, and all data can be stored in one place. Operationally, this is a revolution. It allows you to make better decisions, monitor almost every step, and receive relevant alerts at the right time. Employees' productivity and yield are likely to increase, and employees will have more time to deal with less repetitive and complex tasks. There are three critical components to that journey.?

Connectivity.

A coherent data warehouse is the driving force behind the revolution. We can use every human interaction, machine, and application to gain better insights, actions, and decisions. The creation of data is the power of connectivity in a world where data is king. All of these factors need to be brought together in one place: people's interaction, behavioural data, machine sensors, databases, supply chain information, and ERPs. With the addition of cameras, you will add visual data, giving the organization a superpower.?

Learning.

We are always striving to improve, learn more from each other, and develop ourselves. We have been able to transfer knowledge to machines thanks to machine learning. We have been able to use smart AI applications in a variety of ways. Combined with humans in a closed loop where machines learn from humans, and humans learn from machines, we can now transform the manufacturing industry.?

Scale.

As engineers use the tools at their disposal to create unique applications at scale across thousands of production lines in hundreds of sites, a revolution will be enabled by these tools. As long as everything is connected and your data is centralized, you will be able to learn and deploy at scale.?

Let's put this into practice.

Having the right connectivity, learning capabilities, and scale infrastructure is essential for defect detection, localization, analysis, and measurement of errors across factories and production lines.?

You need to acquire data, stream it to data lakes from many edge devices, collect human labels, build models, deploy them, collect feedback, and correct yourself repeatedly to build a computer vision application.?

Creating such automation depends on enabling user experiences, where humans interact with data and machines. Creating complex solutions at scale will not be possible without no-code platforms. In order to achieve the best outcomes, we must connect data, machines, and humans through platforms and make sure that there is a close loop between the three.