Manufacturing is the creative expression of the human mind. Throughout history, humans have problem solved and created technology to make life easier. From harnessing fire to using simple tools, manufacturing has allowed humans to build complex machines and societies. It is the most human expression of innovation –to meet a need. Even within the smartest manufacturing plants in the world – it is the humans in that environment that make it a success. The pandemic has accelerated our dependence on technology and connectivity, but let’s learn from real life examples, that more technology in the absence of human creativity is not always better. Industry 5.01 encapsulates that learning and places a heavy value on the human workforce in collaboration with smart machines.

Why are humans so important in the manufacturing ecosystem?

What even the smartest AI machines have not been able to do well, to date, is incorporate real life into learning and/or performance. It is these real–life scenarios that differentiate between my car shutting down on the highway (unsafely) versus while I am sitting idle in my driveway (safely). It is the difference between (non-optimal) mobile software performance in cold temperatures where people wear gloves versus (optimal) performance in a warm climate. It’s the difference between knowing that a product launch in two markets was in reality differentiated because the state of Texas was without power in February 2021 and not because the product wasn’t well received. Real life experiences and context is a unique layer of analysis that humans do exceptionally well.

As these smart machines optimize a variety of essential manufacturing operations and have allowed manufacturing to scale and economize, they are limited in their operations by programming. While with AI they, like their human co-workers, can now identify problems in production and stop production until the problem is rectified, what machines don’t get is frustrated – even if a problem is occurring with an annoying frequency. We rarely see frustration as an admirable human quality however, in manufacturing it is often the difference between doing something wrong perpetually and creating an alternate viable solution.

Frustration, it seems, is the human motivator for problem solving and that makes human co-workers alongside robots essential in manufacturing if timely solutions are required to be created and programmed into operations.2

Robotics in Manufacturing

The connectivity, IOT3 and IIOT4 of smart machines and robotics in manufacturing has allowed for manufacturing to scale, learn, and operate at rates never known before. Not only is connectivity important in manufacturing itself, but manufacturers are also pulling real-life data from their products in use. We have all benefited from this connectivity – think of our smart phones – and the future of IOT in manufacturing is exciting, allowing for greater customer personalization, enhanced user interface and remote maintenance and trouble-shooting solutions when things are not optimal. The more connected manufacturing machines are to each other and to us and the more inter-connected users are to the manufacturing interface, the more data that is generated and collected, globally.

That’s a whole lot of data. And the thing about data is that it does tell a story…to a point. The smart machines with AI will be able to sort the data into useful, meaningful charts and graphs that they have been asked to create – things, for example, that may identify a need for a software update to optimize performance and efficiencies. What smart machines will not be able to tell you is that driving habits during a pandemic are going to change and that the driver experience may be compromised when the operating software does not recognize this. They won’t realize that the reason the software is not running optimally in December and January on our smartphones in Canada is because its negative 20 degrees Celsius and users are wearing gloves in colder climates while using the program. What the data will say is that there is an interface problem. Not why. And this is where real-life context is critical to data analysis.

Data alone does not always tell the lived story. The actual ‘climate’ the data was collected in may be completely different than what the smart machine inferred and without human curiosity and a layer of real-life context key and vital information can and is being missed.

“Business decisions today are largely driven by the data that is available to us. However, we need to remember that our data is only as good as the source and our interpretation is only as good as the person telling the story. We will always need to layer in context over any machine interpretations.” Nancy Gray-Starkebaum – Phenom5

Mistakes, like my car’s software glitch, point to the fact that at the heart of manufacturing must still be the pulse of a human. When there is a malfunction, we are reminded that machines and technology are limited to performing exactly as they were asked to – or programed to.  Even in highly automated environments, people must continue to develop, train, and iterate machine learning models to facilitate robotic automation. The feedback provided by the humans in the loop – even in highly automated environments – is critical to the success of automation.6

Humans appear to be the essential workers in manufacturing for some key reasons. We are better at critical thinking, we can multi-task more efficiently, we interpret real-life and experience into our analysis, and we problem solve when we are frustrated. Without humans in manufacturing, you simply have a robotic factory. In the words of Elon Musk – “Yes, excessive automation at Tesla was a mistake. To be precise, my mistake. Humans are underrated.”6

With humans at the centre of manufacturing you have a complex ecosystem that benefits from the collaboration between smart machines and smart humans – utilizing the unique skill sets of both. What we have learned is that humans are not replaceable in manufacturing. They are essential alongside the operations of robotic smart machines for some key reasons. This is the power behind Industry 5.0. Therefore, it is critical that those manufacturing remain committed not just to advancing technologies but also to the allocation of resources that ensure the smartest, most innovative, creative, problem solving, and divergent thinking humans are in their employ.


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5 – Nancy Gray- Starkebaum, VP International Customer Success, Phenom 

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