Everyone is talking about the fourth industrial revolution (IIOTor i4.0), in which the integration of smart technologies, machine-to-machine(M2M) communication and the Internet of Things (IoT) will enable highly automated production lines.
One of the most common questions raised is where will humans fit in the production of the future? Some people question whether the job of“ machine operator” will even exist once there are machines that can self-analyze and diagnose issues and entire production lines can operate without human intervention.
AI is already part of our everyday lives. It helps us make decisions about our financial assets, auto-finishes our internet search questions, and alerts us before we make deadly driving mistakes. AI for manufacturing is still considered as a challenge for some, but the journey toward autonomous manufacturing has already started.
How data is used today
Already, the first steppingstones are in place – in the form of the vast volume of data that is being generated by advanced machines and systems in many factories. The hottest trend right now is smart manufacturing –using that data to better understand manufacturing performance and utilizing data-based decision-support tools to help us meet production and business KPIs.
But that’s only the beginning of how data will affect the manufacturing sector.
Some manufacturing sectors have successfully implemented robotic process automation (RPA) processes and even use AI to support management decision-making. But the vast majority of manufacturers have not yet implemented such technologies on the production floor itself – even though doing so would enhance the control and decision-making capabilities of the control room operators regarding crucial production factors, including production speed and cost, and product quality. Often, the data exists, but they’re not using it.
How important are people, really?
After years of working closely with manufacturers, mainly in the wood processing business through my role here at Smartech, I’ve come to realize that AI, innovation and the human factor together play a crucial role in meeting the goals of the plant. In plants that rely on operator experience, knowledge and skill, the operator has a huge impact on the performance of the machine or the line. Along with that, the operators in a given shift massively affect the performance of the whole plant.
One of our customers, a large wood manufacturer with multiple plants, allowed us to track and review manufacturing process data for60 days at a processed wood boards plant. We took data from one production line and compared the performance of the three different shifts. Oddly enough we found huge differences. All the shifts worked on the same line, operating the same machines, and manufacturing the same products, and yet performance across multiple parameters varied greatly.
Among many parameters we analyzed, we discovered a 35%difference in the quantity of grade-A products from one shift to another. We found a 5%-6% difference in the density of the boards that were produced, depending on which shift was working. And we saw that one shift drove significantly higher productivity than the other shifts during the same period. Additionally, wear on the wood-shredding knives differed according to shift.
Imagine if the entire production performance baseline could be as good as the performance of the best shift… or even higher.
This can be achieved by combining the human factor with smart AI capabilities.
The enduring value of human knowledge
As you can see, the human factor has a huge impact, for better or worse, on the production line. Human operators are vital to the success of the plant as a source of knowledge for troubleshooting malfunctions and when creative thinking is required. Even when AI algorithms are ‘operating’ the production line, human ingenuity and action will still be needed.
Rather than replacing operators, autonomous manufacturing will create a new role for them, as ‘mentors’ to the algorithms. The AI algorithms, as they are designed to do, will continually learn from human behavior and optimize it.
Instead of fearing the future, we need to embrace AI and other advanced technologies, and use them to reduce costs, improve the quality of our products and become more productive.