Smart Factory. Internet of Things. Industry 4.0. These buzzwords seem to be everywhere, but what does it all even mean?
Industry 4.0 is a name for the current trend of automation and data exchange in manufacturing technologies. Industry 4.0 is commonly referred to as the fourth industrial revolution.
So how did we get to Industry 4.0?
Industry 1.0 is considered to be the first stage of modern mechanization. This involved the use of energy and power sources such as water and steam. Having a constant power source meant the ability to increase scale of activity and achieve more constant outcomes from a production process.
Industry 2.0 originated from the concept of mass production and standardization. The idea of the assembly line was born, and the availability of electricity made it all possible.
Industry 3.0 arose with computers and their ability to tie everything together into automation, which further enhanced the ease by which production processes could be streamlined and/or expanded in scope.
That brings us to Industry 4.0. Computing and associated technologies have evolved to a point where physical connections or wiring for communication isn’t necessary in most instances. Technologies have evolved to be able to learn through artificial intelligence. Some examples for Industry 4.0 are machines which can predict failures and trigger maintenance processes autonomously or self-organized logistics which react to unexpected changes in production.
This interconnectedness and machine learning together represent the basis for Industry 4.0. So, what do we do with it?
Because the ideas of interconnectedness and machine learning are very broad, it’s often difficult to determine how to even get started with taking advantage of them or implementing them into our reality and processes.
Let’s consider a flexographic printing press. What if the press just “knew” what good print and sellable product was? How would it do that? What would it mean?
Some press offerings already offer Industry 4.0 features such as:
Automatic impression setting and control (through learning)
Automatic register setting and control
Automatic ink viscosity control
Automatic cleaning and washup
Automatic diagnosis of hardware and software
Automatic material splicing and transferring
Automatic web guiding
Print job recall and sharing between several presses
Automatic defect detection and culling
Automatic web tension control
Automatic notification of status (Text? Email?)
Automatic process adjustments through production speed changes
What’s next? Automation leads to consistent output, or more reliable performance for sellable product. Automation can help expand production capabilities and open up access to new or expanded markets. Machine learning can help guide innovation and process improvement toward higher efficiencies and increased effectiveness. Higher profits can result.
Will presses be run remotely? Will they automatically monitor and adjust all process variables? Will presses communicate with one another and with other equipment and information systems to optimize an entire facility’s production? Will they train operators? Will they need operators?
In the short term, since getting our arms around the broad concepts of artificial intelligence and complete connectivity will be difficult, their implementation is likely to be in the form of features. However, as interconnectedness increases, complete thinking platforms may become the norm.
Welcome to Industry 4.0.