Four myths about smart factories debunked
Yves Bourgeois on
Smart factories are costly, as exclusive as an Oscars afterparty, and building them would take more time than teaching an old dog new tricks. Their end goal? Eradicate human brain activity from the production floor. Here are four bogus myths and misconceptions about smart factories.
Digital factories use connected and flexible automation systems that gather data from equipment, processes and people in real time, in order to learn and adapt quickly to new demands. They’re considered the backbone of Industry 4.0.
Smart factories aren’t new, they have existed for over 10 years. Yet, there are still many misconceptions and false claims about them. Here are four common myths about digital factories – and why they don’t make sense.
1. Smart factories are only meant for the happy few
It’s probably the most persistent misconception about smart factories: they’re reserved for a small circle of large enterprises with deep pockets only.
The opposite is true: through its scalability and flexibility, the next generation of web-based IIoT technology has never brought the concept of the connected factory closer to the SME world.
What is even more important, IIoT solutions will save you money, resources and time, and therefore pay for themselves. No additional hardware is necessary to get the system up and running. In fact, in case you run a smart factory in the cloud, there’s (almost) no need for complex IT infrastructure anymore.
2. It takes ages to implement IIoT technology
When considering starting an IIoT project, some companies fear a never-ending implementation process. And if they’re thinking about traditional solutions, they’re spot on.
Sure, building a framework for a smart factory could potentially take years, in case your current infrastructure lacks all flexibility and scalability.
Yet thanks to web-based technologies, implementing a smart factory MES can now be done in a matter of months after functional analysis, not years.Fact is that smart factories aren 't created over a fixed period of time. They take a continuous learning and automation process.
By thinking big, starting small and scaling fast, any business can pull a successful IIoT project off the ground without wasting huge amounts of time.
Start gathering process and machine data from one or two processes using open source tools, and gradually build further on the results. This will help you create value at a much quicker pace than with a classic black-box solution, which will require you to go all-in without first taking a look at your hand.
3. Legacy equipment has no place in a smart factory
Most industrial companies that have been around for a while, are still running some kind of machine, SCADA system, or even production line they used in the 90s. Mostly because it has never stopped working. Often used for specialty or long-running orders, some of them have built legendary status around the plant.
Their IIoT-abilities, however, have less mythical proportions. A common issue is that they use older industrial protocols such as OPC-DA and Modbus instead of today’s OPC-UA. But this doesn’t mean they can’t be part of the smart factory ecosystem. A relatively simple conversion tool can do the trick.
With Factry Historian, collecting data from legacy systems and equipment is made easy. Our IIoT data platform is shipped with our own sturdy collectors for these protocols, teleporting your company’s relics of the 90s into the IIoT world.
4. The end goal of smart factories is to replace humans
When introducing the concept of a smart factory to staff workers, it might be perceived as the first step in creating a fully automated ‘lights out’ production site, with no need for human intervention. Not in the least by production operators and managers, who might fear a smart factory will cut their jobs.
Instead, it will only make their jobs easier and more useful.
Since data of production and process parameters are collected automatically, there is no need for the operator to enter data manually. As such, the software streamlines their workflow and reduces stress. Production progress can be displayed around the site, having people feel more part of the process.
Contrary to what is often believed, full automation is not a prerequisite for smart factories. Its success is defined by the data that is collected and how you analyse and learn from it. Today’s smart factory automation software is finally aimed at improving the workflow of operators, and not at ruling them out.
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