With the right systems in place, the continual collection of data from all devices in the connected factory provide a depth of contextual insights to help form the complete story. With the complete story, business leaders are more accurately informed which fosters alignment and decisive action.
The right systems will also improve the capabilities within a connected business so devices can be enabled to apply what they have learned and automate tasks, helping to turn factories into smart factories. Therefore, not only do you have the complete story, but machines that use insights to continually improve productivity; a hallmark of the Industrial Internet of Things (IIoT).
Automation as a manufacturing concept is re-defined when viewed through an IIoT lens. Traditional, single function automation is not collaborative, nor is it agile. It performs static functions based on pre-defined rules. The type of automation that exists in a smart factory, however, self-optimises. It learns, not only from other machines and devices in the same factory but from wider networks which could even include comparable production equipment on an international scale.
Imagine you have a back injury caused by a number of contributing factors over the last few years. Now imagine that your desk knew that your chair was positioned too low for optimal ergonomics and that your mattress identified that your pillow height was causing poor sleeping posture, and beyond just knowing, your chair and your pillow actively corrected these issues to avoid the injury even occurring. Your chair and your pillow worked in tandem, using data and proven methods from other similar cases to formulate a collaborative solution, optimised for your specific needs.
Through machine learning, manufacturing software can begin to predict outcomes with greater accuracy. Predictions can also be continually improved as new data allows the system to learn as it defines patterns and monitors outcomes. Network security, predictive maintenance and advanced analytics are just some of the areas where machine learning can deliver tremendous improvements.
Intelligent machines have the capacity to be the most disruptive force in manufacturing, significantly transforming roles that we once resolved to be fundamentally human territory. ‘Cobots’ is the term given to collaborative robots which work with humans to complete production tasks more efficiently. Automated Guided Vehicles (AGVs) are used to move items safely throughout factories. As we discuss in our upcoming topic; The Connected Worker, IIoT will cause the role of the factory worker to be redefined.
Many of the most critical functions of IIoT for manufacturers draw on functions already established by ERP/MES technologies. Terri Hiskey, vice president for Product Marketing, Manufacturing Portfolio at Epicor Software provides valuable insights into how manufacturers can prepare for IIoT, in this Q&A.
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Originally published by Epicor