The everchanging landscape of Industry 4.0 means that new phrases and terms appear more often than screws on a BOM. Besides the main terms like Cloud Computing, Interoperability or Machine Learning, new phrases such as ‘Servitization’, ‘Edge Computing’, and ‘Digital Twins’ have emerged recently, making it hard to keep up. We’ve collated them, and below, you’ll see the top 6 terms we think all manufacturers should understand.
Servitization deals with the service-related expansion of manufacturers, many of whom are re-examining their business models and starting to offer services together with their traditional product offerings. This leads to an integrated service and product offering, where the manufacturer provides both the product as well as the expertise, support, and/or maintenance. The ‘product’ then becomes a ‘solution’, where the product and service are packaged together.
A digital twin is basically a digital version (a ‘twin’) of a physical model, product or process. It uses sensors that gather real-time data which are connected to a cloud-based analytics system. As per Forbes, “this pairing of the virtual and physical worlds allows analysis of data and monitoring of systems to head off problems before they even occur, prevent downtime, develop new opportunities and even plan for the future by using simulations.”
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Commonly mentioned in relation to 3D-printing, additive manufacturing deals with the technologies that adds layers of material to produce these 3D objects. With the use of a computer, 3D modeling software, machine equipment, and layering material, “the AM equipment reads in data from the CAD file and lays downs or adds successive layers of liquid, powder, sheet material or other, in a layer-upon-layer fashion to fabricate a 3D object.”
Forming the base of Industry 4.0, Cyber-Physical Systems are “integrations of computation, networking, and physical processes. Embedded computers and networks monitor and control the physical processes, with feedback loops where physical processes affect computations and vice versa. The technology builds on the older discipline of embedded systems, computers and software embedded in devices whose principle mission is not computation, such as cars, toys, medical devices, and scientific instruments.”
Per GE, “In the context of IIoT, 'edge' refers to the computing infrastructure that exists close to the sources of data, for example, industrial machines (e.g. wind turbine, magnetic resonance (MR) scanner, undersea blowout preventers), industrial controllers such as SCADA systems, and time series databases aggregating data from a variety of equipment and sensors.” With big data and advanced analytics, larger amounts of data is being processed and stored in smaller devices that are situated closer to the original source (the industrial machine).
Predictive Maintenance describes a range of techniques that aims to determine actual conditions of in-service equipment using periodic or continuous monitoring, and help to decide when the equipment will require servicing. The goal of predictive maintenance is to be able to schedule maintenance to reduce downtime and increase plant productivity. Since it uses actual data to determine maintenance times, it is more accurate than preventive maintenance, which uses average or expected numbers.
Download our full list of Manufacturing Industry 4.0 terms in our resources page!