The right tools and tech can enable advanced predictive maintenance, bottleneck prevention and optimization. Find out how digitalization is bridging the gap between legacy systems and Industry 4.0.
Without a doubt, digitalization is setting high standards for efficiency and throughput in production. Today, as manufacturers move ever closer to Industry 4.0, the question has increasingly shifted from ‘if’ to ‘when’ production companies will be able to make use of the data being generated with every piece that comes off the line. How do traditional companies take the first steps to digitalization and put that data to work? How do they make the move to unlocking the potential in every production system to improve and optimise their output? And what is the simplest way to harness the power of cloud computing and artificial intelligence at the edge?
As we know, not every modern factory is a greenfield high-tech showroom with pristine workers in lab smocks. In fact, many of them may not even be all that modern, but that doesn’t mean they shouldn’t benefit from the modern tools, processes and best practices that are the hallmarks of a productive and successful factory. In this journey to modernity, digitalization has become a vital bridge, enabling owners and production directors to begin harvesting the data that can provide vital clues to enhancing production.
Start with sensors
As new standards of efficiency and quality become the norm, those seeking a competitive edge are turning increasingly to digitalization. Sensors (from very simple to highly complex) can be incorporated into all types of production lines, to measure everything from unit temperature and speed to output shape and size, weight and hardness and most everything in between. Sensors can form part of a wireless network, sending signals remotely, or can be connected directly into an existing production system, depending on the needs of the factory.
From raw data to vital information
The resulting output from these sensors is the raw data that can be transformed into information and insights to streamline efficiency, remove bottlenecks, reduce downtime and optimize production cycles—when used correctly. Before any data can be analysed, it has to be stored, either on an in-house server or using a cloud-based service for greater scope for expansion and off-site processing. Exactly how much storage is needed depends on the application, level of digitalization, output form and required analysis. For comparison, a production line with simple sensors attached to monitor throughput will generate significantly less data than one with quality-control cameras monitoring multiple types of product forms.
Cloud or edge?
Pulling together the data points from various gates in the production process is an important first step. The speed of many production lines is one of many determining factors in what happens next. Once data is captured, it must be stored and processed. If intensive analysis is required (for bottleneck prevention / correlation analysis etc.) then local storage might be suggested. If large amounts of data are to be processed, a cloud solution might be preferred, though if real-time processing is needed, the constant back-and-forth of data to and from the cloud can cause delays through latency. Here is where edge devices are ideal, since they enable processing much of the data close to the machine itself, without needing to overload the network with streams of files destined for processing in the cloud. Simply put: when data is processed at the edge, the results can be made available faster, at less cost, but it all depends on the precise needs of the application, which can be determined with the support of OMRON together with our partner network.
Creating a manageable system
Of course, there are solutions that can help simplify and automate the entire process. For instance, bringing it all together into a meaningful and manageable system, OMRON’s Sysmac Automation Platform, a proven solution that delivers powerful and robust data capture and processing capabilities. Providing accurate and predictable data capture and analysis, Sysmac uses an Artificial Intelligence engine to allow real-time data predictive analysis. It has a controller that includes direct SQL database connectivity, with OPC-UA and MQTT compatibility. It provides a single control for the entire machine or production cell, and can be easily configured to suit any setup.
Built with security and ease of use in mind, the Sysmac range brings reliability, robustness and fast control into the hands of factory owners looking to benefit from digitalization. Handling input and output from sensors and actuators, vision and motion controllers, IO and safety, it is easily networkable and simple to control. So, whether you’re looking for manufacturing traceability, predictive maintenance, change simulation or bottleneck resolution, proven tools are out there, ready to help.
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