Machine control strategies to minimize downtime
By Omron Product Managers, Thomas Kuckhoff and Clark KromenakerAutomation Machine Building noads
Sponsored by Omron
How AI, predictive maintenance, remote monitoring and 2D/3D simulation help manufacturers deliver high quality and low cost.
The automotive manufacturing industry is under pressure to keep boosting productivity with Industrial Internet of Things (IIoT) and smart machine control solutions. In addition, manufacturers need to control quality and enhance safety to meet advanced regulatory requirements. To fulfill these requirements, it is crucial to utilize information, protect operator safety, control quality and improve production efficiency all at once.
Challenges are always evolving in fast-moving environments like automotive manufacturing, but one that has been recently amplified, is the sheer amount of information available from manufacturing processes. Companies are looking for ways to take advantage of that information for the purpose of improving quality and delivery times while continuing to meet changing regulatory requirements.
A focus on control technology — and the incorporation of AI
Automotive suppliers of all tiers and OEM manufacturers are under tremendous pressure to deliver both high quality and low cost. Controllers have been positioned to be a bridge between these diverging metrics. As the controller is the very heart of machine control, it is essential to allow the unit to gather data in real-time to ensure product traceability without a dauntingly steep learning curve. This is seen in programming environments with drag-and-drop features as well as data that can be sent on deterministic networks through controllers with high throughput.
Unscheduled equipment downtime can be a costly productivity killer. Using artificial intelligence, we can predict that certain processes or equipment will soon need attention. Before a downtime event occurs, maintenance or required replenishment can be scheduled. AI controllers can preemptively assist in analyzing the data that is collected at the manufacture level, then take action to notify parties across plant levels.
Integrating AI into controllers provides a set of eyes on real-time data, even when thousands of bits of data need to be monitored. Of course, controllers require a fair amount of processing power to achieve this, and that is exactly what controller manufacturers can provide in their flagship products. With this processing power, controller AI can raise alarms and make basic decisions to give the automotive industry the ability to get ahead of product hurdles versus being in a pure firefighting mentality.
How predictive maintenance can help companies avoid downtime
One of the largest contributions to productivity is predictive maintenance (PdM). Predictive maintenance is a proactive strategy that involves evaluating equipment’s condition through continuous monitoring. The goal is to use real-time data to identify component failures early, reduce unplanned downtime, and avoid costly repairs. With PdM, maintenance is only scheduled when specific conditions are met and before the asset breaks down.
By combining component information and monitoring into the controller, we can monitor components like relays and estimate the time before they need to be replaced rather than waiting for them to fail. Items such as servo drives and power supplies can have monitoring circuits built in to watch how the components in those devices are working. These monitoring circuits will let maintenance personnel know exactly when to replace them — after they start to age, but before they fail and cause downtime. Components that have settings saved into parameters on the device can have those parameters saved in the controller for easy download over the industrial network, so time can be minimized when replacement is needed.
How remote monitoring breaks down data silos
Remote monitoring has allowed companies a big-picture view of their operations. Previously, if a corporation had several manufacturing locations, these were likely silos for machine data. Remote access has allowed these silos to be broken down, so machine performance data and analytics can be available to a central location, offering a better view into company performance. It can also allow access to the machine from its OEM as well as the controller manufacturer. This can help during troubleshooting and lead to ideas on how to make the program of the machine as efficient as possible to allow the highest machine throughput.
Remote monitoring provides not only safety, but also non-intrusive inspection of machine performance. In so many steps within the automotive manufacturing process, for both EVs and ICEs, placing distance between operators and the process’s required energy has real benefits. Monitoring remotely gives that protection without losing connection to the condition of the process. Additionally, troubleshooting is difficult when the process is unable to replicate the fault, whereas remote monitoring allows maintenance teams to identify root causes more quickly as more data around the fault gets collected. This enables diagnosis of the true source of the problem and not merely its side effects.
How software innovation is enabling powerful, all-in-one control systems
The automotive industry boasts some of the greatest talent within the engineering workforce. Some the best and brightest are leading the charge in making automobiles safer and longer-lasting while simultaneously reducing the carbon footprint associated with transporting people and goods. Software development has taken this into account to provide these leaders with the ability to control the entire site from a central powerful location and prove that each machine’s program is feasible before implementing on the line.
With 3D and 2D simulation, we have seen software development changing machine controls as these simulations greatly decrease the risk of machine crashes or failing first-piece production. Control software with simulation capabilities helps take the risk out of automation, and it thereby reduces costs while increasing quality. For those seeking to sharpen their competitive edge, a control software that flattens the learning curve, proves that programs work prior to their implementation, and allows for a wide breadth of hardware compatibility is an excellent choice.
One advanced control system that is available today is an all-in-one automation system. This can create an environment that integrates logic, motion and drives, robotics, safety, visualization, sensing, and IT into a single platform, thus reducing the learning curve and the intra-operative software costs. The all-in-one system provides one point of connection, one backup file, and one software to maintain on a computer in a single environment.
Manufacturers have choices. At the controller level, an integrated development environment (IDE) product would be preferred for the purpose of configuring the controller — whether it be an AI system, OPC-UA (Open Platform Communications Unified Architecture), SQL (Structured Query Language), or one of the enablers of IIoT. It is inconvenient to have separate packages for each and every programming and configuration activity. It will help in the design development and save integration time when there is no need to move between products.
Automation control system improves sustainability
Environmental changes will affect every industry, and manufacturers must also move to more sustainable ways of working by conserving energy and materials and maximizing efficiency whenever possible throughout the whole production process. An automation control system can help improve sustainability for manufacturers by minimizing downtime and the wasted energy associated with it. Powerful software, including AI algorithms and simulation capabilities, can dramatically improve machine design and reduce downtime from unexpected failures as well.
Thomas Kuckhoff is an Omron Product Manager for Controllers;
Clark Kromenaker is an Omron Product Manager for HMI, IPC, Controllers, Software.
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