Four machine control trends to watch closely
Machine control is at the heart of new automation strategies today because it connects machines to the enterprise level, integrates other systems like robotics and vision, and significantly impacts system security. Due to its important role, it’s essential to understand what’s impacting the current evolution of machine control.
Let’s take a look at some major control trends that are evolving in manufacturing today.
1. Integrating control- and enterprise-level networks
Automation systems were traditionally structured according to the pyramid-shaped Purdue Model. The model’s lowest level comprises the physical processes that the machines execute, while the highest level corresponds to the overarching business logistics systems. Intelligent devices, control systems and manufacturing operations systems reside in between.
With the increasing adoption of Industrial Internet of Things (IIoT) technologies, this hierarchical design paradigm appears to be losing its relevance. Manufacturers are favoring more hardware integration between network levels, increased peer-to-peer networking and a flatter approach to system design.
2. Leveraging the benefits of both PCs and PLCs
The PC versus PLC debate has swung in both directions over the years. PLCs are more reliable and more optimized for machine control, but PCs offer greater flexibility and greater processing power. Near future trends include efforts to put more complex software applications – such as data analysis algorithms – onto PLCs.
Omron has been working to give manufacturers the best of both worlds with an IPC that has a split-core PLC and PC. This innovative solution provides all the reliability one expects from an IEC 61131 programmable controller while running in parallel with PC software and staying immune to Windows OS crashes.
3. Improving maintenance with machine learning
Manufacturers are increasingly employing machine learning algorithms to detect patterns and anomalies in machine function. In some cases, machine learning engines run within the machines themselves to analyze machine data over time, determine the baseline of “normal” machine behavior, and recognize any outliers in the data that could indicate a problem.
The use of machine learning to improve maintenance and keep an eye on machine functionality poses significant benefits for manufacturing facilities that could suffer excessive amounts of machine downtime when experienced workers leave. Applying machine learning to maintenance can minimize downtime while new hires are learning the ropes.
4. Implementing solutions with a single IDE
As automation solutions grow in complexity, manufacturers are beginning to see great value in implementing integrated solutions from a single supplier. This dramatically reduces the engineering costs of automation design and integration and makes maintenance much less complicated.
The use of a single integrated development environment (IDE) for all automation programming needs, including robotics, sensing, vision, motion and safety, reduces the time required to train operators because they only need to familiarize themselves with a single software interface.
This post is adapted from an article in Control Design to which Omron Automation Center Director Mike Chen and Omron Controllers/Components/Safety Marketing Manager Sriram Ramadurai contributed. Read the full article here.