Edge Systems Enable PdM In Legacy Systems
EP Editorial Staff | June 8, 2021
Edge computing can add predictive maintenance and OEE analysis to existing discrete and hybrid manufacturing systems, creating cohesive insight-driven operations.
By Rich Carpenter, Emerson
New industrial-automation capital projects can easily incorporate the latest technologies for providing built-in remote monitoring and analytical functions. Often these features can be included for a negligible cost, especially in comparison with the extensive value they deliver.
There are far more manufacturing sites already in service than there are new installations. Equipment at existing discrete and hybrid manufacturing sites is years or decades old and must continue to operate, requiring increasing amounts of ongoing maintenance. End users at these sites would like to gain some of the advantages of modern predictive maintenance (PdM), overall equipment effectiveness (OEE) analyses, and key performance indicator (KPI) determination. Industrial edge-computing devices, with integrated computational capabilities, are the answer for these manufacturing plants.
Modern Computing Value
Under normal operating conditions, personnel at most manufacturing sites are satisfied if equipment and systems achieve basic functionality. Perhaps some locations have undertaken rudimentary efforts to measure, and then improve, operational performance, but essential productivity often trumps more involved optimization efforts.
The reality is that aging equipment becomes increasingly prone to failure. Most facilities support their systems using traditional methods such as time-based preventive maintenance or event-based reactive maintenance. The former approach can waste resources and the latter leads to downtime because things are only fixed once they break. Both schemes are costly in the long run.
Many users have come to realize the elementary benefits provided by typical automation devices and platforms such as programmable logic controllers (PLCs), human-machine interfaces (HMIs), and supervisory control and data acquisition (SCADA) systems. These provide visualization of current equipment status, annunciation of alarms, and historization of data for analysis. All are important for taking the first steps toward a continuous-improvement program, but greater gains are achievable.
When modern computing systems can be added to existing equipment, it becomes possible to tap into on-machine and other plant-sourced data. Once data is accessible, perform OEE analyses to quantify performance so users can recognize problem areas, implement potential solutions, and track the results of optimization efforts. OEE is also useful as part of a broader strategy to improve operational efficiency, drive lean production, and reduce overall waste. It is a fundamental part of a data-based approach to improved operation, but this can only be accomplished when the right data gathering and computing systems are in place.
Taking things a step further, PdM makes maintenance more proactive and cost-effective, minimizes costly failures, and increases productivity. OEE information helps users identify instances and duration of downtime, frequency of failures, and reasons for these failures—guiding efforts to fix underlying problems. Secondary information, such as energy consumption, may not be needed for operational purposes, but can often be traced to wear conditions, providing opportunities for improvement through maintenance and repairs.
Traditional PLCs and HMIs, when properly implemented, can provide some of the necessary building blocks. To truly move away from reactive operations and maintenance and toward a proactive approach, it is necessary to add modern edge controllers and full-featured HMI platforms designed for advanced data handling and processing.
Growing Up the Edge
Digital transformation does not occur by simply adding a newly automated machine or upgrading some equipment. Instead, it is a journey enabled by the progressive implementation of new hardware and software devices and architectures. An edge-maturity model provides some perspective.
Equipment at many manufacturing sites still exists as standalone automation islands, with only limited connectivity and simple functional interlocks. Other sites may be somewhat more progressive in terms of having a more advanced connected automation strategy, but most still rely largely on only the raw data available in the control and SCADA systems.
When existing systems are in production, it’s hard to justify a large automation retrofit capital expenditure project necessary to take the next steps. The thought of installing a new overall manufacturing execution system is daunting. Therefore, many sites get by with manual effort, spreadsheet manipulation, and data transfer by “sneaker-net” as the main means of improving operations and maintenance. These approaches are burdensome, ineffective, and error prone.
One Step at a Time
Modern edge-computing technologies make it possible to implement digital transformation one step at a time, targeting the most beneficial returns. With edge controllers or industrial PCs, along with advanced software, it becomes possible for in-house staff or local systems integrators to economically upgrade equipment and systems as part of operational-expenditure budgets.
Edge controllers are a special category of industrial hardware that combine real-time PLC control with general-purpose PC computing abilities. They are ideal as new automation devices, but they are also a good addition to existing PLCs because they work with most industrial and IT-oriented communication protocols. If an edge controller’s real-time control capability is not needed, an industrial PC is often the best platform for upgrade applications.
At the very least, the right software, running on an edge-computing platform, can act as a data concentrator and gateway, consolidating information from many other edge sensors and devices and connecting to higher-level analytical systems. Support for numerous protocols means it is possible to access smart devices and other sensors not typically available through traditional industrial data-collection mechanisms.
There is no reason for such edge computing to be single tasking. The newest edge applications can provide rich local visualization such as a standard HMI, remote and web-based visualization such as more advanced SCADA systems, and comprehensive remote access for operators and maintenance personnel.
In fact, the newest edge software includes wizard-driven options for plant analytics, lean manufacturing, and energy usage. These largely pre-configured elements make it easy for users to incorporate OEE in support of their optimization, maintenance, and sustainability initiatives.
It has long been possible to carefully test and integrate various hardware and software elements to build solutions that partially support OEE and PdM analyses. What has changed is the widespread availability of edge-computing options, along with comprehensive edge-capable and cloud-connected software.
These complementary hardware and software products can be used for new equipment, but existing legacy-asset systems are more numerous and thus present greater opportunities for improvement. These existing systems can be progressively upgraded to add broad OEE and PdM capabilities, without disturbing the underlying real-time control functionality. EP
Rich Carpenter is the General Manager for Product Management for Emerson’s, St. Louis, emerson.com, machine automation solutions business and has responsibility for its portfolio of control system, operator interface, industrial PC, and industrial IoT software and hardware products for industrial automation.