End users, OEMs and technology partners engage on IIoT

IIoT-enabled predictive maintenance maximizes uptime, with machinery end users and OEMs working together to determine best practices

By Silvia Gonzalez August 26, 2020

The Industrial Internet of Things (IIoT) solutions and methods enable collection of machine data and monitoring of machine performance and reliability. Both end users and original equipment manufacturers (OEMs) can act on this data to achieve their goals, improving asset uptime through predictive maintenance and asset efficiency through production analytics.

Because of the benefits, digital transformation and incorporation of IIoT concepts have become business priorities, requiring more collaboration than ever to ensure success. This is because digital transformation isn’t just a one-time event but instead a journey involving both technology and people.

To ensure they are travelling down the same path, manufacturing plant end users, OEMs, and IIoT technology suppliers are partnering in the design and implementation of equipment to ensure value can be realized, while overcoming the perceived risks of sharing data. Manufacturing plant end users and machinery OEMs also demand robust and secure platforms, which are now available in the form of edge computing.

The playing field

For greenfield projects, end users will likely expect OEMs to deliver equipment automated with the latest IIoT-enabled technologies. However, many industries have substantial investments in legacy equipment and control platforms, and they also look for ways to implement IIoT and achieve the associated asset monitoring benefits, with minimal disruption to their operations.

Both end users and OEMs share a common desire to determine and implement the best IIoT practices. The IIoT objective cannot be well defined, let alone be achieved, if these parties remain siloed. End users and OEMs are finding they can coordinate with each other, and with IIoT technology partners, to ensure their strategies result in a complete and compatible ecosystem solution.

Some design goals are desired by both parties. For instance, automation systems that include technologies that make integration and data sharing easier are preferred because they provide flexibility and scalability. Similarly, designs that are as close to plug-and-play as possible facilitate integration and reduce downtime during retrofits.

End users and OEMs alike want to keep the design focus on implementing technologies that add value and begin by addressing the biggest pain points. Because OEMs are designing and building the equipment, it is vital for them to understand end users and how IIoT technologies can help deliver value.

End user concerns

Industrial end users want to implement IIoT solutions able to improve operational and business performance. End users may have multiple sites, and likely operate several different systems at each, so interoperability, reliability, security and scalability are all crucial.

While end users will not be able to reach all of their IIoT goals immediately, they definitely want OEMs to enable their machines to collect, store, and analyze the types of data needed for optimizing performance and accomplishing predictive maintenance (See Figure 1).

Some end users need their OEM suppliers to adhere to programming, design, and operational standards, a challenge for OEMs delivering systems to numerous different clients. However, adherence to industry standards and industrial communication protocols can lead to improved consistency and compatibility.

Digital transformation may not change the underlying equipment operation directly, at least not initially. While users want full access to all the data liberated by IIoT, they may have concerns about sharing this data with other parties, especially via the internet. Data sharing, especially with OEMs hungry to understand equipment performance in the field, may be acceptable to end users if mutual value is realized, such as improving asset reliability.

End users usually know the key performance indicators (KPIs) they want to see, but they may need help identifying what other data to integrate via IIoT, especially with regards to establishing valuable predictive maintenance capabilities.

Finally, to realize the full benefits of IIoT, users must converge their operational technology (OT) equipment with their IT infrastructure. These are under way, but it is not a given yet for all end users. OEMs and technology suppliers need to offer IT-ready solutions to ease this process.

OEM focus

OEMs are experts in designing and fine-tuning their machines. Some may be laser-focused on this goal and may therefore be challenged to fully understand how end users need to operate a collection of machines as a system. Nonetheless, every OEM will know the important “little data” available from their machines, which is needed to develop analytics such as overall equipment effectiveness (OEE) indications (See Figure 2).

Because OEMs typically produce large numbers of machines, and sometimes many models with a variety of options, they are naturally interested in establishing a standard automation platform for consistency and efficiency within their organization. A modularized automation hardware design and programming approach are usually a good fit for OEMs, but their internal standards may not fully align with those of their end user customers

OEMs can reconcile these issues by implementing platforms providing the deterministic control they need and supporting industrial OT as well as IT-friendly communication protocols. This ensures the automation platform can interact with any type of field device, while also exposing the resulting data to end users.

Of course, OEMs are also keen to obtain large amounts of real-world operational data so they can use it to improve their equipment designs and performance. Data from equipment in service for long periods of time can reveal insights simply not possible under limited testing conditions. Yet OEMs must be sensitive to the fact that end users will likely not want to supply data that could expose their competitive position. OEMs and end users can benefit from stronger collaboration in this area.

Edge computing solutions

Edge computing options offered by industrial automation technology suppliers enable end users and OEMs alike to take advantage of IIoT to improve their operations and equipment. Edge gateways and edge devices added to new and existing OT systems collect and transmit data to on-site or cloud-based systems. Making this data available is the first step toward optimizing operations and providing predictive maintenance.

An even more comprehensive option is to use edge controllers when automating new equipment (See Figure 3). Edge controllers perform deterministic control just like traditional industrial options, but they also integrate IT-friendly general-purpose computing. Therefore, edge controllers are an important way for end users and OEMs to achieve robust and reliable control, combined with secure and seamless integration of OT data with IT systems.

Edge controllers installed on-site can collect, store, aggregate and analyze data. Because they are located next to the data source, they avoid any latency or resolution issues that could affect results. By preprocessing in the field, edge controllers send only relevant data to higher level systems using efficient IT-based protocols, which minimizes bandwidth and upstream processing costs.

Concluding thoughts

Digital transformation and IIoT bring many new opportunities to increase productivity, improve efficiency and create new revenue models. Manufacturing end users, OEMs, and IIoT solution partners understand this and are building their long-term strategies to take advantage of these technologies and to differentiate themselves from the competition. Using the right edge computing platforms, OEMs can offer equipment that delivers the KPI, OEE, and predictive maintenance information that end users need to realize maximum value from their capital equipment.

Original content can be found at Control Engineering.

Author Bio: Silvia Gonzalez is a solutions development leader for Emerson’s machine automation solutions business. She is responsible for creating, developing, and driving solutions-oriented approaches for translating end user challenges into improved operational performance. Silvia holds a bachelor’s degree in Electrical/Electronic Engineering from Universidad La Salle, Mexico, has received a Digital Business Strategy certificate from MIT, and is based in Houston, Texas.