Smart machines can give OEMs new asset visibility to help reduce end-user downtime, meet performance guarantees and improve machine designs.
By Mike Wagner, global segment lead for Packaging, and Todd Smith, product manager, Rockwell Automation
Digital transformation is providing manufacturers new insights into their operations with smart machines and equipment that are connected throughout the enterprise. Many original equipment manufacturers (OEMs) also would benefit from tapping into these increasingly connected systems. Machines are getting smarter, and OEMs can see what manufacturers are beginning to learn about their facilities. These new levels of visibility can promote asset performance and help simplify meeting contractual obligations.
For example, OEMs that monitor a smart machine’s performance or identify the critical process anomalies will be able to expand support they provide. Rather than working with their customers proactively to prevent issues from happening, they often physically send help to a customer’s site. The result? Longer downtime for customers and higher travel costs for OEMs.
All of the smart machines using connected technology in the plant are limited by keeping OEMs out of the digital ecosystem.
Fortunately, cloud-based machine analytics present an opportunity for OEMs to get real-time and historical insights into smart machines or equipment from anywhere. This can help them reduce customer downtime, improve collaboration, meet performance guarantees and even create new revenue streams.
Skip the Do-It-Yourself Perils
Remote analytics isn’t an entirely new concept for machine and equipment builders. Some OEMs already do this. However, it typically involves building remote-monitoring and analytics capabilities in-house from the ground up, which can be a time-consuming and costly process.
Most OEMs, for example, don’t have the IT staff or knowledge required to deliver critical aspects of remote analytics, such as secure remote access, cloud-based data collection and database management. As a result, they take on the upfront costs to acquire the skills needed for developing a machine customized to their customer and supporting the equipment long term.
A simpler and more cost-effective approach is available with software-as-a-service applications. By providing analytics in the cloud, OEMs acquire real-time and historical insights into how their equipment is operating from anywhere, so they can collaborate with customers to help reduce downtime.
The technology available to OEMs allows them to embed a gateway device onto their smart machines or equipment and connect with minimal configuration between the device and selected controllers. That provides access to information securely via prebuilt dashboards.
Information Creates Opportunities
When OEMs gain access to real-time performance information for their smart machines, they can begin serving customers in new or better ways.
Service and support are key opportunities. Rather than traveling to a customer’s site if equipment fails, smart machines let OEMs troubleshoot and diagnose the problem remotely. They also can collaborate with the user and resolve the issue in a timely manner. As a result, the OEM can help its customer more quickly and reduce travel costs, and the end user can realize higher uptime and output and lower maintenance costs.
Performance guarantees are another big area of opportunity for OEMs. By collecting data and analyzing performance analytics, such as overall equipment effectiveness (OEE), OEMs can collaborate with their users to optimize a smart machine’s operation and help it reach required performance levels. Additionally, cloud-based analytics provide a single, shared version of the truth about a machine’s performance.
Data collected over time also can be used to reshape service agreements. After an OEM has collected enough performance data and gained a solid understanding of what a machine can do, it can begin offering a range of agreements that promise improved performance.
Also, OEMs can use cloud-based analytics to continually improve machine designs. Whether looking at multiple machines deployed across one customer’s sites or one machine deployed across multiple different customer sites, the OEM can identify deviations in performance, trends and patterns and best practices. They then can convert that data into engineering changes to design better-performing, more reliable machines.
Bigger Roles for OEMs
Access to cloud-based analytics also can lead to new business models and help carve out bigger roles with current customers.
For example, some large global manufacturers are beginning to transition away from in-house teams that specify and purchase machines or equipment. Instead, they can send production requirements to an OEM that then is responsible for designing and delivering the right solution to meet those requirements. OEMs are shifting from being machine providers to being productivity providers.
After OEMs have gained access to performance data, they can supplement their customers’ in-house teams’ knowledge, especially as companies struggle to find and retain skilled maintenance workers.
For instance, an OEM could take over responsibilities for monitoring machine or equipment performance, and for servicing them as needed, with guaranteed response times built into their support contract. The OEM also could use the information it collects to begin providing proactive maintenance and training to help users get ahead of failures and operate more effectively.
Let There Be Light
Cloud-based, smart machine analytics are revolutionary — they give OEMs access to insights that have been into how their machines and equipment are performing and create new opportunities to serve their customers better. Analytics also are central to the larger role that smart machines are playing in end users’ operations to help improve asset utilization and time to market.
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