Digital transformation is providing manufacturers new insights into their operations with smart machines and equipment that are connected throughout the enterprise. Many OEMs would also benefit from tapping into these increasingly connected systems. Machines are getting smarter and OEMs can add further levels of insight into what manufacturers are beginning to learn about their facilities. These new levels of visibility can promote asset performance and 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 the support they provide. Rather than working with their customers to proactively 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, the days of working in the dark are over. 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 is not an entirely new concept for machine and equipment builders. Some OEMs already do this today. But 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, do not have the IT staff or expertise 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. OEMs are looking to standardized, cloud-based analytics to gain new levels of insight into their machines. By providing analytics in the cloud, OEMs gain 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 simply embed a gateway device onto their smart machines or equipment, and connect with minimal configuration between the device and selected controllers. That is all it takes to begin securely accessing actionable information via prebuilt dashboards.
Information Creates Opportunities
When OEMs gain access to real-time performance information for their smart machines, they can immediately begin serving customers in new or better ways.
Service and support is one key opportunity. Rather than traveling to a customer’s site if equipment fails, smart machines provide OEMs the opportunity to remotely begin troubleshooting and diagnosing the problem. They will also have the ability to collaborate with their customer and resolve the issue in a timely manner. It’s a win-win: the OEM can more quickly help its customer 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. By collecting data and analyzing performance analytics, such as OEE, OEMs can collaborate with their customers to optimize the performance of a smart machine and help it reach required performance levels. Additionally, cloud-based analytics provide a single, shared version of the truth about machine performance.
Data collected over time also can be used to reshape service agreements. Once an OEM collects enough performance data and gains a solid understanding of what a machine is capable of, they could begin offering a wider range of agreements that promise higher levels of performance.
Last but certainly not least, OEMs can use cloud-based analytics to continually improve their 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 can then convert that data into engineering changes, and ultimately supply customers with better-performing, more reliable machines.
Bigger Roles for OEMs
Access to cloud-based analytics can also lead the way 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, who is then responsible for designing and delivering the right solution to meet those requirements. OEMs are shifting from a machine provider to a productivity provider.
Once OEMs gain access to performance data, they can supplement the expertise of their customers’ in-house teams, especially as companies struggle to find and retain skilled maintenance workers.
For example, 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 customers 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 existed outside their field of view for decades. They empower OEMs with instant insights into how their machines and equipment are performing, and new opportunities to better serve their customers.
But analytics are also central to the larger role that smart machines are playing in end users’ operations to help improve asset utilization, time-to-market and more. OEMs that are not supporting their customers with a digital transformation by providing smart machines and cloud-based services not only risk missing out on business opportunities, they risk being left behind entirely.
