The fourth industrial revolution, with its emphasis on automation and digitization, doesn’t conjure up images of sweat, steam and steel like the 19th century version, but there’s no doubt about the power of this ongoing transformation.
This revolution, also known as Industry 4.0, relies heavily at its core on analytics and Internet of Things (IoT) data and functions to automate processes and maximize manufacturing efficiencies. This enables a range of new capabilities, like “smart” factories, where production procedures continuously self-optimize and respond to real-time organizational demands. The promise here is huge, but the prospect of incorporating the needed technology and expertise can be daunting.
As companies look for ways to capitalize on the gains Industry 4.0 makes possible, one of the easiest entry points is predictive maintenance. This application heads off system breakdowns by using deep analytics and IoT sensor data (sounds, vibrations, etc.) to foresee and fix problems before they happen.
Companies often see fast and significant value from predictive maintenance initiatives, and they are becoming more prevalent. A new report written by Pierre Audoin Consultants (PAC) and sponsored by Equinix indicates 55% of companies are at least piloting predictive maintenance initiatives.
But the report also found reluctance to move forward, including in the very country where the Industry 4.0 concept originated. Among the reasons: A hesitancy among established firms to invest in the needed technology as they protect revenues and profit margins. Many also don’t fully understand how to build a fully integrated data management strategy. But the failure to act puts companies at risk of being outmaneuvered by smaller, more agile companies with less to lose.
The truth is it doesn’t take significant investment to adopt predictive maintenance capabilities, but it does take time. A partner like Equinix offers access to agile global interconnection, leading analytics platforms and a variety of cloud services that can assist with data management and analytics. That can help companies get started.
A need, and a solution
Industry 4.0 was the name of a German government initiative launched in 2011 to advance computerized manufacturing. In the years since, the term has taken on the broader definition that describes the global trend of automation and data exchange in manufacturing technologies.
To us, predictive maintenance is the proverbial low-hanging fruit of Industry 4.0. Maintenance is a perpetual burden on industries across all sectors, and IoT-enabled maintenance is a way to substantially reduce or avoid equipment downtime, reducing costs while increasing efficiency and customer satisfaction.
The PAC report, which was based on interviews with 230-plus business leaders at European manufacturing and transport companies, reveals both the need for improved maintenance processes and the gains being seen by early adopters. Some key findings:
- 93% of companies describe their maintenance processes as not very efficient, indicating real room for improvement.
- 83% of companies plan to invest in predictive maintenance initiatives in the next two years.
- Nearly a quarter of companies, 23%, already report a tangible business impact from predictive maintenance initiatives.
Milos Milojevic, an industry analyst and co-author of the PAC report, said the percentage of companies already benefitting from predictive maintenance is promising and points to faster and greater adoption.
“It’s considerable in this area of technology, which is digital, which is new, which requires some change, in terms of managing the data,” he said. “It’s a number we expect to grow, definitely over the mid-term, but in the short term as well.”
But the PAC report also highlights a variety of challenges companies see with deploying predictive maintenance capabilities. A major concern is data security, since greater IoT adoption is sometimes seen as expanding the field of attack for cyber-criminals. Companies also say they don’t have the internal analytics capabilities needed to manage and find insight from the streams of data IoT and predictive maintenance will unlock. Another key worry is a familiar one – cost, in this case the cost of purchasing the technology required to enable predictive maintenance solutions.
Milojevic acknowledged the real challenges companies face in adopting predictive maintenance technology. But he added that in today’s highly competitive environment, the risks of being a late adopter may be greater, including bankruptcy.
“If companies don’t invest, they could potentially see increases in operating costs,” he said. “They could miss out on opportunities to get leaner and more agile in a competitive world where everybody is looking for every advantage they can find. If they don’t invest, they could be left behind.”
One related and striking finding of the PAC report is the relatively low percentage of companies (15%) generating business impact with predictive maintenance initiatives in Germany – where Industry 4.0 was born. The report cites a reluctance there to take on more data responsibilities, given strict regulations and general data privacy concerns – especially when processing customer data about product utilization obtained via IoT. We see additional factors, including an overabundance of caution and an unwillingness to overhaul existing structures.
The German Mittelstand (the country’s robust sector of small- and medium-sized businesses) is a long-term success story, and many members see no reason to change their approach. But they’re underestimating the threat from emerging companies willing to adopt new technology because they don’t have much revenue to lose. Established companies must accelerate digitization, or they risk being overtaken by new entrants. They must be willing to cannibalize their own revenue in the short term to invest in technology that prevents other companies from eating into their revenues in the mid- and long term. In addition, companies that hesitate to commit to new ways to solve old infrastructure problems and inefficiencies can miss out on innovative functions, services and products that improve the customer experience.
Companies everywhere, not just in Germany or EMEA, should be focused on enabling the market opportunities, products and services that Industry 4.0 makes possible. That requires access to new technology platforms, and that access is driven by interconnection, the private data exchange between businesses.
A platform for Industry 4.0
When it comes to ensuring that predictive maintenance works, companies can’t view it like they’re making a solo scoring break down a soccer field. Instead, it takes partners and a highly integrated team effort, because no company can master the challenges of the digital world alone. This requires a distributed edge computing model, with interconnection at its heart. Interconnection enables companies to quickly add partners to their ecosystem. It brings people, locations, clouds, data and “things” closer together at the digital edge. This proximity supports lower latency, better security, reduced network costs and faster data exchange. It optimizes the real-time data collection, analysis and insight that’s central to predictive maintenance technology – and so much of what Industry 4.0 will make possible.
Equinix has everything companies need to support Industry 4.0 initiatives. Platform Equinix expands across 200 data centers in 52 markets on five continents and is home to more than 1,700 networks. Companies can get close to the digital edge from everywhere. They can implement an Interconnection Oriented Architecture™ (IOA™), a proven set of best practices that enables the secure, low-latency interconnectivity essential to unlocking the capabilities of the IoT, even as those capabilities expand in a new IoT-powered industrial age.
Download this infographic on the PAC report to get details about predictive maintenance and a more interconnected future.
And to learn about predictive maintenance in action, see how Siemens, Teradata and Equinix combined to enable these capabilities with remarkable results.