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Industrial digitalisation

We explore how back-office IT is being applied to industrial machines

The tools and techniques IT departments have mastered to manage diverse technological infrastructure are now being applied to manage machines, in what some experts refer to as Industry 4.0.

PwC’s Industry 4.0: Building the digital enterprise report, published earlier this year, looks at how industrial companies are creating digital services to deliver a competitive edge.

IT leaders need to be at the forefront of these initiatives, to position the IT function as key to operations, rather than a back-office support function.

According to the PwC report, IT leaders should develop an agile IT function that can respond flexibly to business demand. “By focusing on creating working solutions and responding to new requirements in an agile way, an agile IT function helps you continuously improve services,” notes PwC.

PwC believes the other core technology capability is likely to be internet of things (IoT) management – monitoring, controlling and orchestrating large amounts of diverse devices and providing central IoT services.

This includes providing functions (via software upgrades), communications standards and connectivity, and ensuring an appropriate level of security.

Seize the digital opportunity

If enterprise resource planning (ERP) and supply chain management (SCM) software drove efficiencies in manufacturing, analysis of data collected from internet-connected machines is set to revolutionise industrial processes, putting IT at the core of operations.

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The GE Predix platform is now positioned as an operating system to run industrial machines more efficientl.

Big data is a fitting match for IT operations management, where the endless logs and events finally add up to more efficiency and less troubleshooting

At the Minds+Machines event in Paris in June, GE CEO Jeff Immelt urged delegates to seize the opportunity digitisation offers industrial companies. “As a CEO, if you wait for a tailwind you’ll be waiting for a long time. I have worked at GE for 34 years, and this is the biggest transformation I have seen,” he said.

Immelt pointed out that industrial companies need to achieve greater levels of productivity. For these companies, even small, almost insignificant, levels of improvement can have a profound effect on the bottom line. For instance, he said, a 1% improvement in asset utilisation could represent $800m.

According to Immelt, combining analytics fed in from sensors on machines in the real world with domain expertise could enable industrial companies to improve productivity.

GE has built a software platform called Predix to analyse machine data. Bill Ruh, CEO of GE Digital, says that by bringing all data from an industrial plant into a data lake, then applying statistical analytics, industrial companies are able to identify trends and anomalies.

Predix uses domain expertise to support decision making and help deliver business outcomes. For instance, information processed by Predix can be used to route work automatically, making people more productive in their jobs. It is about going after a 1% drive to greater productivity. In industrial systems this fractional improvement can represent savings of billions of pounds.

A platform approach

Pitney Bowes specialises in high-volume mailing machines designed to send out thousands of letters per hour. Typically, its inserter machines are used for large mailing operations, such as when a bank or insurance firm sends out paperwork to its customers. The machines make sure the right letter is put in the right envelope and sent to the right person.

Over the past decade, Pitney Bowes has built a software as a service (SaaS) and data platform to digitise its business.

“We have $1bn digital revenue out of $3bn overall revenue,” says Roger Pilc, executive vice-president of innovation at Pitney Bowes. “Similar to Uber and Airbnb, digital technology at Pitney Bowes doesn’t replace physical assets, but it does make them more useful.”

So how does an inserter machine move into the digital age? GE and Pitney Bowes share similar ideas of how connected devices combined with analytics can help customers address machine efficiency and productivity, which in turn helps them improve revenue and profitability.

Two years ago, says Pilc, Pitney Bowes began talking to GE about how it might be able to offer consulting and information services. Its customers wanted benchmarking, he says, to see how well their mailing operations performed against other organisations in their sector.

GE’s Predix platform supports predictive maintenance for industrial machines – from jet engines and turbines to power generation plants – and Pitney Bowes wanted to investigate whether Predix would work equally well in the high-volume mailing business.

“GE didn’t have experience of mail machines before it met us, but it knew about asset performance management. It had core disciplines that could be modified to our world,” says Pilc.

“When we got to know Bill Ruh, his ideas resonated with us. We saw Predix as a fantastic platform. Customers want business outcomes.”

One goal for Pitney Bowes was to investigate how the GE Predix analytics platform could be applied to reduce unplanned downtime and achieve 100% utilisation.

Pitney Bowes developed a suite of digital services. One of these, Clarity Advisor, is designed to combat unplanned downtime. The company collects data from its customers’ mailing machines, which is then fed into applications built on Predix.

Machine and employee productivity is another area developed through Pitney Bowes’s digital strategy. “Clarity Optimizer gives customers the analytics to drive increased productivity of operators and machines,” says Pilc.

He gives the example of one Clarity customer that has improved the efficiency of its mailing operations. The customer previously found it was only attaining 60% operator efficiency from the mailing machines. Pilc says Clarity Optimizer provided greater visibility of operations, such as checking the process of switching between different job types. It recorded sources of unproductive time and prioritised them, which allowed the company to provide relevant operator coaching.

A third Predix-powered application, Clarity Scheduler, automates placement of the right job on the right machine at the right time. Using Excel for workload and capacity management means  changeover time (when the machine needs to be switched over for a new job) is lost time, says Pilc.

“The combination of capacity planning on the machine and scheduling the right job on the right machine allows us to make optimal use of the factory,” he adds.

IT best practice for machine management

Scheduling and capacity planning have analogies in IT. Prior to Pitney Bowes, Pilc spent 10 years in IT management, heading up the datacentres at two software providers. “Those disciplines that have existed in IT are now being used in industry,” he says.

There are economies of learning and scaling that can be applied in an industrial setting, in a similar way to how DCIM is used to manage datacentres, he says.

In fact, GE recently repositioned its Predix platform as an operating system for the industrial internet.

“We are building an open platform, where GE’s 14,000 developers can collaborate with our customers and partners to create new applications,” says Ruh.

Pitney Bowes is one of the third parties creating its own applications on top of Predix, using IT to optimise operations at its customers’ premises.

In this age of operational IT, there are new pioneers providing software platforms and applications. These organisations, like GE and Pitney Bowes, have not traditionally been associated with IT. And more organisations are set to join them as Industry 4.0 gains momentum.

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