In this “Big Data” era, more than 50% of data originates from automation
Automation has been an important tool for increasing efficiency and output.
For the last 40 years in the industrial space, automation has been one of the most important tools for increasing efficiency and output. Consequently, industry has become very intimate with the operation, maintenance and management of automation. With particular emphasis on how these systems take advantage of networking to become more efficient.
But automation is just one element in a portfolio of plant- and enterprise-level disciplines which, when they converge, exponentially increase production agility and innovation.
This convergence is fueled by network- and connectivity-centric technologies that break down traditional walls and eliminate silos. Increasingly sophisticated integration and collaboration is establishing an intelligent manufacturing ecosystem that extends from the production floor to the top floor.
Ultimately, and most important, the convergence revolution is protecting and maximizing manufacturing output. This article looks at multiple “intelligent manufacturing” disciplines merging with each other in a seamless, barrier-free communication and production environment that enables operators to produce more efficiently, remove costs, and optimize an increasingly lean workforce.
Security is probably the single biggest challenge that manufacturers face today. You might wonder why security rises above any number of complicated automation and networking elements. But we’re not talking about the difficulty factor in guarding intellectual property, or protecting the network against cyber intrusion. In the convergence context, security represents the most significant challenge because it is inseparable from the ability to produce. Automation makes production more efficient. But securing that automation determines whether the production line stays online, with consistency, and takes advantage of the productivity upside that automation enables. Given the four-decade concentration on employing automation to achieve productivity gains, it’s natural for the automation discipline to fully embrace the security discipline. Ideally, in the manufacturing zone, the two converge to operate as a single discipline.
The justification to deploy plant-floor energy management differs from the productivity-driven reasons to automate production. Energy management aims to reduce one of the largest variable costs in the profit equation: the consumption of electricity and other energy sources. Automation clearly is the right place to search for energy cost reduction. Production lines are responsible for the largest portion of the overall energy expense. But traditional energy reduction – often keyed to reducing the plant’s monthly utility bill – frequently results in looking at specific scenarios in isolation. Focusing, for example, on the energy appetites attached to conspicuous, high-use systems like robotics, a curing oven, or a drying tower.
The kilowatt draw that puts a drying tower squarely in the energy-reduction crosshairs is impossible to discount. But relative to the machine- and device-level data capture emerging on today’s networked plant floor, swapping out a piece of low-efficiency equipment may amount to simply nibbling at the edges of what is truly possible today in energy management. Monitoring energy use at the heart of automation – think machine level, enterprise-wide granularity – enables energy management focused where bottom line contributions are greatest. Not simply at the meter where power enters the building.
On today’s production floor, in the emerging “Big Data” era, more than 50% of the data provided to the rest of the enterprise originates with automation equipment. Managing energy utilization is a good example of why the industrial compute discipline is inseparable from effective modern-day plant automation. Industrial compute includes managing the operations-critical information from databases, virtualization and software applications that must converge with automation to be distributed throughout the enterprise and beyond. That’s how raw data can become useable information. It’s how decisions about saving energy ultimately evolve into decisions on fundamental changes in how a production plant operates. Plant operators, for example, might consider a data-driven, profit-serving analysis that compares the productivity tradeoff in employing people during a night shift (at off-peak utility rates) versus day-shift operations burdened with peak electricity costs.
The energy information example above confirms that despite dramatic advances in automation and the value of Big Data, people ultimately make decisions that drive production processes. Executing a process or system improvement still requires a human interpretation in response to the data. At the same time, there are far fewer factory employees – each with much more to do – when compared to headcounts and work roles 20 years ago. Yes, today’s plant floor employees have more support in the form of business and automation systems. But progress across quality, cost and productivity metrics depends, more than ever, on employees accessing the information they need to do their jobs seamlessly, in real-time, and wherever they are on the plant floor.
When a maintenance technician finishes a job, he doesn’t want to return to the maintenance briefing room to pick up the next work order. He wants to access the order where he stands. A production manager who needs to make a decision does not prefer information relayed via telephone or radio. He expects direct access to information so he can cross reference the data, construct and evaluate options, and make the correct choice for the enterprise. This leads to the next important topic.
The discussion on changes in the way people work on the production floor is incomplete, of course, without acknowledging the impact – and the demands – of mobility. Optimizing efficiency and productivity requires information moving to people rather than people moving to the information. Mobility merges with security because sending data to someone with mobile status requires ensuring the transmission is secure. Mobility merges with automation because, as we’ve seen, that is where a significant amount of critical operational information is sourced.
The lean staffing that coincides with greater systems and process complexity also means there’s no guarantee you can access an on-site resource who is expert in a specific technology or piece of equipment. Particularly in connection with a still-emerging discipline of energy management, where there is an even smaller pool of local resource. The answer to supplementing the manufacturing zone workforce is tapping remote assets, services and expertise. Critical, strategic resources positioned outside the immediate facility, but still within the total enterprise. Or assets contracted from the ranks of a key machine builder.
The most powerful sensor that a plant operator can deploy in the manufacturing zone is the human eye. Although that eye is located 2000 miles from a plant floor, the remote resource can observe the production process or system through a secure video feed that enhances the expert’s efficiency and productivity. Reducing the time required to work on your system lowers the support cost. It also protects uptime because a remote asset can work on a production system issue while the line is not running.
The connectivity that enables benefitting from the expertise of remote assets is also driving the integration of separate physical locations. Automation at the start of the era 40 years ago involved automating individual machines. There was a human loading the machine, and another unloading. The next phase, progressing to line-level automation, allowed multiple machines to operate together in a single, automated system. But an operator still had to man the control panel.
Today, we separate people from the equipment whenever possible. While still leveraging the systems and process information assets that management uses to optimize productivity, improve quality and reduce costs. A lift station providing effluent for a water treatment plant should never be manned. Historically, however, the information attached to that standalone system was available once a day. Or, in a best-case scenario, once each hour. Within today’s connected and convergent enterprise, that station is an intelligent remote asset interacting with the rest of the water treatment plant continuously in real time.
In a similar scenario, the rise of remote-asset productivity – and breaking down the limitations of time and distance – avoids the increased cost of employees that must be compensated in accordance with severe duty. Perhaps as part of the workforce staffing an oil rig in an ultra-cold, severe-duty location. It is another example of remote assets and support merging with secure automation systems and big data to create intelligent production from formerly distinct manufacturing and enterprise domains.
Industrial IP is the Forward-Focused Backbone
Convergence does not happen by magic. The potential promised by Internet-powered integration can only achieve traction with the power of the correct technology platform behind it. Industrial Internet Protocol (IP) comprises the network technology, infrastructure and practices to support the harmonious coexistence and interoperability of the disciplines discussed here. The stronger the IP presence, the greater the potential for converging operational systems in a holistic solution that can optimize manufacturing output.
While it’s a given that networking infrastructure and technology plays a critical role in convergence, we’re not nearly as certain about the top-end potential promised by intelligent manufacturing. The accelerating nature of the “Internet of Everything” indicates we may have only scratched the surface of what can be achieved through the connected enterprise.
Given that reality, realizing the potential in convergence is best served by investing in and adopting a unified, IP-centric networking infrastructure with proven abilities to scale up, expand and embrace the intelligent manufacturing future.