New shop-floor data collection and analysis tools can ease the strain of digitizing factory operations in the IoT age
As the move toward a more connected manufacturing industry gains momentum and manufacturers start collecting factory-floor data, the need for fast, efficient data analysis becomes ever more critical. Data collection and analysis tools are paramount in the digital manufacturing/Industry 4.0 era, and manufacturers are gearing up with new solutions to help them collect, manage and analyze factory-floor data more effectively, taking advantage of key performance indicators (KPI) such as overall equipment effectiveness (OEE), machine uptime, machine/spindle utilization, and other metrics.
Many manufacturing data collection and machine monitoring options are available, with most offering at least some basic manufacturing metrics analytics in shop-floor monitoring packages or manufacturing execution software (MES) systems. In some cases, automation companies are teaming up with established IT providers, such as the recent partnership announced by automation supplier ABB Inc. (Cary, NC, and Zurich) and Hewlett Packard Enterprise Co. (HPE; Palo Alto, CA) that will combine ABB’s industrial automation and operational technology (OT) expertise with HPE’s hybrid IT experience and software portfolio.
Teaming Up OT with IT
In the ABB/HPE partnership, announced in November 2017, ABB’s Ability digital offering will be combined with HPE’s hybrid IT solutions. Ability solutions will run on hybrid platforms such as the HPE ProLiant for Microsoft Azure Stack, with deployments at customers’ preferred locations in industrial plants and datacenters, or in the Microsoft public cloud, as needed to meet requirements for performance, security or cross-site collaboration.
The partnership moves computing resources closer to where they’re required, using “edge computing.” ABB and HP will integrate Ability datacenter automation, which controls and monitors infrastructure, with OneView, HPE’s IT infrastructure automation software. “Quite frankly, we can’t do this on our own; we need a partner for this hybrid, and OT/IT is needed,” said Dublin-based Ciaran Flanagan, group vice president and head of global datacenter solutions for ABB. By combining IT and OT, largely siloed today, “we think there’s huge opportunity, and it’s maturing fast,” he added.
Offering users secure edge datacenters for remote industrial environments, the ABB/HPE partnership also uses Rittal rack infrastructure with ABB’s industrial power distribution systems and HPE’s software-defined infrastructure and services. “The protocol layer is very different in OT than in IT,” observed Volkhard Bregulla, HPE vice president, global manufacturing industries. “The IT side is quite ahead.” The ABB-HPE solution will be available in the first half of 2018.
Collecting, then Analyzing Shop Data
On the shop floor, many options exist for monitoring and collecting data, most offering at least basic machine analytics and some sophisticated shop-floor analysis.
When monitoring machines, shop managers first need to know when particular machines are running, or if they are down or offline. It is vital to know when the machine is under program control, according to David McPhail, president and CEO, Memex Inc. (Burlington, ON). “We’re agnostic with it when it comes to how you connect,” he said.
With Memex’s MERLIN (Manufacturing Execution Real-Time Lean Information Network) Tempus platform, process and discrete manufacturers can connect their machines in either on-premises or cloud environments. MERLIN Tempus is an MES software that features dashboards and can connect using FANUC FOCAS, MTConnect, OPC and other protocols for linking machine tools via the Internet.
For legacy, non-intelligent equipment, Memex developed an MTConnect interface. “There are 16 digital input signals from the machine,” said McPhail. “There are three data streams: from the equipment; from the human capital, something that a human has control over [and] that a machine can’t tell us; and from outside solutions like ERP.”
Users can run the Tempus MES, which is a Manufacturing Operations Management (MOM) portfolio, on the shop floor to check machine status, McPhail said. “Typically our people will run our software on a tablet and walk about the shop floor. Let’s say an operator is having trouble with a part; you’ll get a message, ‘Support the Internal Customer.’ That turns the operator from a reactive to an active mode.
“There’s no custom programming,” McPhail continued, and the system includes analytical tools. “The data collection piece is foundational. The business case we’ve chosen is OEE, but you could insert TPM [Total Predictive Maintenance] and many others. It essentially calculates the financial impact of poor performance.”
Memex is developing an FOEE (Financial OEE) module for release later this year that will calculate for shops the costs of running equipment at less than optimal settings. The module will show shop managers “right now you’re running at less than top performance, by a delta of this much, and every hour that you run [at that level] costs you that much,” McPhail said.
Monitoring a Must, but Avoid Analysis Paralysis
A big question for shops setting up data monitoring/analysis is just how much data should be collected. While the industry hypes the need for “Big Data” analysis, for the average shop less may be more.
“We work with our customers to understand the equation. The how is a known entity. The why, the business case that underpins it,” is what Memex works on, McPhail said.
While some companies work on massive Big Data issues involving simulation environments, such as CAE data, in most shops that is not the case. “Big Data, we call that digital exhaust,” McPhail added. “If you take a Mazak machine, if you subscribe to every tag, that [amount of data] will overwhelm you. Do you really need to know every data point?”
Another developer, Predator Software (Portland, OR), aims its Predator suite of shop-floor monitoring applications at everything from two-man shops to large manufacturing organizations, according to Mike Rogers, Predator Software director, automation and OEM relations. “Predator MDC [machine data collection] is our core product for monitoring, and with over 20 different protocols, from Mori, OPC and OPC/UA, we can monitor anything on the shop floor,” Rogers said.
Collecting and analyzing data is more accepted by shops today. “It’s going to become the hottest topic,” Rogers said. “Everyone wants it and not everyone has it. … Large corporations want Big Data. The little guy [needs to] learn to walk before they run. You’re going to get overwhelmed otherwise.”
A key is convincing customers to focus on simple things, he noted, such as “will the machine cycle? Is it sitting? Is it running? … It can be an overwhelming process,” Rogers said. “One of the problems I run into is finding the champion in the organization that will follow it through.”
Predator’s MDC solution features an intuitive interface, making it simple for users to get started, Rogers said. “MDC has [a built-in] charting and reporting engine. If you run the permutations, we have somewhere between 20,000–30,000 reports.” MDC is one of Predator’s eight core products aimed at shop-floor data collection and monitoring, control and communication. The products all work off one database, and when customers buy MDC, they get the DNC communications module as well. Predator’s software supports Microsoft’s Access database, used by many smaller shops, Rogers said, and it also supports Microsoft SQL Express, SQL Server, and Oracle databases. The Predator software can operate either on premises or on the cloud.
Follow the OEE
Shops both small and large need to pay close attention to the OEE metric, which can allow machine operators and managers to optimize efficiency. Visualizing the process, making it easy for shop personnel to quickly see, understand and react to changing conditions, is critical.
“We offer both the data collection and the data analysis sides, and we can either provide that a la carte or as a full solution,” said Jeff Price, executive vice president and general manager, 5ME LLC (Cincinnati). With 5ME’s Freedom suite, users get software plus available hardware to link and control a variety of machines.
“Our team has a long history with OT-type devices, and we have interfaces or adapters to almost any asset in the plant, often on the CNC controller,” Price added. “When we have legacy controllers, we also have a hardware appliance” to connect to the network. Along with Freedom eLog software, 5ME offers data visualization with customizable smartboards displayed on flat-screen TVs, Price said.
“With the smartboard technology, we have dashlets or wizards—a collection of data with pie charts and bar charts—that you can save into smartboards,” he said. The smartboards use Raspberry Pi embedded systems to help boost processing speed where the data is most needed. “We’re using Raspberry Pi with smartboards for driving visualization to the shop floor,” Price said. “For years in automotive plants we had Andon boards, but those are pretty rigid.”
Freedom servers, located on the cloud or on premise, are where the data crunching happens. With the connectivity offered, customers can build on gains the industry has already made, Price said, such as lean manufacturing and six sigma. “We short-circuit that whole process,” he added. “Most of our customers will see a minimum 20% productivity improvement with OEE, which is comprised of availability, performance, and quality. Availability is are you running [at optimal levels], performance is are you producing at the levels you should be, and quality is purely a yield-type situation.”
With the OEE metric alone, shops can make big performance gains, he said. “Availability is where the big gains are. The initial improvements are 10–20% in 30 days.” The Freedom suite is a software install, over the web. “It’s a light IT footprint, harnessing the power of the processing on controllers. We can do 100 machines in four weeks.”
Price added that shops must winnow the data down to what’s most important. “It depends on the analysis tools; we call it drip—data-rich, information-poor,” he said. “If your systems present the right metrics, there’s a ton of improvements to be gained.”
Taking that First Data Step
Not all shops, particularly smaller ones without big OT/IT budgets, are easily convinced of factory data monitoring’s value. “People are trying to understand their baseline,” Price said. “The things like how often is your equipment running? There’s still a gap—our role is to bridge that gap. They don’t understand it.” 5ME customers like Textron, Bell Helicopter, Caterpillar, Schlumberger, and Cummins, are interested in Big Data, but they don’t all have a use case for it, said Price, although he sees one such use in predictive maintenance.
“Data collection and analysis is essential to any modern manufacturer—from small shops to corporate enterprises,” said Jody Romanowski, CEO of Cimco Americas Inc. (Streamwood, IL). “Accurate real-time data helps identify areas that can be improved, whether they are equipment, processes or personnel. That data is required to reach significant improvements.” Cimco’s shop-floor offering, MDC-Max, is a data-collection solution providing structured and automated production monitoring. The scalable MDC-Max can benefit both small shops and large manufacturers, Romanowski said.
“As customers consider real-time data analysis, they are often a bit overwhelmed by a whole range of data points. Our approach is to keep the project simple initially, analyzing three to five data points to secure early success,” she said. “Manufacturers can then start analyzing further data points gradually. In an OEE context, all manufacturers struggle with a complete and consistent analysis of the quality parameter.
“We don’t recommend a Big Data approach to collecting machine data,” Romanowski continued. “We advise keeping it simple and reaping the low-hanging fruit initially, then building upon experiences and the challenges overcome. When companies operating shop floors all over the world strive to get a consistent overview globally, including across business units, the project complexity will increase dramatically, though not necessarily from a Big Data perspective. Instead, complexity normally grows from handling legacy machines/systems and different procedures and/or cultures. That puts further emphasis on keeping first phases as operational and simple as possible, while keeping focus on tactical goals such as ERP integration in further stages of the project.”
For shops that collect the data but don’t adequately analyze it, new analysis tools may offer an edge. “Often, their current software is too limited, rigid or complicated,” Romanowski said. “MDC-Max is flexible enough to scale and meet the future needs of our customers. The data must be easily accessible on any device and it must be aggregated in a meaningful way—such as in reports and real-time dashboards.”
At a Cimco customer outside Tianjin, China, Romanowski said the manufacturer had a key machine that was a productivity bottleneck, affecting other machines. “Upon putting a simple MDC-Max system in operation with a limited number of data points, the manufacturer experienced a 30% higher utilization rate on that specific machine,” she noted, “thereby increasing productivity both from reducing that specific bottleneck and by increasing productivity on all other machines as well. The estimated payback time for the investment, in this case, was less than four months.”