Emulation, simulation, modeling—the process of using software to replicate the behavior of one or more pieces of industrial hardware—has been a part of automotive manufacturing for a long time. For example, emulation for logic validation, also referred to as control system simulation or virtual commissioning, was developed by General Motors in the early 1990s. In the aerospace industry, offline software is well known for integrating thousands of sub-assembly parts into larger systems for a faster production process. It’s a complex and evolving area of industrial engineering with a laudable goal: to provide a way for control engineers to validate controller logic and human-machine interfaces (HMIs) prior to system installation, thereby improving quality and speeding up system commissioning.
Today, the science and tools behind virtual commissioning technologies have evolved enough for other industries to take notice and start reaping the benefits. Procter & Gamble, for example, now uses simulation testing to cut commissioning time in half. Packaging machine makers are also using it to improve packaging line operations.
“The automotive industry embraced virtual commissioning and simulation early, but they have had difficulties with it,” says Dick Slansky, senior analyst for PLM at ARC Advisory Group. “General Motors and their Conveyors, Control, Robotics & Welding (CCRW) group originally worked to get Dassault Systèmes’ Delmia factory virtual commissioning [software] to work with their equipment, and they had mixed success.”
Systems thinking
Virtual commissioning’s challenges have not deterred automotive companies, however. Volkswagen, for example, “is on a mission,” says Slansky. “The German automaker wants to take over the world and have a common automation system for the whole lifecycle of their design—including the build, operation, maintenance” of their machines.
“Virtual commissioning really has evolved towards systems thinking, not just pure control simulation tools,” Slansky adds.
Though simulation software originally targeted control applications like robotic spot welding on an assembly line, a larger systems engineering approach is taking hold now. For example, automation vendor Siemens, through its Siemens PLM division, offers a mechatronic concept designer platform that embraces a multi-engineering discipline approach.
Siemens’ mechatronic platform leverages simulation tools to provide a concurrent and connected design environment. A product design would start with a mechanical design while electrical engineers work at the same time—in the same software environment—on their designs. This would impose certain constraints on the mechanical design in real time. The interconnected design process would also have to meet software constraints on the overall design.
That systems approach involves a lot of upfront engineering design—something that has not historically been done in some segments, like downstream food and beverage packaging applications. There, plug-and-play machines are preferred, and customization rarely exceeds 20 percent. Given that reality, can virtual commissioning really work in the food and beverage industry?
“I’ve talked to many engineers at original equipment manufacturers in food and beverage, such as R.A. Jones and Tetra Pak, and asked whether virtual commissioning is a possible fit,” says Slansky. “OEM engineers would use it, but with a big caveat: If a machine builder for a large beverage filling line has to spend more time upfront building via machine simulation, it might not be profitable.” However, legacy food plants with their hard-to- reach production data are candidates for such a digital manufacturing systems approach, he says. “It’s an aid in implementing line and plant optimization.”
Packaging line simulation
Recently, a Midwestern food manufacturer needed to increase production for three packaging lines as demand increased for its product. The overriding problem resided in its legacy equipment for the packaging lines, but the challenge was identifying the specific equipment bottlenecks and the investment needed to fix them. Burns & McDonnell, a Kansas City, Mo.-based design and engineering firm, was brought in to help. They simulated the existing packaging line operations using Rockwell Automation’s Arena software. Arena simulation uses what-if, deterministic modeling with single-point estimates; uncertain variables in the packaging line are assigned a “best guess” estimate.
Using existing production data, Burns & McDonnell simulated these three packaging lines and discovered that some equipment was underperforming. Burns & McDonnell captured overall plant capacity, production schedules, equipment reliability data, and equipment rates and capacities to create the simulated line.
“Our simulation software enables a company to simulate and leverage a holistic evaluation that’s able to predict overall equipment effectiveness (OEE) based upon available historical data and other information like resource availability, raw material supply, line capacity and storage/shipping processes,” says Rob Kranz, director and general manager of Arena Software for Rockwell Automation.
According to Burns & McDonnell, production data was then used to build a range for each piece of packaging equipment. “The simulation software accurately modeled 150 days of plant floor output, which was compared against six months of historical plant- floor data,” says Abbey Hatke, industrial engineer for Burns & McDonnell. “These results included both equipment reliability and line reliability, and were within 0.25 percent of each other— confirming that our team had created a realistic plant environment in which to test its simulations.”
After sifting through plant data, the food manufacturer focused on 42 different scenarios to test and evaluate. The bundler, bottle capper, tray former and palletizer were specifically targeted for individual analysis. Burns & McDonnell was able to capture the operating range for each piece of equipment and establish a performance average for 120 days of production.
The result was the food company avoided a costly rip-and-replace of the packaging lines and instead replaced only specific pieces of equipment. The total cost for the three new lines reached $18 million, but it produced 80 percent less downtime. This delivered the much-needed 10 percent increase in production capacity sought by the company, according to Burns & McDonnell.
Charlie Gifford, chief manufacturing consultant at the Intelligent Manufacturing Institute and chair for the ISA-95 Manufacturing Operations Management (MOM) working group, spoke about Procter & Gamble’s advocacy of simulation software and the systems engineering approach.
“Under corporate group leader Dave Chappelle (now retired), the company successfully ran simulation testing to reduce commissioning, equipment and line specification by half,” Gifford says. “Through simulated testing via data-set building, Procter & Gamble would run this data through a PLC to do a failure effects mode analysis and see if logic could do what it was supposed to do for automation systems.”
Alan Beaulieu, economist and president of the Institute for Trend Research, said that this decade should “be a good decade for automation technologies,” noting that strong manufacturing investment is evident with recent economic data pointing to “growth for the manufacturing sector in 2015 and 2016.”
One benefactor of this increased automation investment has been system integrators for robotic work cells. Robotic applications have trickled farther downstream in some industries, including food and beverage, semiconductor and pharmaceuticals. These kinds of advanced SCARA robot applications mean more opportunity for use of simulation.
Davenport, Iowa-based Genesis Systems Group is a systems integrator that has executed a range of robotic applications, including welding and mechanical assemblies, non-destructive testing and material handling. The company’s simulation department is relatively new, but has seen tremendous growth in the past four years.
“Offline programming allows you to minimize downtime and switchover from one production run to another,” says Mike Jacobsen, director of product and OEM marketing for Genesis Systems. “A lot of other industries, such as automotive, all-terrain vehicles (ATVs) or construction equipment, are using simulation to decrease time-to-market for multiple products.”
Genesis uses Dassault Systèmes’ Delmia V5 universal robotic simulation software for workcell conception and layouts. The software also provides a quick and efficient method for the concept testing of robotic offerings from various OEMs. Genesis, on average, has reduced retool time during the build phase by up to 30 percent, and reduced design changes by 65 percent, says Jacobsen.
For automotive and other clients, Genesis uses Highyag RLSK software from the Highyag division of II-VI Inc. to do the offline programming of laser-head robotic welding applications. This software provides accurate cycle times and paths for the laser. For the actual robot programming, Genesis “dumps” the simulated code into Fanuc or Kuka robotics software, and then begins the actual build process, says Jacobsen.
Aerospace applications
As in automotive, control simulation is a staple of the aerospace industry, and a testament to its usefulness can be found at Hawthorne, Calif.-based SpaceX. This ambitious rocket company—led by Elon Musk of Tesla Motors and Paypal fame—looks to cut the cost of rocket launches by a factor of 10 with its Falcon 9 rocket, a reusable payload rocket with reversible thrusters. Femap and NX simulation software from Siemens PLM is a key part of the strategy.
Today’s more robust simulation software for rocket or airline design offers a better view of the interdependent relationship between sub-assemblies and larger assemblies. The process, also known as “designing into context,” involves large designs requiring powerful computing needs. SpaceX has designed its two signature rockets, Falcon 1 and Falcon 9, as well as its Dragon capsule using Femap and NX software.
The Falcon 1 and Falcon 9 rockets each include more than 25,000 part assemblies. “Having the ability to work with an assembly of such size in an efficient and timely manner is very important,” says Chris Thompson, vice president of development operations at SpaceX. “The entire assembly takes only five to 10 minutes to load. Once loaded, a virtual mockup of the rocket enables designers to readily find interferences.”
Beyond the improved speed of design, assembling these rockets is also faster. The NX design models are accessible to SpaceX technicians on the shop floor so, for example, the routes of tubes and wires within a rocket are immediately visible. The software also enables video simulation of rocket launches, so every system can be tested in a virtual environment.
