Engineers at Queen’s University model the injection stretch blow molding process for PET bottles to improve bottle production and performance—and to cut costs.
If something can be modeled, it can be studied, optimized and tested as needed via simulation without trial-and-error methodologies. This speeds development time and cuts costs.
For more than two decades, engineers in the Advanced Materials and Processing group based in the School of Mechanical and Aerospace Engineering at Queen’s University, Belfast, Northern Ireland, have explored almost everything that happens when a plastic bottle is created—and identified which parameters are most critical in ensuring that the end result is an optimized bottle.
As Packaging Digest readers know, there are ongoing pressures to use less material, produce stronger containers and redesign plastic bottles according to customer demand and consumer desires. As a result, the University’s specialized skillset remains in demand by leading multinational companies around the globe.
“The challenge our industrial partners face is to make a bottle with as little material as possible, yet still have the proper end-service performance requirements,” explains Dr. Gary Menary, senior lecturer, School of Mechanical and Aerospace Engineering. “The problem is that the process continues to rely to some extent on trial and error. Even now, we hear of engineers who come up with a new bottle idea and bring it down to the shop floor to manufacture different shapes while guessing the proper design and production conditions. It’s still a bit of a black art all around.”
Beginning in 1991, the group received funding from the U.K. Research Council with the objective of removing all the trial and error from the injection stretch blow molding (ISBM) process.
"This started as a three-year project, but 20 years later we're still working on it, though with a far more sophisticated toolset," Menary points out. “As we get ever closer to numerically describing and predicting the blowing process from start to finish, we are beginning to be able to optimize the design, and even the manufacture, of just about any product configuration.”
The primary simulation tool for Queen’s all along has been Abaqus Finite Element Analysis (FEA) software from Dassault Systèmes SIMULIA (see A primer on nonlinear FEA, below). As the group’s analyses of the ISBM process grew increasingly sophisticated over the years, so did the software’s capabilities.
Menary’s vision is to link everything together with simulation, from bottle and preform design and process conditions, to thickness distribution and mechanical properties.
Menary reports that their group typically interfaces with senior engineers from companies’ research and development teams who are responsible for computer-aided engineering (CAE) within their organization. Besides optimizing new bottle designs, their tools are also used for troubleshooting.
Here are more responses from Menary and his team.
Why do companies come to you?
Queen’s University: At the quantities that the typical large-scale converter produces bottles (an average of 2 billion annually), taking even a single gram out of a bottle translates into 2 million kilos (4,409,245 pounds) of material, or about $3 million saved per year. At the same time they are lightweighting a bottle design, the converter also needs to ensure strength and durability. We offer highly sophisticated simulation and testing tools that enable our customers to optimize their bottle designs faster and more cost-effectively.
What do you offer that can’t be found elsewhere?
Queen’s University: We have unique expertise and testing equipment in characterizing materials, and the process. Using this information, we can develop and validate our simulations. There is no one else in the world offering the type of services we provide.
What are the main factors that influence the ISBM modeling process?
Queen’s University: The ISBM process is a complex process that depends on many process parameters and that is why I believe simulation is a vital tool. The major parameters for the process are the preform design, the material (the behavior of which is highly dependent on temperature and time), the stretch rod displacement and the pressure.
One of the key challenges for the simulation is to obtain accurate enough input data that is representative of the process. This is one of the main reasons why instrumentation is one of the main themes of our research. We have developed specialist tools including an instrumented stretch rod and the THERMOscan device that enable us to obtain this critical data. THERMOscan is a patent-pending device for preform temperature monitoring sold by our spin-off company Blow Moulding Technologies to several leading brand names and converters.
These tools were initially developed for our simulation purposes but are now sold commercially and are currently being used by the industry to provide quantitative data that they can use to better control and scale up their processes.
What polymers can you work with?
Queen’s University: We have mainly worked with PET, though more recently we have been working on characterizing and modeling some new materials for stretch blow molding. Unfortunately, I cannot go into the details.
What about renewable biopolymers?
Queen’s University: We’ve got a pretty good handle on the behavior of PET right now. Next, we may turn to modeling the newer plant-based plastics. One of the advantages of our approach is that we can apply the same methodology that we currently use for PET easily to other materials and have an Abaqus FEA simulation of the process running very quickly, giving us a powerful tool for optimizing the preform design and the process conditions.
What have been the key findings over the past months?
Queen’s University: We’ve learned that what goes on inside the bottle during inflation is much more complex than earlier work had estimated. As the PET material expands, pressure inside the membrane is not uniform: it changes over time, depending on the rate of air flowing into the system as well as the expansion of the membrane. By first observing what happened to a bottle being inflated outside of a mold, we could fully visualize what was happening and use that data to more finely calibrate our latest computer models of what is going on inside the mold. We have developed specialist instrumentation and methodology for characterizing the process to obtain this information from stretch blow molding machines.
Queen’s University: Linking it all together with simulation, from bottle and preform design and process conditions, to thickness distribution and mechanical properties. Then transferring the data from the ISBM simulation to virtual packaging tests where you can see how the preform design affects things like bottle drop, top-load performance or even shelf life. This can all be coupled together with optimization software to pinpoint best process or minimum material—whatever is the goal.
Blow Moulding Technologies, +44 28 9097 4780
Dassault Systèmes SIMULIA
Tech at a glance
Queen’s Belfast University ISBM
TARGET MARKETS: PET containers (of any size) used as Fast-Moving Consumer Goods (FMCG)
STATUS: Available for industrial applied research and commercial products
LEAD TIME: 12 weeks
A primer on nonlinear FEA
Frankly, with little to no experience reporting on Finite Element Analysis much less nonlinear FEA, this reporter asked our contacts for help, and here’s what we were told:
“Nonlinear finite element analysis is a way of using computer simulation to look at the multiple effects that different loads (such as stress, strain, pressure and temperature change) have on an object being studied. It’s called nonlinear because it demonstrates effects that go beyond just simple load-and-response. Nonlinear FEA shows how an object deforms over time as the result of a load being applied, or how different temperatures affect the response of a material to a load.
“Once a computer model (computer-aided-design/CAD) is made of the object, and then prepared (meshed into tiny elements) for FEA, it can be virtually subjected to any number of stresses, such as heating, stretching and dropping. This gives engineers insight into how to improve their designs to make the finished product lighter, stronger and longer-lasting. They can alter their designs on the computer and then re-run the FEA to see the changes in how the design stands up to different loading scenarios. Once a design has been “proven out” through FEA, it is validated with real-world testing. FEA has become highly accurate and predictive: with computer models that agree closely with test results, engineers can use the models to virtually test designs before prototyping, thereby reducing the amount of real-world testing.”