While the predominant current weight of 500ml PET water bottles in the United States is now as light as eight grams, new launches are trying to squeeze that down even further. Yet zeroing in on the optimal design that can offset lightweight material composition with a structure that still meets stringent performance requirements is no easy matter. In fact, it’s a delicate balancing act that has sent brand owners, bottle manufacturers, resin and machine manufacturers scrambling to embrace innovative design processes that can help them achieve their goals.
At Plastic Technologies Inc. (PTI), simulation-led design combines an in-house virtual-prototyping tool with finite element analysis from Dassault Systèmes’ realistic simulation application SIMULIA, a key component of the Perfect Package Industry Solution. Simulation enables the PTI design team to reduce the amount of time and resources spent on building and testing physical prototypes.
Abaqus is often employed in concert with PTI’s proprietary virtual-prototyping software. This is used to simulate the reheating of preforms, replicate the blow moulding of containers and predict the material thickness distribution of associated mechanical properties. The data is then used as input for FEA studies that explore the highly nonlinear deformation of different containers under various types of loading conditions.
Abaqus has become an essential part of PTI’s development process, helping designers quickly screen designs and identify the best light weighting opportunities, optimising the production process and identifying root-cause failures.
PTI has two primary objectives when light weighting container designs for its customers: to achieve materials savings without greatly affecting structural performance and to enhance both container structure and preform designs to improve the efficiency of material distribution so that each grain of material is maximised.
In one study that explored plastic water bottle performance during light weighting, PTI used Abaqus in simulations of what happens to top-load strength and/or side-wall rigidity under varying pressures to ensure that a lighter plastic water bottle would not buckle under loading or stacking conditions.
Surprisingly, it was revealed that the top-load strength of a plastic bottle drops nearly in half from 19lbf (pound force) to 12lbf as the container is light-weighted from 17g to 14g - a critical finding that allowed the company to redirect its design efforts quickly.
Abaqus was tapped to explore the orientation and wall thickness of the bottle sidewall to identify the optimal preform dimensions that would result in the desired top load.
PTI also studied top-load and side-load performance of oval and other non-round containers to determine the different outcomes produced by different preform heating methods during the blow-moulding process. In this case, PTI engineers learned that the “preferential heating” method is the preferred option for oval-shaped containers as it resulted in a more uniform weight distribution with better empty and filled top-load strength.
Sumit Mukherjee, Director, CAE & Simulation at Plastic Technologies said this ability to analyse different container shapes and preform designs in a relatively short time meant a wider variety of design features could be rapidly evaluated while providing a good learning tool for future design recommendations.
As packaging becomes an integral part of a company’s brand appeal, new containers are testing current processes and domain expertise, introducing novel challenges in the way of package failures. Since quality standards vary from one producer to another, there is no absolute guidance on what constitutes failure.
PTI decided to further evolve its simulation efforts to tackle root-cause failure analysis and, ultimately, improve its quality efforts. Armed with its own virtual-prototyping software tools along with FEA software and M-Rule models, PTI was able to zero-in on reoccurring failures and resolve them in a fraction of the time and with far fewer resources than were previously required using standard prototype-and-test methods.
In one exercise, engineers tested their new failure-analysis process on a 64-ounce hot-fill juice container, which exhibited bulging in the area of the logo panel on sporadic numbers after being filled. Tracking the errors through the system, PTI determined that the failure sample was being generated during the filling process. Further analysis revealed that material distribution inconsistencies were not the cause of failure, prompting PTI to turn its attention to possible external influences. A thesis emerged that high product temperature coupled with filler pressure spikes was the impetus for the panel failure.
In order for simulation to serve as an effective replacement for the traditional root-cause failure inspection process, PTI had to conduct modeling efforts on a grand scale. The model’s build began with the replication of the material distribution and mechanical properties, but also included reproducing the blow-moulding process in a virtual world as well as the physical aspects of the environment, including conveyors and filling heads. Once the information input was complete, PTI conducted numerous simulations to realistically replicate the failure mechanism. With those validated, the team could then use the model as a baseline to compare design iterations that addressed the failure.
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As a result of its efforts, PTI was able to rule out heavy weighting the juice container design to a 75g version to address the deformation problem and instead concluded that a geometric modification to redesign the logo panel was the optimal resolution to the problem. This very process of continually modifying designs to eliminate failure is exactly where simulation can save time and money.
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