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Amcor
A model for predicting and minimizing impact of post-consumer recycled resins on injection molding cycle time
Packaging
  • Background
  • What we're looking for
  • What we can offer you
  • Who we are
  • Q&A
Have questions about this request?
Get them answered by the team at Amcor.
Background

Post-consumer recycled (PCR) content in PET (polyethylene terephthalate) bottles is on the rise. Brands are demanding the inclusion of 15% - 100% of recycled plastic in their bottles. 

 

In 2-step stretch blow molding of PET containers, the first step is to injection mold the plastic into the shape of a preform, which looks like a test tube with a threaded neck.  

Cycle time refers to the total time required to complete one cycle of the injection molding process, from feeding the resin to dispensing the preform. It includes various stages, such as melting the resin, injecting and molding, holding, demolding and cooling before dispensing the finished parts. In the context of incorporating PCR content in PET containers, variations in the properties of recycled materials can affect each stage differently compared to the processing of virgin resin alone, leading to longer or inconsistent cycle times. These variations reduce manufacturing efficiency and quality consistency. 

 

Amcor is seeking a partner to develop a predictive model to minimize the impact of PCR content on injection molding cycle time.

What we're looking for

We are looking for a model that can predict the impact on cycle time based on PCR attributes and the percentage of PCR incorporated into the PET resin. The developed model should take into account different preform designs and machines with varying capacities and functionalities.

Solutions of interest include:
  • Experts skilled in injection molding that can provide insights and perspectives about the process and contribute to the creation of accurate predictive models.
  • Mathematical modeling and artificial intelligence to predict and optimize cycle times.
  • Material science-based models able to predict changes in flow and thermal properties due to the presence of impurities in resin blends.
  • Machine learning algorithms that analyze historical data to forecast the impact of PCR attributes on cycle times.
Our must-have requirements are:
  • Ability to adjust the model for different preform designs, machine manufacturers and machine generations.
  • The developed model (after collaboration with Amcor) should ultimately possess a cycle time prediction accuracy of 95%.
Our nice-to-have's are:
  • An interface that can directly recommend the optimal machine settings.
Acceptable technology readiness levels (TRL):
Levels 2-9
What we can offer you
Eligible partnership models:
Sponsored researchLicensingSupply/purchaseCo-developmentEquity investment
Benefits:
Sponsored Research
We are able to provide funding for model development. Final funding amounts to be discussed at the appropriate stage of engagement.
Data
Selected partners will be able to access to our data for the duration of project.
Facilities and Services
Partners will be able to access to our pilot plant and analytical labs to generate relevant data.
Expertise
Partners will have access to experts from the industry (injection molding expert, polymer scientist etc.) to guide them to best practices and current manufacturing processes.
Tools and Technologies
Partners will be able to access our work processes and training materials to understand the development cycle and manufacturing processes.
Who we are

We solve packaging challenges, around the world every day. We develop differentiated products, services and processes to protect your products and the people who rely on them, all around the globe. Drawing on unrivaled heritage in design, science and manufacturing, more than 1000 R&D experts are innovating new materials, formats and technologies to better protect your products.

In 2018 we pledged to develop all our packaging to be recyclable or reusable by 2025. On our journey to our 2025 pledge we are innovating across various sustainability options, delivering you more sustainable packaging solutions under the new EcoGuard™ brand.

 Learn more
Reviewers
RP
Robert Power
Sr Mgr Injection Excellence
GC
Gregory Carpenter
Senior Scientist
FB
Frederick Beuerle
Sr. Director, Innovation & IP
Q&A with Amcor

The Q&A is now closed.

Sort by:
Q.
Hi, I am interested in this project. Is a technology that can overwrite molding parameter (velocity, pressure, duration) input and auto adjust based on sensor data in scope of the work?
PG
Peng Gao, Principal Investigator, Western Washington University
June 10, 2024
1
A.
Hello, That sounds very in-line with what we are looking for. As we perceive, this project can either be a software to dial in the process to the most efficient operating point or it can be a mechanical improvement (or both!). Looking forward to reading your submission.
GC
Gregory Carpenter, Senior Scientist, Amcor
June 10, 2024
Is this response helpful?
0
0
Q.
A colleague at THWS in Germany and myself work on the development of machine learning models for a similar project and we would very much like to have a Zoom meeting to learn more details.
RB
Rafael Batres, Principal Investigator, Tecnológico de Monterrey
June 25, 2024
1
A.
Hello Rafael, please send me a direct message through Halo with your email address and your colleague's email address. I can send you a Microsoft Teams meeting invite to discuss the topic.
GC
Gregory Carpenter, Senior Scientist, Amcor
June 25, 2024
Is this response helpful?
0
0
Q.
Would you also be interested in finding the optimum molding parameters by experimentation that is guided by computer algorithms?
RB
Rafael Batres, Principal Investigator, Tecnológico de Monterrey
June 25, 2024
1
A.
Hello Rafael, are you suggesting that we run a DOE? Please submit your proposal and we can discuss. Thanks again!
GC
Gregory Carpenter, Senior Scientist, Amcor
June 25, 2024
Is this response helpful?
1
0
A.
Dear Gregory. DOE results in a large amount of experiments. It would be a computer-guided approach which tells you what experiments to perform towards the optimum with fewer experiments than using DOE.
RB
Rafael Batres, Principal Investigator, Tecnológico de Monterrey
June 25, 2024
1
A.
That does sounds in-line with the approach we are looking for. I look forward to reading your proposal.
GC
Gregory Carpenter, Senior Scientist, Amcor
June 25, 2024
Is this response helpful?
1
0
Q.
What are the parameters of the machine that affect the quality and cycle time? What are the PCR attributes that you can measure and how can you measure them? What equipment do you use to measure the attributes of PCR?
RB
Rafael Batres, Principal Investigator, Tecnológico de Monterrey
July 3, 2024
1
A.
Hello Rafael, the machine parameters that can be adjusted include extruder temperatures, screw speeds, screw backpressures, material residence time (and a few others). Some material attributes that can be measured within the machine during processing could include color and injection pressures. Stresses, unmelts, gate length would need to be observed and input from the operator.
GC
Gregory Carpenter, Senior Scientist, Amcor
July 3, 2024
Is this response helpful?
0
0
A.
Thank you Gregory. Do you also measure material attributes of the PCR before feeding it into the machine?
RB
Rafael Batres, Principal Investigator, Tecnológico de Monterrey
July 4, 2024
1
A.
Hi, We will have the CoA from the supplier for the lot. This should include SIV and AA (other properties reported will vary by supplier). What material attributes are you looking for?
GC
Gregory Carpenter, Senior Scientist, Amcor
July 5, 2024
Is this response helpful?
0
0
Q.
Could you please provide more information about the data, specifically the volume available? Since the cycle time is the total time, does the data capture the processing times for each stage or just their summation?
XG
Xiang Gao, Research Associate, The University of Oklahoma
July 15, 2024
1
A.
Hello, yes we have the time data for each stage in the injection process (e.g. screw recovery time, acceleration (time, position and speed), constant speed (time, position and speed), deceleration (time, position and speed) and hold. Along with timing, speed and position, we also have pressure sensor data at multiple points in the extruder.
GC
Gregory Carpenter, Senior Scientist, Amcor
July 15, 2024
Is this response helpful?
1
0
Q.
We are curious to learn more about the signals and amount of historical data. Are you available for a web meeting to discuss these and other questions we might have?
EL
Edzel Lapira, CEO, Predictronics Corp.
July 22, 2024
1
A.
Hello Edzel, Please send me a direct message through Halo and I can set up a call to discuss.
GC
Gregory Carpenter, Senior Scientist, Amcor
July 22, 2024
Is this response helpful?
0
0
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