Prediction of parison formation using process data in extrusion blow molding

In the extrusion process for plastic fuel tanks, laminated molten polymeric material is extruded and is molded into a hollow cylindrical shape called a parison. Accurately predicting the shape of a parison made from material of inhomogeneous viscoelasticity is a challenging issue. In this study, a numerical simulation based on process data is developed that is capable of predicting the parison shape during production. The process data (extrudate swell, drawdown, and temperature distribution) are collected from the production process and is utilized to develop a simulation model. Comparison of parison shapes extruded by production equipment against numerical simulations verifies for prediction of the distributions of the diameter and thickness of the parison shape to within ±20% of measured values, even under conditions different from those under which the data is obtained except for the data around large and fast stroke changes. The results show the possibility to predict parison shapes close to the one in production without directly solving the complex flow of inhomogeneous viscoelastic materials.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-01-09
DOI
https://doi.org/10.1051/mfreview/2024021/pdf
Primary Topic
Mycorrhizal Fungi and Plant Interactions
Type
article
Field-Weighted Citation Impact
0.00

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article

Prediction of parison formation using process data in extrusion blow molding

Springer Link (Chiba Institute of Technology)
Mycorrhizal Fungi and Plant Interactions
article

Prediction of parison formation using process data in extrusion blow molding

article en

Abstract

In the extrusion process for plastic fuel tanks, laminated molten polymeric material is extruded and is molded into a hollow cylindrical shape called a parison. Accurately predicting the shape of a parison made from material of inhomogeneous viscoelasticity is a challenging issue. In this study, a numerical simulation based on process data is developed that is capable of predicting the parison shape during production. The process data (extrudate swell, drawdown, and temperature distribution) are collected from the production process and is utilized to develop a simulation model. Comparison of parison shapes extruded by production equipment against numerical simulations verifies for prediction of the distributions of the diameter and thickness of the parison shape to within ±20% of measured values, even under conditions different from those under which the data is obtained except for the data around large and fast stroke changes. The results show the possibility to predict parison shapes close to the one in production without directly solving the complex flow of inhomogeneous viscoelastic materials.

Springer Link (Chiba Institute of Technology)
Japan Society for the Promotion of Science
Openalex Percentile: Top 55%
Mycorrhizal Fungi and Plant Interactions
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Prediction of parison formation using process data in extrusion blow molding · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS