| DOI | Resolve DOI: https://doi.org/10.1016/0098-1354(93)80061-Q |
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| Author | Search for: Diraddo, R. W.1; Search for: Garcia-Rejon, A.1 |
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| Affiliation | - National Research Council Canada. NRC Industrial Materials Institute
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| Format | Text, Article |
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| Abstract | The critical stage of the extrusion blow moulding process involves the inflation of a molten parison into the final part. Modelling of the inflation stage generally entails predicting the final part thickness distribution, given the initial parison thickness profile. We refer to this formulation of the process as the “forward formulation” or as the “forward predictor”.
It would be more desirable to model the process using the inverse formulation, that is, given a final part thickness distribution, obtain the required initial parison thickness profile. We refer to this formulation of the process as the “inverse formulation”. Tooling costs and machine downtimes can be minimized with the information obtained from the simulation. Computational times and man-hours involved with trial-and-error runs with the forward predictor can also be minimized.
The approach chosen involves placing a forward predictor in an iterative optimization loop. The loop searches for the parison thickness profile that results in the minimum overall difference between the specified final part thickness distribution and the individual iteration's output from the forward predictor. The forward predictor employs a discretized Newton—Raphson technique in the solution. The profiled optimization methodology utilizes updating techniques analogous to classical process control equations. |
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| Publication date | 1993-08-01 |
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| Publisher | Elsevier |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NRC number | CNRC 35332
NRC-IMI93AP-41300-1450-G |
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| NPARC number | 23004451 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | f3639353-3b91-4fcd-a1d6-bd4dc32e2432 |
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| Record created | 2018-11-02 |
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| Record modified | 2020-04-24 |
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