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Research Papers

Control of Final Part Dimensions in Polymer Extrusion Using a Variable-Geometry Die

[+] Author and Article Information
Lawrence W. Funke

Mem. ASME
Mechanical Engineering Department,
Ohio Northern University,
Ada, OH 45810
e-mail: l-funke@onu.edu

James P. Schmiedeler

Fellow ASME
Department of Aerospace and Mechanical
Engineering,
University of Notre Dame,
Notre Dame, IN 46556
e-mail: schmiedeler.4@nd.edu

1Corresponding author.

Manuscript received August 11, 2017; final manuscript received March 8, 2018; published online May 21, 2018. Assoc. Editor: Donggang Yao.

J. Manuf. Sci. Eng 140(8), 081001 (May 21, 2018) (8 pages) Paper No: MANU-17-1510; doi: 10.1115/1.4039652 History: Received August 11, 2017; Revised March 08, 2018

Parts made via polymer extrusion are currently limited to a constant cross section. Additionally, the process is difficult to control, so desired final part dimensions are often achieved via a manual trial-and-error approach to parameter adjustment. This work seeks to increase the capability of polymer extrusion by using iterative learning control (ILC) to regulate the final width of a rectangular part through changing the width of a simple variable-geometry die. Simulation results determine the appropriateness of the learning algorithm and gains to be used in experiment. A prototype die on a production extruder was used to demonstrate the effectiveness of the approach. These experiments achieved automated control over both gross change in shape and final part dimension when the puller speed was held constant, which has not been seen previously in the literature.

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Figures

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Fig. 1

Schematic of a typical industrial extruder line

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Fig. 2

Iterative learning control flow diagram for polymer extrusion

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Fig. 3

CAD schematic of the model die used in Sec. 3.1. The dump and main ports are circled. The sliding block moves between the top and bottom supports such that one port narrows while the other port widens.

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Fig. 4

Graphs showing the (a) constant width, (b) varying width, and (c) height profiles used for the simulations in Sec. 3.1. Y¯a,d refers to the ath desired output vector.

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Fig. 5

Graphs of the rms error versus iteration number for the simulation of the SISO system for the constant width profile, where max, min, and avg refer to the maximum, minimum, and average rms error of the 100 runs for that iteration, respectively: (a) error is the difference between actual width (y¯1,j) and the desired width shown in Fig. 4(a) and (b) error is the difference between actual height (y¯2,j) and the desired height shown in Fig. 4(c)

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Fig. 6

Graphs of the rms error versus iteration number for the simulation of the MIMO system for the constant width profile, where max, min, and avg refer to the maximum, minimum, and average rms error of the 100 runs for that iteration, respectively: (a) error is the difference between actual width (y¯1,j) and the desired width shown in Fig. 4(a) and (b) error is the difference between actual height (y¯2,j) and the desired height shown in Fig. 4(c)

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Fig. 7

Picture of the (a) die, (b) linear actuator, and (c) support platform (used to connect the linear actuator and die) used in the experimental validation

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Fig. 8

Picture of the die used in experiment and built from the CAD model shown in Fig. 3. The exit ports are circled in red. The main port is on the right and the dump port is on the left.

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Fig. 9

Picture of the laser scanner used to measure the width of the extrudate. Part A is the scanner itself, and part B is the computer used to record the data and save it on the network drive.

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Fig. 10

The rms error at each iteration for the SISO constant width experiments

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Fig. 11

The rms error at each iteration for the SISO varying width experiments

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Fig. 12

Picture of the extrudate form the tenth iteration of the second run shown in Fig. 11. The top shows the extrudate from the narrow part of the profile and the bottom from the wide part of the profile.

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Fig. 13

Graphs of the rms error versus iteration number for the MIMO system experiment for the constant width profile: (a) rms error for width in the MIMO experiment and (b) rms error for height in the MIMO experiment

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Fig. 14

Difference between maximum and minimum puller speed for each iteration

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