Quality control of polymer production processes

Ohshima, Masahiro; Tanigaki, M.

doi:10.1016/s0959-1524(99)00042-6

Cited by 108 publications

(80 citation statements)

References 34 publications

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“…Ohshima and Tanigaki [64] proposed a quality control system for polymer production plants, which integrates optimal control with on-line sensing and scheduling techniques. Report by Kano and Ogawa [65] has provided a detailed description on the state-of-art of the control of industrial processes including the use of soft approaches in process control.…”

Section: Other Control Approachesmentioning

confidence: 99%

Single screw extrusion control: A comprehensive review and directions for improvements

Abeykoon

2016

Control Engineering Practice

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Polymer extrusion is usually a complex process, particularly due to the coupled nature of process parameters, and hence highly prone to fluctuations. Although a number of different approaches have been attempted in research/industry over the last few decades for extrusion control, it is still experiencing some problems in achieving consistent product quality. Presently, most of the polymer processing extruders are equipped with PID controllers mainly for the control of the screw speed and barrel temperatures in their set limits. It seems that only both of these controllers are commonly used as the major aids of process control to achieve the required melt quality. Although, the quality of the melt output (i.e., a thermally homogeneous melt output which is constant in quantity and quality over the time) is the key variable in polymer extrusion, only a few control techniques are available which make control decisions by observing the actual melt flow quality. Therefore, the development of new control strategies which consider the actual melt quality, perhaps incorporating industrially popular nonlinear techniques such as artificial intelligence, should be highly valuable. In this work, a critical evaluation is made on the state-of-the-art of the previous control approaches in polymer extrusion in industry and research while identifying their limitations. Then, some of the possible directions for future research and also to develop an advanced process control strategy are presented by eliminating a few of the existing limitations.

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Section: Other Control Approachesmentioning

confidence: 99%

Single screw extrusion control: A comprehensive review and directions for improvements

Abeykoon

2016

Control Engineering Practice

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“…In polyolefin production plants, it is well-known that the concentration ratio of hydrogen to monomer, X, has a strong effect on the instantaneous melt index MI i . In the literature [1,28] different relationships have been proposed to relate MI i to X. In this work, the following relationship is used:…”

Section: Appendix a Dynamic Model Of The Polymerization Processmentioning

confidence: 99%

Non-linear model based control of a propylene polymerization reactor

Ali

Betlem

Weickert

et al. 2007

Chemical Engineering and Processing: Process Intensification

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Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Abstract A modified generic model controller is developed and tested through a simulation study. The application involves model-based control of a propylene polymerization reactor in which the monomer conversion and melt index of the produced polymer are controlled by manipulating the reactor cooling water flow and the inlet hydrogen concentration.Non-linear control is designed using a simplified non-linear model, in order to demonstrate the robustness of the control approach for modeling errors. Two model parameters are updated online in order to ensure that the controlled process outputs and their predicted values track closely. The controller is the static inverse of the process model with setpoints of the measured process outputs converted to setpoints for some of the state variables.The simulation study shows that the proposed controller has good setpoint tracking and disturbance rejection properties and is superior to the conventional generic model control and Smith predictor control approaches.

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“…Particularly, in the polypropylene production process, it was shown that the melt index can be predicted by some related process variables that significantly reflect the process condition and the product quality, such as hydrogen concentration of the reactor, propylene feed rate, reaction temperature, among others (Shi et al, 2006;Kiparissides et al, 1993;Coates et al, 2003;Zhang et al, 1998;Ohshima & Tanigaki, 2000;Liu, 2007).…”

Section: Introductionmentioning

confidence: 99%

Quality prediction for polypropylene production process based on CLGPR model

Chen

2011

Control Engineering Practice

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Quality control of polymer production processes

Cited by 108 publications

References 34 publications

Single screw extrusion control: A comprehensive review and directions for improvements

Single screw extrusion control: A comprehensive review and directions for improvements

Non-linear model based control of a propylene polymerization reactor

Quality prediction for polypropylene production process based on CLGPR model

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