Polypropylene degradation control during reactive extrusion

Pong, Sheng-Hong; Lu, Chuan‐Pin; Wang, Ming-Chih; Chiu, Shih‐Hsuan

doi:10.1002/app.21275

Cited by 13 publications

(4 citation statements)

References 19 publications

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“…Several authors proposed viscosity control strategies [55,56,57] and also some other control approaches [58,59] for reactive extrusion which mainly uses an extruder as a chemical reactor. Reactive extrusion differs from conventional polymer extrusion methods, where synthesis is a separate operation and the extruder serves only as a processing aid.…”

Section: Viscosity Controlmentioning

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: Viscosity Controlmentioning

confidence: 99%

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

Abeykoon

2016

Control Engineering Practice

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“…At present, the progress in machine learning algorithms allows developing process models based on failure-identifying data [1]. Using machine learning to determine patterns based on historical data (derived from IoT sensors) provides an additional approach to maintenance planning by analyzing datasets of individual characteristics of a machine, identifying abnormal situations, and providing predictable failures for individual parts [2][3][4]. In [5] an artificial neural network was developed for monitoring a coal furnace.…”

Section: Introductionmentioning

confidence: 99%

“…The aggregation time window of 10 minutes was selected based on expert analysis and requirements for the monitoring system to predict a failure in 10-30 minutes. At that, 30 minutes was sufficient time for the process engineer to detect and prevent a failure by using control actions [3,7].…”

Section: Introductionmentioning

confidence: 99%

Monitoring and control of polymer production line based on machine learning

Абдуракипов

2021

J. Phys.: Conf. Ser.

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The work is devoted to the development of an application for monitoring and controlling the state of equipment (extruder) for the petrochemical industry based on sensor readings using a machine learning model. The statistical relationships of the technological process parameters are analyzed, the most significant parameters influencing the occurrence of failures are determined using SHAP values. The hypotheses regarding the effectiveness of various machine learning algorithms in relation to the real problem of predicting the technical state of the extruder are tested. A gradient boosting model has been developed to predict the probability of extruder shutdown due to the formation of polypropylene agglomerates. The developed application allows interpreting the results of the model, which makes it possible to select the most important process parameters that have the greatest impact on the probability of extruder failure, and also proposing a prototype of an extruder monitoring system based on sensor readings using a machine learning model.

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“…Similar to melt‐processing techniques and especially in the presence of oxygen, the sintering process 11,12 can be accompanied with molecular degradation. Molecular degradation may lead to sintered products with unexpected properties and inferior durability, 13–16 while it could also be instigated selectively to improve the polymer blending process and polymer recyclability 17,18 …”

Section: Introductionmentioning

confidence: 99%

Thermo‐oxidative degradation during sintering of polyethylene particles

Salehi

Pircheraghi

2020

J of Applied Polymer Sci

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Polymer sintering is not only a well‐established procedure for producing functional polymeric parts, but it is also the basis for the relatively new additive manufacturing technique, selective laser sintering. Although studying the impact of thermo‐oxidative degradation during sintering has significant practical importance, few studies have focused on this aspect of the sintering process. In the present work, we have investigated the active thermo‐oxidative degradation mechanisms during sintering of high‐density polyethylene (HDPE) particles, the conditions that promote them, and their respective impact on the morphological evolution of the polyethylene particles. To perform a comprehensive study, we have complemented the rheological, thermal, chemical, and morphological analysis of the sintered HDPE particles with the study of their ensemble pore structure. We observed two distinct degradation regimes. At the beginning, the relatively low concentration of oxygen in the particles led to the dominance of branching and resulted in a pore structure evolution limited to surface relaxation. In the second regime and with the diffusion of more oxygen, chain scission became the dominant route. In this regime, the emergence of highly mobile short chains markedly accelerated the pore evolution.

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Polypropylene degradation control during reactive extrusion

Cited by 13 publications

References 19 publications

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

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

Monitoring and control of polymer production line based on machine learning

Thermo‐oxidative degradation during sintering of polyethylene particles

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