Optimization of Polymer Processing: A Review (Part I—Extrusion)

Gaspar‐Cunha, A.; Covas, J. A.; Sikora, Janusz W.

doi:10.3390/ma15010384

Cited by 18 publications

(11 citation statements)

References 128 publications

(142 reference statements)

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“…This paper presents a modification of the WSM presented by [ 28 ] by considering the restriction of the variables in order to obtain an optimal point and reduce the shrinkage and warpage in the plastic injection process. Regarding the plastic injection molding process, different works use Pareto optimization to optimize the parameters of the injection molding process to optimize the quality of the parts in order to reduce manufacturing costs [ 29 , 30 , 31 ].…”

Section: Theoretical Considerations On Injection Molding Process Opti...mentioning

confidence: 99%

Optimization of the Reduction of Shrinkage and Warpage for Plastic Parts in the Injection Molding Process by Extended Adaptive Weighted Summation Method

et al. 2022

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The consumer market has changed drastically in recent times. Consumers are becoming more demanding, and many companies are competing to be market leaders. Therefore, companies must reduce rejects and minimize their operating costs. One problem that arises in producing plastic parts is controlling deformation, mainly in the form of shrinkage due to the material and warpage associated with the geometry of the parts. This work presents a novel extended adaptive weighted sum method (EAAWSM: Extended Adaptive Weighted Summation Method) integrated into a Pareto front model. The performance of this model is evaluated against three other conventional optimization methods—Taguchi–Gray (TG), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Model Optimization by Genetic Algorithm (MOGA)—and compared with EAAWSM. Two response variables and three input factors are considered to be analyzed: material melting temperature, mold temperature, and filling time. Subsequently, the performance is compared and its behavior observed using Moldflow® simulation. The results show that with the EAAWSM method, the shrinkage is 15.75% and the warpage is 3.847 mm, regarding the manufacturing process parameters of a plastic part. This proposed deterministic model is easy to use to optimize two or more output variables, and its results are straightforward and reliable.

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Section: Theoretical Considerations On Injection Molding Process Opti...mentioning

confidence: 99%

Optimization of the Reduction of Shrinkage and Warpage for Plastic Parts in the Injection Molding Process by Extended Adaptive Weighted Summation Method

et al. 2022

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“…For the optimization of twin-screw extrusion processes, in the majority of the published works evolutionary algorithms (EA) are used. 17 Based on an EA and the modeling approach of Vergnes et al, optimizations of the screw configuration and of the operating parameters were carried out by Gaspar-Cunha et al 18 and Teixeira et al 19 using the simulation tool Ludovic©. In this work, we apply an evolutionary algorithm for the discrete decisions and extend it by a local optimization method for the continuous variables, leading to a memetic algorithm (MA).…”

Section: Introductionmentioning

confidence: 99%

Optimal design and operation of reactive extrusion processes: Modeling, model validation, and optimization algorithm

Cegla,

Engell

2023

Polymer Engineering & Sci

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In this work, a methodology for the optimal design and operation of reactive extrusion processes in twin‐screw extruders is presented. As a process model, a very accurate mechanistic finite volume twin‐screw extruder model is used which is adapted to the reactive extrusion case. In the model, in contrast to other models, the pressure is described as a differential state in order to have a consistent set of equations. The model is compared to other models and advantages and disadvantages with respect to accuracy and computation time are discussed. For optimization, a memetic optimization algorithm (MA) that consists of a combination of a local optimization for the continuous operating parameters and an evolutionary algorithm (EA) for the global optimization of the discrete decision variables is employed to overcome the drawback of the longer model simulation time compared to simpler models. A reduction of optimization time by 90% for the MA compared to the EA was observed. The presented modeling and optimization methodology is validated on the widely investigated reactive extrusion process for ε‐Caprolactone. The methodology is very flexible and the underlying model has good prediction characteristics, thus it is applicable to a wide range of reactive extrusion processes of industrial interest.Highlights Simulation and optimization of reactive extrusion. Improved mechanistic twin‐screw extruder model. Novel approaches for pressure and residence time modeling. Efficient combination of local and global optimization in a memetic algorithm. Benchmarking of the optimization results and performance with literature data.

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“…Also, to the authors' knowledge, no specific design approaches for this type of screws have been proposed, i.e., where the modelling equations are employed in a prearranged sequence. The authors have recently published an extensive review on the optimization of extrusion and other processing techniques [16,17]. These methodologies have been successfully used to design conventional single screw and co-rotating twin screw extruders Consequently, screw design will be approached here as a multi-optimization problem, whereby a process modelling package is used judiciously by an optimization algorithm in order to define a Pareto optimal solution.…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Multi-Objective Optimization of Extrusion Barrier Screws: Data Mining and Decision Making

Gaspar‐Cunha¹,

Costa²,

Delbem³

et al. 2023

Preprint

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: Polymer single screw extrusion is a major industrial processing technique used to obtain plastics products. To assure high outputs, tight dimensional tolerances, and excellent product performance, extruder screws may show different design characteristics. Barrier screws, which contain a second flight in the compression zone, have become quite popular as they promote and stabilize polymer melting. Therefore, it is important to design efficiently extruder screws and decide whether a conventional screw will do the job efficiently, or a barrier-screw should be considered instead. This work uses multi-objective evolutionary algorithms to design conventional and barrier screws (Maillefer screws will be studied) with optimized geometry. Processing of two polymers, Low Density Polyethylene and Polypropylene, is analyzed. A methodology based on the use of Artificial Intelligence (AI) techniques, namely data mining, decision making and evolutionary algorithms, is presented and utilized to obtain results with practical significance, based on relevant performance measures (objectives) used in the optimization. For the various case studies selected, Maillefer screws were generally advantageous for processing LDPE, while for PP the use of both types of screws would be feasible.

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Optimization of Polymer Processing: A Review (Part I—Extrusion)

Cited by 18 publications

References 128 publications

Optimization of the Reduction of Shrinkage and Warpage for Plastic Parts in the Injection Molding Process by Extended Adaptive Weighted Summation Method

Optimization of the Reduction of Shrinkage and Warpage for Plastic Parts in the Injection Molding Process by Extended Adaptive Weighted Summation Method

Optimal design and operation of reactive extrusion processes: Modeling, model validation, and optimization algorithm

Evolutionary Multi-Objective Optimization of Extrusion Barrier Screws: Data Mining and Decision Making

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