Using multi-objective evolutionary algorithms in the optimization of polymer injection molding

A Multi-objective optimization methodology has been applied in the optimization of polymer injection molding process. This allowed the optimization of the operating conditions of the process from mold flow simulations, taking into consideration the existence of 5 criteria simultaneously, such as temperature dif-ference on the molding at the end of filling, the maximum pressure, the pressure work, the volumetric shrinkage and the cycle time. The results produced shown that the proposed methodology is an efficient tool to be used in the optimization of this process

Multi-objective optimization of gate location and processing conditions in injection molding using MOEAs: experimental assessment

The definition of the gate location in injection molding is one of the most important factors in achieving dimensionally accuracy of the parts. This paper presents an optimization methodology for addressing this problem based on a Multi-objective Evolutionary Algorithm (MOEA). The algorithm adopted here is named Reduced Pareto Set Genetic Algorithm (RPSGA) and was used to create a balanced filling pattern using weld line characterization. The optimization approach proposed in this paper is an integration of evolutionary algorithms with Computer-Aided Engineering (CAE) software (Autodesk Moldflow Plastics software). The performance of the proposed optimization methodology was illustrated with an example consisting in the injection of a rectangular part with a non-symmetrical hole. The numerical results were experimentally assessed. Physical meaning was obtained which guaranteed a successful process optimization.This work was supported by the Portuguese Fundação para a Ciência e Tecnologia under grant SFRH/BD/28479/2006 and IPC/I3N – Institute for Polymers and Composites, University of Minho.info:eu-repo/semantics/publishedVersio

An Ejection Mechanism Design Method for AIM Tools

One of the key advantages of AIM tooling is time savings when producing small batch production quality parts. However, designing suitable ejection mechanisms is becoming a bottleneck. There are two goals of this paper. First, a model is presented that effectively characterizes the stresses on the mold core and part during injection molding. Second, a method is described for ejection system design. Our approach consists of a combination of analytical, computational, and physical experiments. The ejection system design method will first determine the feasibility of ejection for a particular part geometry, then will determine the number, sizes, and locations of ejector pins. Each phase of the method will be formulated into a Compromise Decision Support Problem, a multi-objective optimization problem formulation. An example will be presented to provide an idea of the robustness and the limitations of the method. Preliminary results indicate that this methodology is sound for a simple geometry.Mechanical Engineerin

Inverse Design Based on Nonlinear Thermoelastic Material Models Applied to Injection Molding

This paper describes an inverse shape design method for thermoelastic bodies. With a known equilibrium shape as input, the focus of this paper is the determination of the corresponding initial shape of a body undergoing thermal expansion or contraction, as well as nonlinear elastic deformations. A distinguishing feature of the described method lies in its capability to approximately prescribe an initial heterogeneous temperature distribution as well as an initial stress field even though the initial shape is unknown. At the core of the method, there is a system of nonlinear partial differential equations. They are discretized and solved with the finite element method or isogeometric analysis. In order to better integrate the method with application-oriented simulations, an iterative procedure is described that allows fine-tuning of the results. The method was motivated by an inverse cavity design problem in injection molding applications. Its use in this field is specifically highlighted, but the general description is kept independent of the application to simplify its adaptation to a wider range of use cases.Comment: 22 pages, 13 figure

Multiscale, thermomechanical topology optimization of self-supporting cellular structures for porous injection molds

Purpose This paper aims to establish a multiscale topology optimization method for the optimal design of non-periodic, self-supporting cellular structures subjected to thermo-mechanical loads. The result is a hierarchically complex design that is thermally efficient, mechanically stable and suitable for additive manufacturing (AM). Design/methodology/approach The proposed method seeks to maximize thermo-mechanical performance at the macroscale in a conceptual design while obtaining maximum shear modulus for each unit cell at the mesoscale. Then, the macroscale performance is re-estimated, and the mesoscale design is updated until the macroscale performance is satisfied. Findings A two-dimensional Messerschmitt Bolkow Bolhm (MBB) beam withstanding thermo-mechanical load is presented to illustrate the proposed design method. Furthermore, the method is implemented to optimize a three-dimensional injection mold, which is successfully prototyped using 420 stainless steel infiltrated with bronze. Originality/value By developing a computationally efficient and manufacturing friendly inverse homogenization approach, the novel multiscale design could generate porous molds which can save up to 30 per cent material compared to their solid counterpart without decreasing thermo-mechanical performance. Practical implications This study is a useful tool for the designer in molding industries to reduce the cost of the injection mold and take full advantage of AM

Optimal design of injection mold for plastic bonded magnet

The optimal design of an injection mold for producing a stronger multipole magnet is carried out using the finite element method and the direct search method. It is shown that the maximum flux density in the cavity obtained by the optimal design is about 2.6 times higher than that of the initial shape determined empirically. 3-D analysis of the nonlinear magnetic field in the injection mold with complicated structure is also carried out. The calculated flux distribution on the cavity surface is in good agreement with the measured one</p

Optimization of polymer processing: a review (Part II - Molding technologies)

The application of optimization techniques to improve the performance of polymer processing technologies is of great practical consequence, since it may result in significant savings of materials and energy resources, assist recycling schemes and generate products with better properties. The present review aims at identifying and discussing the most important characteristics of polymer processing optimization problems in terms of the nature of the objective function, optimization algorithm, and process modelling approach that is used to evaluate the solutions and the parameters to optimize. Taking into account the research efforts developed so far, it is shown that several optimization methodologies can be applied to polymer processing with good results, without demanding important computational requirements. Furthermore, within the field of artificial intelligence, several approaches can reach significant success. The first part of this review demonstrated the advantages of the optimization approach in polymer processing, discussed some concepts on multi-objective optimization and reported the application of optimization methodologies to single and twin screw extruders, extrusion dies and calibrators. This second part focuses on injection molding, blow molding and thermoforming technologies.This research was funded by NAWA-Narodowa Agencja Wymiany Akademickiej, under grant PPN/ULM/2020/1/00125 and European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No 734205–H2020-MSCA-RISE-2016. The authors also acknowledge the funding by FEDER funds through the COMPETE 2020 Programme and National Funds through FCT (Portuguese Foundation for Science and Technology) under the projects UIDB/05256/2020, UIDP/05256/2020

In-Mold Assembly of Multi-Functional Structures

Combining the recent advances in injection moldable polymer composites with the multi-material molding techniques enable fabrication of multi-functional structures to serve multiple functions (e.g., carry load, support motion, dissipate heat, store energy). Current in-mold assembly methods, however, cannot be simply scaled to create structures with miniature features, as the process conditions and the assembly failure modes change with the feature size. This dissertation identifies and addresses the issues associated with the in-mold assembly of multi-functional structures with miniature components. First, the functional capability of embedding actuators is developed. As a part of this effort, computational modeling methods are developed to assess the functionality of the structure with respect to the material properties, process parameters and the heat source. Using these models, the effective material thermal conductivity required to dissipate the heat generated by the embedded small scale actuator is identified. Also, the influence of the fiber orientation on the heat dissipation performance is characterized. Finally, models for integrated product and process design are presented to ensure the miniature actuator survivability during embedding process. The second functional capability developed as a part of this dissertation is the in-mold assembly of multi-material structures capable of motion and load transfer, such as mechanisms with compliant hinges. The necessary hinge and link design features are identified. The shapes and orientations of these features are analyzed with respect to their functionality, mutual dependencies, and the process cost. The parametric model of the interface design is developed. This model is used to minimize both the final assembly weight and the mold complexity as the process cost measure. Also, to minimize the manufacturing waste and the risk of assembly failure due to unbalanced mold filling, the design optimization of runner systems used in multi-cavity molds for in-mold assembly is developed. The complete optimization model is characterized and formulated. The best method to solve the runner optimization problem is identified. To demonstrate the applicability of the tools developed in this dissertation towards the miniaturization of robotic devices, a case study of a novel miniature air vehicle drive mechanism is presented

The Study of Optimal Molding of a LED Lens with Grey Relational Analysis and Molding Simulation

Injection molding technology is known as the most widely used method in mass production of plastic products. To meet the quality requirements, a lot of methods were applied in optimization of injection molding process parameter. In this study the optimization based on Taguchi orthogonal array and Grey relational analysis (GRA) is used to optimize the injection molding process parameters on a LED lens. The four process parameters are: packing pressure, injection speed, melt temperature and mold temperature. The&nbsp;multi-response quality characteristics are total displacement, volumetric shrinkage, and thermal residual stress. The optimal molding parameters are packing pressure (90 MPa), injection speed (300 mm/sec), melt temperature (270 °C) and mold temperature (90 °C). The luminous uniformity of the LED is 92.61 % and the viewing angle of the LED is 124.76°. Among the four factors, packing pressure plays the key role in reducing total displacement, volumetric shrinkage, and thermal residual stress