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A special issue of Polymers (ISSN 2073-4360). This special issue belongs to the section "Polymer Processing and Engineering".

Deadline for manuscript submissions: closed (25 December 2022) | Viewed by 36698

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Dr. Jorge Manuel Mercado-Colmenero

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Department of Engineering Graphics, Design and Projects, Universidad de Jaen, 23071 Jaén, Spain
Interests: injection molding; additive manufacturing; MEX; sustainability in advanced polymer manufacturing technologies; industrial design; conformal cooling; characterization of materials; numerical simulation; advanced injection molding design and tooling
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Prof. Dr. Cristina Martín-Doñate

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Prof. Dr. Miguel Ángel Rubio-Paramio

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Guest Editor

Department of Graphic Engineering, Design and Projects, Universidad de Jaén, Jaen, Spain
Interests: injection molding, industrial design; computer aided manufacturing; plastic part design; new injection molding design

Special Issue Information

Dear Colleagues,

Plastic injection moulding is, at the present time, one of the most widespread manufacturing processes with plastic materials at industrial sectors as automotive, aeronautics, construction, etc. All this, highlights the relevant impact that optimal design of the main elements and systems that define a plastic injection mould, as well as the application of innovative manufacturing techniques for them, positioning this research line as one of the areas of greatest interest in the industrial. Nowadays, this manufacturing technology is maintained in a process of constant development and evolution since plastic parts manufacturers demand higher technical and geometric requirements regarding surface quality, optics, tolerances, etc. However, despite all development made so far, many challenging issues remain open. In this line, this Special Issue will collect a selection of papers presenting original and innovative contributions to the study of optimization in the design of the systems and main elements that define a plastic injection mould, as well as the application of new design methodologies and innovative manufacturing techniques for them.

We look forward to receiving your contributions.

Dr. Jorge Manuel Mercado-Colmenero
Prof. Dr. Cristina Martín-Doñate
Prof. Dr. Miguel Ángel Rubio-Paramio
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Polymers is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

injection molding design
injection molding manufacturing
additive manufacturing
conformal cooling
numerical simulation
computer aided manufacturing
thermoplastic material characterization
industrial design for injection molding

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Published Papers (11 papers)

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Research

29 pages, 17996 KiB

Open AccessArticle

Optimize Injection-Molding Process Parameters and Build an Adaptive Process Control System Based on Nozzle Pressure Profile and Clamping Force

by Guan-Yan Liou, Wei-Jie Su, Feng-Jung Cheng, Chen-Hsiang Chang, Ren-Ho Tseng, Sheng-Jye Hwang, Hsin-Shu Peng and Hsiao-Yeh Chu

Polymers 2023, 15(3), 610; https://doi.org/10.3390/polym15030610 - 25 Jan 2023

Cited by 3 | Viewed by 7500

Abstract

The injection-molding process is a non-linear process, and the product quality and long-term production stability are affected by several factors. To stabilize the product quality effected by these factors, this research establishes a standard process parameter setup procedure and an adaptive process control system based on the data collected by a nozzle pressure sensor and a tie-bar strain gauge to achieve this goal. In this research, process parameters such as the V/P switchover point, injection speed, packing pressure, and clamping force are sequentially optimized based on the characteristics of the pressure profile. After the optimization process, this research defines the standard quality characteristics through the optimized process parameters and combines it with the adaptive process control system in order to achieve the purpose of automatic adjustment of the machine and maintain high-quality production. Finally, three different viscosity materials are used to verify the effectiveness of the optimization procedure and the adaptive process control system. With the system, the variation of product weight was reduced to 0.106%, 0.092%, and 0.079%, respectively. Full article

(This article belongs to the Special Issue Injection Molding of Polymers)

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25 pages, 10255 KiB

Open AccessArticle

Application of New Conformal Cooling Layouts to the Green Injection Molding of Complex Slender Polymeric Parts with High Dimensional Specifications

by Abelardo Torres-Alba, Jorge Manuel Mercado-Colmenero, Juan de Dios Caballero-Garcia and Cristina Martin-Doñate

Polymers 2023, 15(3), 558; https://doi.org/10.3390/polym15030558 - 21 Jan 2023

Cited by 14 | Viewed by 2266

Abstract

Eliminating warpage in injection molded polymeric parts is one of the most important problems in the injection molding industry today. This situation is critical in geometries that are particularly susceptible to warping due to their geometric features, and this occurs with topologies of great length and slenderness with high changes in thickness. These features are, in these special geometries, impossible to manufacture with traditional technologies to meet the dimensional and sustainable requirements of the industry. This paper presents an innovative green conformal cooling system that is specifically designed for parts with slender geometric shapes that are highly susceptible to warping. Additionally, the work presented by the authors investigates the importance of using highly conductive inserts made of steel alloys in combination with the use of additively manufactured conformal channels for reducing influential parameters, such as warpage, cooling time, and residual stresses in the complex manufacturing of long and slender parts. The results of this real industrial case study indicated that the use of conformal cooling layouts decreased the cycle time by 175.1 s—66% below the current cooling time; the temperature gradient by 78.5%—specifically, 18.16 °C; the residual stress by 39.78 MPa—or 81.88%; and the warpage by 6.9 mm—or 90.5%. In this way, it was possible to achieve a final warping in the complex geometry studied of 0.72 mm, which was under the maximum value required at the industrial level of 1 mm. The resulting values obtained by the researchers present a turning point from which the manufacturing and sustainability in the injection molding of said plastic geometries is possible, and they take into account that the geometric manufacturing features analyzed will present a great demand in the coming years in the auto parts manufacturing industry. Full article

(This article belongs to the Special Issue Injection Molding of Polymers)

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21 pages, 11877 KiB

Open AccessArticle

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

by Guillermo Hiyane-Nashiro, Maricruz Hernández-Hernández, José Rojas-García, Juvenal Rodriguez-Resendiz and José Manuel Álvarez-Alvarado

Polymers 2022, 14(23), 5133; https://doi.org/10.3390/polym14235133 - 25 Nov 2022

Cited by 6 | Viewed by 2941

Abstract

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. Full article

(This article belongs to the Special Issue Injection Molding of Polymers)

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16 pages, 4301 KiB

Open AccessArticle

Novel Method for Failure Modes Detection in UV-Cured Clear Coated Polymer for Automotive Interior Mechatronic Devices

by Ion Cristian Braga, Razvan Udroiu and Anisor Nedelcu

Polymers 2022, 14(18), 3811; https://doi.org/10.3390/polym14183811 - 12 Sep 2022

Cited by 2 | Viewed by 2540

Abstract

Plastic parts used in automotive interior are difficult to coat, due to their low surface energies as well as their sensitivity to temperature and solvents, rendering the development of coating systems for such substrates challenging. Automotive customer requirements are explicit and clear, mainly focused on functional and surface defects. A new failure modes detection methodology of UV clear coated polymers for automotive interior, obtained by a multi-step manufacturing process, is proposed. The polymer complex parts analyzed in this paper are manufactured in various steps as follows: two components plastic injection molding, primer coating, laser engraving, and UV-cured clear coating. The failure modes detection methodology of the parts within each process step is investigated using different tests and analyses as follows: surface tension test, painting adhesion test, optical 3D measuring, energy dispersive X-ray analysis (EDX), and microscopy. A design of the experiments (DoE) based on the Taguchi technique with the aim to detect the influence of the main factors that lead to surface defects was performed. The proposed methodology is validated by a case study. The results showed that the mold temperature and the laser engraving current have a significant influence on the surface defect occurrence. Additionally, a possible contamination of the molding tool can generate the defects. A solution to reduce the occurrence of the failures was proposed, reducing the defect rate from 50% to 0.9%. Full article

(This article belongs to the Special Issue Injection Molding of Polymers)

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22 pages, 4733 KiB

Open AccessArticle

Predicting of Process Parameters for Theoretical Concentrated Stress of Fatigue Notch Coefficient of Auto Parts Using Virtual Recognizable Performance Evaluation Research

by Hanjui Chang, Shuzhou Lu, Yue Sun and Guangyi Zhang

Polymers 2022, 14(15), 3043; https://doi.org/10.3390/polym14153043 - 27 Jul 2022

Viewed by 1649

Abstract

This paper analyzes the structure of the key parts of the car belt guide, and the average stress of the vulnerable parts is simulated by analysis software. The theoretical stress of the section is calculated. The theoretical stress concentration factor (

K_{t}

[...] Read more.

K_{t}

) is given. The relation between the gap radius and the notch coefficient (

K_{f}

) was studied according to a previous

K_{f}

calculation formula. The tensile tests of real products are used as reference data. The results showed that

K_{f}

and

K_{t}

are linear in most cases, but there are also cases of non-compliance. The relationship between the fatigue notch coefficient

K_{f}

and the theoretical stress concentration coefficient

K_{t}

was closely related to the service life and fatigue strength of the product. In addition, we found that the size and direction of warpage improved significantly with the increase of fillet size, which was not consistent with the effect of adding glass fiber material. The rounded corners of ordinary PP materials usually displayed forward warping, but the addition of glass fiber into PP materials made the degree of warping smaller, or even led to reverse warping. The size of rounded corners is an important optimization parameter. The relationship between

K_{f}

and

K_{t}

was studied from the perspectives of virtual measurement (VM) and recognizable performance evaluation (RPM). According to abnormal filling pressure, these relationships were compared with filling data to generate a fracture initiation control model. Based on a large amount of normal process data and quality inspection data, the historical data (causes) and quality inspection data (results) were combined. Full article

(This article belongs to the Special Issue Injection Molding of Polymers)

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25 pages, 6333 KiB

Open AccessArticle

Non-Dominant Genetic Algorithm for Multi-Objective Optimization Design of Unmanned Aerial Vehicle Shell Process

by Hanjui Chang, Guangyi Zhang, Yue Sun and Shuzhou Lu

Polymers 2022, 14(14), 2896; https://doi.org/10.3390/polym14142896 - 16 Jul 2022

Cited by 12 | Viewed by 1813

Abstract

This paper uses Pareto-optimized frames and injection molding process parameters to optimize the quality of UAV housing parts with multi-objective optimization. Process parameters, such as melt temperature, filling time, pressure, and pressure time, were studied as model variables. The quality of a plastic part is determined by two defect parameters, warpage value and mold index, which require minimal defect parameters. This paper proposes a three-stage optimization system. In the first stage, the main node position of the electronic chip in the module is collected by the unified sampling method, and the chip calculation index of these node positions is analyzed by the mold flow analysis software. In the second stage, the kriging function predicts the mathematical relationship between the mold index and warpage value and the process parameters, such as melt temperature, filling time, packing pressure, and packing time. In the third stage, using LHD sampling and non-dominant rank genetic algorithm II, a convergence curve of warp value is found near the Pareto optimal frontier. In the fourth stage, the fitting degree of Pareto optimal leading edge curve points was verified by analytical experiments. According to experimental verification, it can be seen that the injection molding factors are pressure and pressure time, because the injection molding time and pressure time are completely positively correlated with the mold indicators, the correlation is the strongest, the mold temperature and glue temperature are not the main influencing factors, and the mold temperature shows a certain degree of negative correlation. In this experiment, the die index is mainly improved by injection time and pressure, optimal injection parameter factor combination and minimum injection index, the optimization rate of the die index is up to 96.2% through genetic algorithm optimization nodes and experimental verification, the average optimization rate of the four main optimization nodes is 91.2%, and the error rate with the actual situation is only 8.48%, which is in line with the needs of actual production, and the improvement of the UAV IME membrane is realized. Full article

(This article belongs to the Special Issue Injection Molding of Polymers)

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32 pages, 7828 KiB

Open AccessArticle

Analysis of the Warpage Phenomenon of Micro-Sized Parts with Precision Injection Molding by Experiment, Numerical Simulation, and Grey Theory

by Wei-Chun Lin, Fang-Yu Fan, Chiung-Fang Huang, Yung-Kang Shen and Hao Wang

Polymers 2022, 14(9), 1845; https://doi.org/10.3390/polym14091845 - 30 Apr 2022

Cited by 15 | Viewed by 2863

Abstract

In this study, we determined the effects of design and processing parameters of precision injection molding (PIM) to minimize warpage phenomena of micro-sized parts using various plastics (polyoxymethylene (POM), acrylonitrile-butadiene-styrene (ABS), polypropylene (PP), polyamide (PA), and ABS+ polycarbonate (PC)). We applied a numerical simulation (Moldflow) to determine the runner’s balance in multi-cavities of the micro-sized part and simulate the warpage phenomenon of micro-parts with PIM. We used simulation data to fabricate a steel mold by computer numerical control (CNC) machining. In this, we study manufactured a micro-sized part and measured its warpage value using various PIM process parameters (melt temperature, mold temperature, injection pressure, and filling time). In order to obtain optimal results (i.e., minimum warpage), we employed the Taguchi method and grey theory to discern the influence of each process parameter on PIM. Finally, we determined that the most significant PIM process parameter influencing the warpage phenomenon of micro-sized parts was the mold temperature, regardless of whether in terms of the experimental results, numerical simulations, or grey theory. The PA material had the most suitable properties for application for micro-sized parts, regardless of whether in terms of experimental results, numerical simulations, or grey theory for PIM. This study also illustrates that micro-sized parts can be fabricated by PIM without the use of micro-injection molding, and we determined that the mold temperature required for molding does not need to be higher than the glass-transition temperature of the material. Full article

(This article belongs to the Special Issue Injection Molding of Polymers)

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22 pages, 5954 KiB

Open AccessArticle

Optimal Processing Parameters of Transmission Parts of a Flapping-Wing Micro-Aerial Vehicle Using Precision Injection Molding

by Huei-Yu Huang, Fang-Yu Fan, Wei-Chun Lin, Chiung-Fang Huang, Yung-Kang Shen, Yi Lin and Muhammad Ruslin

Polymers 2022, 14(7), 1467; https://doi.org/10.3390/polym14071467 - 4 Apr 2022

Cited by 4 | Viewed by 2182

Abstract

In this study, we designed and fabricated transmission parts for a flapping-wing micro-aerial vehicle (FW-MAV), which was fabricated by precision injection molding, and analyzed its warpage phenomena. First, a numerical simulation (Moldflow) was used to analyze the runner balance and temperature, pressure, and stress distributions of the base, gears, and linkage of the transmission structures in an FW-MAV. These data were then applied to fabricate a steel mold for an FW-MAV. Various process parameters (i.e., injection temperature, mold temperature, injection pressure, and packing time) for manufacturing transmission parts for the FW-MAV by precision injection molding were compared. The Taguchi method was employed to determine causes of warpage in the transmission parts. The experimental results revealed that the causes of warpage in the transmission parts were, in order of importance, the mold temperature, injection pressure, packing time, and injection temperature. After the transmission parts were assembled on the FW-MAV, experiments revealed that the MAV could achieve a flight time of 180 s. Mass production of the FW-MAV by precision injection molding could potentially produce substantial savings in time, manpower, and cost. Full article

(This article belongs to the Special Issue Injection Molding of Polymers)

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21 pages, 29250 KiB

Open AccessArticle

Development of a Multi-Criteria Design Optimization Methodology for Automotive Plastics Parts

by Victor J. Romero, Alberto Sanchez-Lite and Gerard Liraut

Polymers 2022, 14(1), 156; https://doi.org/10.3390/polym14010156 - 31 Dec 2021

Cited by 3 | Viewed by 3229

Abstract

The plastic industry is undergoing drastic changes, due to the customer sustainability perception of plastics, and the eruption of new processes (such 3D printing) and materials (such as renewably sourced resins). To enable a fast transition to high-quality, sustainable plastic applications, a specific methodology could be a key competitive advantage. This novel methodology is focused on improving the objectivity and efficiency of plastic production and the design review process. It is applicable to discrete optimization events in any product lifecycle milestone, from concept design to serial production stages. The methodology includes a natural way to capture plastic-related knowledge and trends, oriented towards building a dynamic “interaction matrix”, with a list of potential optimizations and their positive or negative impacts in a comprehensive set of multi-criteria evaluations. With an innovative approach, the matrix allows the possibility to incorporate a business strategy, which could be different at every lifecycle stage. The business strategy is translated from the common “verbal” definition into a quantitative set of “Target and Restrictions”, making it possible to detect and prioritize the best potential design optimization changes according to the strategy. This methodology helps to model and compare design alternatives, verify impacts in every evaluation criteria, and make robust and objective information-based decisions. The application of the methodology in real cases of plastic material design optimization in the automotive industry has provided remarkable results, accelerating the detection of improvement methods aligned with the strategy and maximizing the improvement in product competitiveness and sustainability. In comparison with the simultaneous application of existing mono-criteria optimization methodologies (such as “Design to Cost” or “Eco Design”) and subjective expert-based reviews, the novel methodology has a reduced workload and risks, confirming its potential for future application and further development in other polymer-based products, such as consumer goods or packaging. Full article

(This article belongs to the Special Issue Injection Molding of Polymers)

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20 pages, 7575 KiB

Open AccessArticle

Optimized Micro-Pattern Design and Fabrication of a Light Guide Plate Using Micro-Injection Molding

by Fang-Yu Fan, Hsin-Hua Chou, Wei-Chun Lin, Chiung-Fang Huang, Yi Lin, Yung-Kang Shen and Muhammad Ruslin

Polymers 2021, 13(23), 4244; https://doi.org/10.3390/polym13234244 - 3 Dec 2021

Cited by 2 | Viewed by 3552

Abstract

This study examined the uniformity of illuminance field distributions of light guide plates (LGPs). First, the authors designed microstructural patterns on the surface of an LGP. Then, a mold of the LGP with the optimal microstructural design was fabricated by a photolithography method. Micro-injection molding (μIM) was used to manufacture the molded LGPs. μIM technology can simultaneously manufacture large-sized wedge-shaped LGPs and micro-scale microstructures. Finally, illuminance values of the field distributions of the LGPs with various microstructures were obtained through optical field measurements. This study compared the illuminance field distributions of LGPs with various designs and structures, which included LGPs without and those with microstructure on the primary design and the optimal design. The average illuminance of the LGP with microstructures and the optimal design was roughly 196.1 cd/m². Its average illuminance was 1.3 times that of the LGP without microstructures. This study also discusses illuminance field distributions of LGPs with microstructures that were influenced by various μIM process parameters. The mold temperature was found to be the most important processing parameter affecting the illuminance field distribution of molded LGPs fabricated by μIM. The molded LGP with microstructures and the optimal design had better uniformity than that with microstructures and the primary design and that without microstructures. The uniformity of the LGP with microstructures and the optimal design was roughly 86.4%. Its uniformity was nearly 1.65 times that of the LGP without microstructures. The optimized design and fabrication of LGPs with microstructure exhibited good uniformity of illuminance field distributions. Full article

(This article belongs to the Special Issue Injection Molding of Polymers)

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13 pages, 3720 KiB

Open AccessArticle

Optimization of Injection-Molding Process for Thin-Walled Polypropylene Part Using Artificial Neural Network and Taguchi Techniques

by Mehdi Moayyedian, Ali Dinc and Ali Mamedov

Polymers 2021, 13(23), 4158; https://doi.org/10.3390/polym13234158 - 28 Nov 2021

Cited by 27 | Viewed by 4033

Abstract

Plastics are commonly used engineering materials, and the injection-molding process is well known as an efficient and economic manufacturing technique for producing plastic parts with various shapes and complex geometries. However, there are certain manufacturing defects related to the injection-molding process, such as short shot, shrinkage, and warpage. This research aims to find optimum process parameters for high-quality end products with minimum defect possibility. The Artificial Neural Network and Taguchi Techniques are used to find a set of optimal process parameters. The Analytic Hierarchy Process is used to calculate the weight of each defect in the proposed thin-walled part. The Finite Element Analysis (FEA) using SolidWorks plastics is used to simulate the injection-molding process for polypropylene parts and validate the proposed optimal set of process parameters. Results showed the best end-product quality was achieved at a filling time of 1 s, cooling time of 3 s, pressure-holding time of 3 s, and melt temperature of 230 °C. The end-product quality was mostly influenced by filling time, followed by the pressure-holding time. It was found that the margin of error for the proposed optimization methods was 1.5%, resulting from any uncontrollable parameters affecting the injection-molding process. Full article

(This article belongs to the Special Issue Injection Molding of Polymers)

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