Soft Tooling Process Research Articles

Enabling Micro Injection Moulding Using a Soft Tooling Process Chain with Inserts Made of Mortar Material

The manufacturing of inserts for micro injection moulding made of mortar material is presented in this work. The fabrication of the mortar insert described in this publication relied on a versatile and relatively fast rapid prototyping process based on soft tooling. The mortar insert has a QR code with micro features on its surface, which was replicated in acrylonitrile butadiene styrene (ABS) polymer by the micro injection moulding process. With this approach, it is possible to fabricate hard inserts for micro injection moulding purposes that are able to compete with conventional-made inserts made of tool steel.

Soft tooling process chain for the manufacturing of micro-functional features on molds used for molding of paper bottles

Paper-based packaging products, due to their excellent sustainable properties are preferred over the glass, plastic, and metal-based packaging solutions. The paper bottle molding process is very new in this category, and the tooling aspect is not well explored. Existing tooling solutions offer certain limitations in the molding process such as clogging of channels, low open-area fraction, low fatigue life, and longer cycle times. With the utilization of additive manufacturing techniques, the tooling can not only be made more economical and produced in shorter time duration but also more efficient. VAT photopolymerization based soft tooling process chain is highlighted and discussed in this work. Design of micro-features and their fabrication is carried out using UV light mask projection method. A characterization approach for precision manufacturing of micro-features using X-ray Computed Tomography is also discussed. Validation of the soft tooling process chain and its effectiveness against the conventional tools is presented and discussed in this work. It is shown that the proposed soft tooling process chain for the manufacturing of molds for paper bottle production is a better performing and cheaper alternative to existing solutions implemented in industry.

Experimental investigation and thermo-mechanical modelling for tool life evaluation of photopolymer additively manufactured mould inserts in different injection moulding conditions

There is a growing interest for integrating additive manufacturing (AM) technology in different manufacturing processes such as injection moulding (IM) due to the possibility of achieving shorter manufacturing times and increased cost effectiveness. This paper evaluates IM inserts fabricated by the AM vat photopolymerisation method. The inserts are directly manufactured with a photopolymer material, integrated on an injection moulding tool and subsequently used for IM. Therefore, particular attention has to be paid in order to develop the soft tooling process chain and the IM experimental procedure as detailed in this study. Different combinations of IM parameters are investigated in this work in order to determine the influence of the various process settings on the inserts’ performance (lifetime, crack propagation, consistency of the mould surface features). The mould inserts were analysed by three-dimensional optical metrology and evaluated with regard to the different surface features that were affected by the IM process. A three-dimensional thermo-mechanical with phase change model for the analysis of the effects of the IM process on the additive manufactured tools was accomplished in the FE software COMSOL Multiphysics. The potential causes for the insert failure are identified both by means of the IM experiments and the numerical model. The developed model could also predict the thermally induced deformations produced in the mould and identify where this phenomenon would eventually lead to defects in the shape of the parts. The influence of three different temperatures of the insert at 25 °C, 50 °C and 100 °C on the failure of the insert was investigated. Also a detailed discussion about the solidification and temperature changes is given.

A Soft Tooling Process Chain for Injection Molding of a 3D Component with Micro Pillars

The purpose of this paper is to present the method of a soft tooling process chain employing Additive Manufacturing (AM) for fabrication of injection molding inserts with micro surface features. The Soft Tooling inserts are manufactured by Digital Light Processing (vat photo polymerization) using a photopolymer that can withstand relatively high temperaturea. The part manufactured here has four tines with an angle of 60°. Micro pillars (Ø200 µm, aspect ratio of 1) are arranged on the surfaces by two rows. Polyethylene (PE) injection molding with the soft tooling inserts is used to fabricate the final parts. This method demonstrates that it is feasible to obtain injection-molded parts with microstructures on complex geometry by additive manufactured inserts. The machining time and cost is reduced significantly compared to conventional tooling processes based on computer numerical control (CNC) machining. The dimensions of the micro features are influenced by the applied additive manufacturing process. The lifetime of the inserts determines that this process is more suitable for pilot production. The precision of the inserts production is limited by the additive manufacturing process as well.

A Soft Tooling Process Chain for Injection Molding of a 3D Component with Micro Pillars.

The purpose of this paper is to present the method of a soft tooling process chain employing Additive Manufacturing (AM) for fabrication of injection molding inserts with micro surface features. The Soft Tooling inserts are manufactured by Digital Light Processing (vat photo polymerization) using a photopolymer that can withstand relatively high temperaturea. The part manufactured here has four tines with an angle of 60°. Micro pillars (Ø200 µm, aspect ratio of 1) are arranged on the surfaces by two rows. Polyethylene (PE) injection molding with the soft tooling inserts is used to fabricate the final parts. This method demonstrates that it is feasible to obtain injection-molded parts with microstructures on complex geometry by additive manufactured inserts. The machining time and cost is reduced significantly compared to conventional tooling processes based on computer numerical control (CNC) machining. The dimensions of the micro features are influenced by the applied additive manufacturing process. The lifetime of the inserts determines that this process is more suitable for pilot production. The precision of the inserts production is limited by the additive manufacturing process as well.

A Soft Tooling process chain employing Additive Manufacturing for injection molding of a 3D component with micro pillars

The purpose of the research presented in this paper is to investigate the capability of a soft tooling process chain employing Additive Manufacturing (AM) for preproduction of an insert with micro features by injection molding. The Soft Tooling insert was manufactured in a high temperature photopolymer by Digital Light Processing (vat photopolymerization). The mold cavity was formed by two insert halves, by design; both inserts have four angled tines, with micro holes (Ø200μm, 200μm deep) on the surface. Injection molding with polyethylene was used with the soft tool inserts to manufacture the final production components. The diameter and height of the pillars that were replicated on the molded components were characterized by means of a 3D profilometer. The influence of the injection molding parameters on the replication was evaluated using a 2-levels DOE of three factors. The uniformity of the pillars are also evaluated regarding the diameter and height.

Genetic Algorithm–Based Design and Development of Particle-Reinforced Silicone Rubber for Soft Tooling Process

In order to enhance the solidification rate of soft tooling process, design of a silicone rubber composite mold material is carried out based on multiobjective optimization (MOO) of conflicting objectives. The elitist nondominated sorting genetic algorithm (NSGA-II), a genetic algorithm–based MOO tool, is used to find the optimum parameters first by obtaining the Pareto-optimal front and then selecting a single solution or a small set of solutions for manufacturing applications using a suitable multi-criterion decision making technique. Based on the optimal design parameters, an experimental study in soft tooling process is carried out in particle-reinforced silicone, and it is observed that the solidification time is minimized appreciably keeping the same advantages of soft tooling process.

Design of particle-reinforced polyurethane mould materials for soft tooling process using evolutionary multi-objective optimization algorithms

Polyurethane is used for making mould in soft tooling (ST) process for producing wax/plastic components. These wax components are later used as pattern in investment casting process. Due to low thermal conductivity of polyurethane, cooling time in ST process is long. To reduce the cooling time, thermal conductive fillers are incorporated into polyurethane to make composite mould material. However, addition of fillers affects various properties of the ST process, such as stiffness of the mould box, rendering flow-ability of melt mould material, etc. In the present work, multi-objective optimization of various conflicting objectives (namely maximization of equivalent thermal conductivity, minimization of effective modulus of elasticity, and minimization of equivalent viscosity) of composite material are conducted using evolutionary algorithms (EAs) in order to design particle-reinforced polyurethane composites by finding the optimal values of design parameters. The design parameters include volume fraction of filler content, size and shape factor of filler particle, etc. The Pareto-optimal front is targeted by solving the corresponding multi-objective problem using the NSGA-II procedure. Then, suitable multi-criterion decision-making techniques are employed to select one or a small set of the optimal solution(s) of design parameter(s) based on the higher level information of the ST process for industrial applications. Finally, the experimental study with a typical real industrial application demonstrates that the obtained optimal design parameters significantly reduce the cooling time in soft tooling process keeping other processing advantages.

Effective properties of particle reinforced polymeric mould material towards reducing cooling time in soft tooling process

AbstractCooling time in soft tooling process using conventional mold materials is normally high. Although increase of effective thermal conductivity of mold material by inclusion of high thermally conductive fillers reduces the cooling time, it affects other properties (namely, stiffness of mold box and flow ability of melt mold material), which play important roles in soft tooling process. Therefore, to apply composite polymer in soft tooling process as mold material simultaneous studies of these properties are important. In this work, extensive experimental studies are made on the effective thermal conductivity, modulus of elasticity and viscosity of composite polymeric mold materials namely Polyurethane and RTV (Room Temperature Vulcanizing)‐2 silicone rubber, with aluminum and graphite particle reinforcements. To find suitable models of the effective properties of composite mold materials, which are required to decide the optimum amount of filler content before actual application, attempts are made to fit the experimental results using various models reported in the literature. Finally, different aspects in reducing cooling time in soft tooling process and further activities are reported. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012

Investigating the role of metallic fillers in particulate reinforced flexible mould material composites using evolutionary algorithms

To reduce the cooling time in soft tooling (ST) process, high thermal conductive fillers (such as metallic filler) are included in flexible mould material. But addition of metallic fillers affects various properties of ST process and the influences may vary according to the types of materials used. Therefore, in order to investigate the role of various metallic fillers in particulate reinforced flexible mould material composites, multi-objective optimizations of maximizing equivalent thermal conductivity and minimizing effective modulus of elasticity of composite mould materials are conducted using evolutionary algorithms (EAs). Here we have adopted two EA-based algorithms namely NSGAII and SPEA2 in order to solve the present problem independently. Comparative study of the results reveals that NSGAII performs better over SPEA2 for investigating the role of metallic fillers in particulate reinforced flexible mould material composites. A recently proposed innovization procedure is also used to unveil salient properties associated with the obtained trade-off solutions. These solutions are analyzed to study the role of various parameters influencing the equivalent thermal conductivity and modulus of elasticity of the composite mould material. Based on the findings through investigations, the optimal selection of materials is suggested including the cost implication factor.

Improvement of Soft Tooling Process Through Particle Reinforcement with Polyurethane Mould

Use of conventional flexible polymeric mould materials yields to longer solidification time of (wax/plastic) patterns in soft tooling process, thereby reducing the rapidity of the process to a great extent, which is not desirable in present competitive market. In this work, approach of particle-reinforcement with mould materials is introduced to reduce the cycle time of Soft tooling process and the resulting cooling time is experimentally investigated in considering a case of manufacturing of a typical wax pattern with aluminium particle filled polyurethane. It is observed that cooling time is significantly reduced particularly with higher loading condition of aluminium filler. This happens due to the increase of effective thermal conductivity of mould material. However, it is also found that the stiffness of mould becomes simultaneously high due to increase of effective modulus of elasticity of mould material. Realizing these facts, an extensive study is carried out to find the effect on equivalent thermal properties and modulus of elasticity of polyurethane composite mould materials with the reinforcement of aluminium and graphite particles independently through rigorous experimentation and correlation of experimental findings with the models cited in literatures.

Experimental investigation on equivalent properties of particle reinforced silicone rubber: Improvement of soft tooling process

The main disadvantage in soft tooling process using conventional flexible reactive polymeric mould materials, namely silicone rubber, is the longer solidification time of (wax/plastic) patterns that yields to reduce the rapidity of the process to a great extent, which is not desirable in the present competitive market. The approach of particle reinforcement with mould materials is introduced here to reduce the cooling time of soft tooling process and the resulting cooling time is experimentally investigated in considering a case of manufacturing of a typical wax pattern with aluminium particle–reinforced silicone rubber mould material. It is observed that cooling time is significantly condensed, particularly with higher loading condition of aluminium filler. This is due to the increase of equivalent thermal conductivity of mould material. However, it is also noticed that at the same time, the stiffness of mould becomes high due to the increase of equivalent modulus of elasticity of mould material. Therefore, in order to effectively utilize the particle-reinforced silicone rubber for preparing mould, it is important to have a perceptive on the equivalent thermal conductivity and modulus of elasticity of composite mould materials with different filler loadings. Based on this realization, an extensive study is carried out to find the effect on equivalent thermal properties and modulus of elasticity of silicone rubber composite mould materials with the reinforcement of various metallic and non-metallic filler particles independently through rigorous experimentation and correlation of experimental findings with the models cited in literatures.

Studies on effective thermal conductivity of particle-reinforced polymeric flexible mould material composites

Due to poor thermal conductivity of conventional flexible polymeric mould materials, the solidification of (wax/plastic) patterns in soft tooling (ST) process takes a longer time. This problem can be solved by increasing the effective thermal conductivity of mould materials through (high thermal conductive) particle reinforcement. Therefore in this study, the equivalent thermal conductivities (ETCs) of particle-reinforced polymeric mould materials, namely silicone rubber and polyurethane are experimentally observed using hot disc technique. Findings show that not only the amount of filler content and type of filler material, but also particle size has significant influence on the effective thermal conductivity of polymer and it starts increasing drastically at 20–30 per cent volume fraction of filler content. To predict the cooling time in ST process, it is important to have an appropriate model of ETC. In this study, a new method is proposed based on a genetic algorithm fuzzy (GA-fuzzy) approach to model the effective thermal conductivity of a two-phase particle-reinforced polymer composites (PCs). The effectiveness of the model is extensively tested in comparison with various empirical expressions reported in literature based on the experimental measurements. It has been found that the model based on GA-fuzzy approach not only outperforms the existing models, but also possesses a generic one applicable to a wide range of two-phase particle-reinforced PCs.

Investigating the Role of Nonmetallic Fillers in Particulate-Reinforced Mold Composites using EAs

In the soft tooling (ST) process, flexible polymeric materials (namely, silicone rubber, polyurethane, etc.) are used for making mold for producing wax pattern. Due to low thermal conductivity of mold materials, the ST process takes longer time for cooling. Hence, to reduce the cooling time, thermal conductive fillers are included in mold materials. But addition of fillers affects various properties of ST process (such as stiffness of the mold box) and the influences may vary according to the types of materials used. Therefore, in the present work, multiobjective optimizations of equivalent thermal conductivity and effective modulus of elasticity of composite mold materials are conducted using evolutionary algorithms in order to investigate the role of various nonmetallic fillers in particulate reinforced mold material composites. We have adopted NSGA-II to optimize the conflicting objectives—maximization of thermal conductivity and minimization of modulus of elasticity. A recently proposed innovization procedure is used to unveil salient properties associated with the trade-off solutions. The obtained Pareto fronts are used successfully to study the role of various parameters influencing the equivalent thermal conductivity and modulus of elasticity of the composite mold material. The optimal selection of materials is suggested in consideration with the cost implication factor based on the findings through investigations.

Effect on cooling time in soft tooling process using particle reinforcement with polyurethane mould material

Use of conventional flexible polymeric mould materials yields to longer solidification time of (wax/plastic) patterns in soft tooling (ST) process. Thereby, reducing the rapidity of the process to a great extent which is not desirable in present competitive market. In this work, approach of particle reinforcement with mould materials is introduced to increase the productivity of ST process and the resulting cooling time is experimentally investigated in considering a case of manufacturing of a typical wax pattern with aluminium filled polyurethane (PU). It is observed that cooling time is significantly reduced particularly with higher loading condition of aluminium filler due to the increase of equivalent thermal conductivity (ETC) of mould material. But simultaneously, it is also found that the stiffness of mould becomes high due to increase of equivalent modulus of elasticity of mould material. Realising these facts, an extensive experimental study is carried out to find the effect on equivalent thermal properties and modulus of elasticity of PU composites by reinforcing aluminium and graphite particles independently with different loading conditions. The existing models of ETC and modulus of elasticity of composites are also tried to validate based on the experimental findings.

Studies on Equivalent Viscosity of Particle-Reinforced Flexible Mold Materials Used in Soft Tooling Process

To reduce the cooling time in soft tooling process, one of the possible solutions is the use of composite mold materials, but that may affect melt mold flow properties. Therefore, a study on equivalent viscosity of melt mold material, which primarily influences the flow ability is essential. In this work, we have carried out an experimental study on equivalent viscosity of flexible mold materials (such as polyurethane and silicone rubber, which are of particular type) reinforced with highly thermal conductive filler particles, namely, aluminum and graphite powder. It has been observed that in addition to an increase of equivalent viscosity, different curing behaviors were noticed in mold materials reinforced with different fillers. By analyzing the performances of various equivalent viscosity models reported in literature, it has been observed that for higher particle size, the existing models deviate much from the experimental results. We have proposed an extension of the generalized model of Arefinia and Shojaei by including a factor that depends on particle size. It is found that the extension model provides better explanations compared to other models to the experimental results, especially for suspensions of flexible mold materials with higher particle sizes. Finally, a predictive approach is suggested for the equivalent viscosity of reinforced flexible mold materials, which may be useful to decide the amount of typical filler particles to be considered for mixing with a flexible mold material.