The additive manufacturing (AM) of injection molding inserts has gained popularity during recent years primarily due to the reduced design-to-production time and form freedom offered by AM. In this paper, topology optimization (TO) is performed on a metallic mold insert which is to be produced by the Laser Powder Bed Fusion (LPBF) technique. First, a commercially available TO software is used, to minimize the mass of the component while ensuring adequate mechanical response under a prescribed loading condition. The commercial TO tool adopts geometry-based AM constraints and achieves a mass reduction of ~50 %. Furthermore, an in-house TO method has been developed which integrates a simplified AM process model within the standard TO algorithm for addressing the issue of local overheating during manufacturing. The two topology optimized designs are briefly compared, and the advantages of implementing manufacturing constraints into the TO algorithm are discussed.
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... The conducted studies confirm the importance of using the system, part, and process design approach and having efficient design as the selection criterion. The objective of efficient design is to improve the efficiency and performance of the tool in operation, i.e. shorter cycle time, avoidance of stops, minimization (or elimination) of the rejections, improved quality, maximization of the production efficiency etc. [11,25,. ...
... Efficient design is of particular significance for the production tools in hot working and injection molding. The importance of process design and its close relationship to part and system design is illustrated in . ...
... The conducted studies have shown that efficient operational performance as the target yields the best results as the tool, die, or mold is designed for and made by L-PBF [1,11,25,. This review shows that it is possible to improve this operational performance by adding LMPp (DED-p, LC) for surface functionalization  and tool, die, or mold remanufacture [52,. ...
This paper explores the possibilities to use laser-based additive processes to make, surface treat and repair/remanufacture tools, dies and molds for cold working, hot working, and injection molding. The failures encountered in these applications are described. The materials used conventionally and in the laser additive processes are accounted for. The properties of the tools, dies and molds made by Laser-based Powder Bed Fusion (L-PBF) are as good as and in some cases better than the properties of those made in wrought materials. Shorter cycle time, reduced friction, smaller abrasive wear, and longer life cycle are some of the benefits of L‑PBF and Directed Energy Deposition with powder (DED-p) (or Laser Metal Deposition with powder, LMD‑p, or Laser Cladding, LC). L‑PBF leads to higher toolmaking costs and shorter toolmaking lead time. Based on a review of conducted investigations, this paper shows that it is possible to design and make tools, dies and molds for and by L‑PBF, surface functionalize them by DED-p (LMD‑p, LC), and repair/remanufacture them by DED-p (LMD‑p, LC). With efficient operational performance as the target for the whole tool life cycle, this combination of L‑PBF and DED-p (LMD‑p, LC) has the greatest potential for hot working and injection molding tools and the smallest for cold working tools (due to the current high L‑PBF and DED-p (LMD‑p, LC) costs).
... An L-PBF inclusive manufacturing of the tooling for injection molding has been addressed in many studies. The possibility to design, manufacture and use conformal cooling channels has been subject to investigation from different perspectives in the many of these studies [59, Figure 29. ...
... The height = the outer diameter = 200 mm, the outer skin thickness = 6 mm, and the lattice diameter = 0.5 mm in Figure 30 As mentioned above, the implementation of conformal cooling channels to enhance the cooling efficiency has been the most common example of L-PBF design freedom in the injection molding sector and corresponding academic research. To benefit further from the L-PBF potential, the removal of excessive non-contributing material, topology optimization, should also be considered . ...
... In this study, two topology optimization methods were considered and used : ...
The journey of production tools in cold working, hot working, and injection molding from rapid tooling to additive manufacturing (AM) by laser-based powder bed fusion (L-PBF) is described. The current machines and their configurations, tool steel powder materials and their properties, and the L-PBF process parameters for these materials are specified. Examples of production tools designed for and made by L-PBF are described. Efficient design, i.e., high tooling efficiency and performance in operation, should be the primary target in tool design. Topology and lattice structure optimization provide additional benefits. Using efficient design, L-PBF exhibits the greatest potential for tooling in hot working and injection molding. L-PBF yields high tooling costs, but competitive total costs in hot working and injection molding. Larger object sizes that can be made by L-PBF, a larger number of powder metals that are designed for different tooling applications, lower feedstock and L-PBF processing costs, further L-PBF productivity improvement, improved surface roughness through L-PBF, and secured quality are some of the targets for the research and development in the future. A system view, e.g., plants with a high degree of automation and eventually with cyber-physically controlled smart L-PBF inclusive manufacturing systems, is also of great significance.
... Therefore, a significant portion of current AM research is focussed on investigating these different aspects of precision, namely the repeatability, predictability, and robustness of the process. Various approaches have been employed for this purpose, including investigating the design for precision AM using topology optimization , computational modeling of the L-PBF process , and statistical process optimization studies . These methods are also complemented by studies on improving methods for the finishing of parts , as well as for metrology . ...
... In particular, Sinico et al. compared two topology optimization (TO) techniques-one based on commercial software and another based on an in-house developed TO method that also compensates for localized overheating caused during part manufacturing. This work discusses the precision benefits that are achieved when manufacturing constraints are included within topology optimization, rather than just purely geometric constraints . Bayat et al. developed a multi-physic numerical model of the L-PBF process, which was then used to track the formation of porosities that cause imprecision while printing. ...
The rise in popularity of Additive Manufacturing technologies and their increased adoption for manufacturing have created a requirement for their fast development and maturity. However, there is still room for improvement when compared with conventional manufacturing in terms of the predictability, quality, and robustness. Statistical analysis has proven to be an excellent tool for developing process knowledge and optimizing different processes efficiently and effectively. This paper uses a novel method for printing overhanging features in Ti-6Al-4V metal parts, by varying process parameters only within the down-facing area, and establishes a methodology for predicting dimensional errors in flat 45° down-facing surfaces. Using the process parameters laser power, scan speed, scan spacing, scan pattern, and layer thickness, a quadratic regression equation is developed and tested. An Analysis of variance (ANOVA) analysis concluded that, within the down-facing area, the laser power is the most significant process parameter, followed by the layer thickness and scan speed. Comparatively, the scanning pattern is determined to be insignificant, which is explained by the small down-facing area where the various scanning patterns play no role. This paper also discusses the interaction effects between parameters. Some thoughts on the next steps to be taken for further validation are discussed.
... Lastly, it was shown here that extension of the hotspot constraint to a 3D setting is straightforward. This is also exemplified by Sinico et al. (2019) where the method was applied for TO of an industrial injection mold design. Experimental validation of 3D designs using optical tomography-based in situ monitoring technique is currently under investigation. ...
A novel constraint to prevent local overheating is presented for use in topology optimization (TO). The very basis for the constraint is the Additive Manufacturing (AM) process physics. AM enables fabrication of highly complex topologically optimized designs. However, local overheating is a major concern especially in metal AM processes leading to part failure, poor surface finish, lack of dimensional precision, and inferior mechanical properties. It should therefore be taken into account at the design optimization stage. However, including a detailed process simulation in the optimization would make the optimization intractable. Hence, a computationally inexpensive thermal process model, recently presented in the literature, is used to detect zones prone to local overheating in a given part geometry. The process model is integrated into density-based TO in combination with a robust formulation, and applied in various numerical test examples. It is found that existing AM-oriented TO methods which rely purely on overhang control do not ensure overheating avoidance. Instead, the proposed physics-based constraint is able to suppress geometric features causing local overheating and delivers optimized results in a computationally efficient manner.
... A comparison between two designs was presented in a paper by Sinico et al. one design created using a commercial software, Siemens NX, and the other using an in-house method developed to integrate an algorithm to address the issue of local overheating during the LPBF process. Promising results were achieved in both cases [128,204]. ...
In this PhD project at DTU MEK, Mandaná Moshiri investigated how to define an integrated process chain for first time production of mould components to be used for plastic injection moulding using laser powder bed fusion metal additive manufacturing (AM) technologies. This technology is already used for fabricating injection moulding components, but its maturity and readiness for full-scale industrial applications it is still far from reality. Mandaná articulated her project over five main topics, each addressing a specific aspect for the major development of AM and its full adoption in the manufacturing industry. The topics started from a clear assessment of the advantages of using AM over conventional manufacturing in terms of technologies required and production cost impact, followed by an AM machines benchmarking to understand what are the current capabilities and limitations of AM. The technology gap between what AM can deliver and what it is required by injection moulding industrial applications was defined, exploring also new way of exploiting AM products for mould inserts, beyond the well-known enhancement of thermal management. In the last two topics, the systems and research areas for creating an integrated first-time-right process chain were analysed in the context of the Industry 4.0 framework including key-enabling technologies such as monitoring and simulation.
Additive manufacturing (AM) is a fast-growing sector with the ability to evoke a revolution in manufacturing due to its almost unlimited design freedom and its capability to produce personalised parts locally and with efficient material use. AM companies, however, still face technological challenges such as limited precision due to shrinkage, built-in stresses, and limited process stability and robustness. Moreover, often post-processing is needed due to the high roughness and remaining porosity. Qualified, trained personnel are also in short supply.
In recent years, there have been dramatic improvements in AM design methods, process control, post-processing, material properties and material range. However, if AM is going to gain a significant market share it must be developed into a true precision manufacturing method. The production of precision parts relies on three principles:
1. Production is robust (i.e. that all sensitive parameters can be controlled).
2. Production is predictable (for example, the shrinkage that occurs is acceptable because it can be predicted and compensated in the design).
3. Parts are measurable (as without metrology, accuracy, repeatability and quality assurance cannot be known).
AM of metals is inherently a high-energy process, with many of sensitive and inter-related process parameters, making it susceptible to thermal distortions, defects and process drift. The complete modelling of these processes is beyond current computational power and novel methods are needed to practicably predict performance and inform design. In addition, metal AM produces highly textured surfaces and complex surface features that stretch the limits of contemporary metrology. With so many factors to consider, there is a significant shortage of background material on how to inject precision into AM processes. Shortage in such material is an important barrier for a wider uptake of advanced manufacturing technologies and a comprehensive book is thus needed.
This book aims to inform the reader how to improve the precision of metal AM processes by tackling the three principles of robustness, predictability and metrology, and by developing computer-aided engineering methods that empower rather than limit AM design.
Featured Application: This paper presents the first investigations towards closed loop feedback control of the selective laser melting (SLM) process. Insight gained from this work can be applied to facilitate in-process optimization of the SLM process for maximizing part quality and minimizing surface roughness.
Abstract: Additive manufacturing provides a number of benefits in terms of infinite freedom to design complex parts and reduced lead-times while globally reducing the size of supply chains as it brings all production processes under one roof. However, additive manufacturing (AM) lags far behind conventional manufacturing in terms of surface quality. This proves a hindrance for many companies considering investment in AM. The aim of this work is to investigate the effect of varying process parameters on the resultant roughness of the down-facing surfaces in selective laser melting (SLM). A systematic experimental study was carried out and the effects of the interaction of the different parameters and their effect on the surface roughness (Sa) were analyzed. It was found that the interaction and interdependency between parameters were of greatest significance to the obtainable surface roughness, though their effects vary greatly depending on the applied levels. This behavior was mainly attributed to the difference in energy absorbed by the powder. Predictive process models for optimization of process parameters for minimizing the obtained Sa in 45 • and 35 • down-facing surface, individually, were achieved with average error percentages of 5% and 6.3%, respectively, however further investigation is still warranted.
Manufacturing-oriented topology optimization has been extensively studied the past two decades, in particular for the conventional manufacturing methods, for example, machining and injection molding or casting. Both design and manufacturing engineers have benefited from these efforts because of the close-to-optimal and friendly-to-manufacture design solutions. Recently, additive manufacturing (AM) has received significant attention from both academia and industry. AM is characterized by producing geometrically complex components layer-by-layer, and greatly reduces the geometric complexity restrictions imposed on topology optimization by conventional manufacturing. In other words, AM can make near-full use of the freeform structural evolution of topology optimization. Even so, new rules and restrictions emerge due to the diverse and intricate AM processes, which should be carefully addressed when developing the AM-specific topology optimization algorithms. Therefore, the motivation of this perspective paper is to summarize the state-of-art topology optimization methods for a variety of AM topics. At the same time, this paper also expresses the authors’ perspectives on the challenges and opportunities in these topics. The hope is to inspire both researchers and engineers to meet these challenges with innovative solutions.
Additive Manufacturing (AM) enables fabrication of geometrically complex designs and hence offers increased freedom for designers. It has been recognized that topology optimization can serve as an ideal design tool in order to fully exploit the advantages offered by AM. However, AM processes have specific limitations which should be taken into account at the design optimization stage in order to minimize manual design adaptations and post processing cost. One such major constraint is local overheating during processing. It is evident that excessive local heating can cause defects such as melt ball formation which subsequently leads to poor surface finish and undesired mechanical properties. This paper presents a simplified thermal model inspired by the physics of additive processes and detects zones of local heat concentration i.e. `hotspots' in a geometry. Although the model emulates the boundary conditions of an AM layer and predicts the temperature field, it is not a detailed process simulation. Instead, a dedicated computationally inexpensive thermal analysis has been preferred here as it proves to be able to identify regions which are prone to overheating. The model is thus referred to as 'hotspot detector'. A mathematical formulation is developed in order to integrate the 'hotspot detector' model with the density based topology optimization using adjoint sensitivity calculation method. The new method is tested and demonstrated on several numerical examples.
Additive manufacturing (AM) enables the fabrication of parts of unprecedented complexity. Dedicated topology optimization approaches, that account for specific AM restrictions, are instrumental in fully exploiting this capability. In popular powder-bed-based AM processes, the critical overhang angle of downward facing surfaces limits printability of parts. This can be addressed by changing build orientation, part adaptation, or addition of sacrificial support structures. Thus far, each of these measures have been studied separately and applied sequentially, which leads to suboptimal solutions or excessive computation cost. This paper presents and studies, based on 2D test problems, an approach enabling simultaneous optimization of part geometry, support layout and build orientation. This allows designers to find a rational tradeoff between manufacturing cost and part performance. The relative computational cost of the approach is modest, and in numerical tests it consistently obtains high quality solutions.
Additive manufacturing (AM) techniques such as selective laser melting (SLM) can enable the construction of injection moulding (IM) tools with conformal cooling channels that significantly improve performance through higher cooling uniformity and reduced cycle times. Design of IM cooling systems is typically achieved using commercial IM numerical modelling software originally developed for conventionally cooled mould designs. However, the accuracy of IM modelling software in predicting the performance of SLM manufactured tools with conformal cooling, across a range of moulding materials and processing conditions, has not been thoroughly evaluated in the literature. Furthermore, the SLM manufacturability and mechanical properties of tool steels typically applied in IM, such as AISI H13, are not well documented. This work addresses these deficiencies through the following: quantification of SLM H13 material properties, in particular fatigue strength which has not been previously reported; design and manufacture of a mould tool with easily exchangeable conventionally and conformally cooled inserts; and subsequent experimental validation of IM simulation software predictions under a range conditions. Result of mechanical testing showed SLM H13 parts to offer lower mechanical properties in the as-built condition compared to conventional materials; however, these increased substantially following residual stress reduction with heat treatment. Evaluation of the temperature prediction accuracy of IM numerical models showed generally high accuracy for conformally cooled SLM tools, although marginally lower when compared to conventionally cooled moulds. The outcomes of this work offer designers typical material property data for SLM manufactured H13 tooling, as well as an indication of the expected prediction accuracy of current commercial IM simulation software when applied to conformally cooled SLM tooling.
This work presents implementation of numerical analysis and topology optimization techniques for redesigning traditional injection molding tools. Traditional injection molding tools have straight cooling channels, drilled into a solid body of the core and cavity. The cooling time constitutes a large portion of the total production cycle that needs to be reduced as much as possible in order to bring in a significant improvement in the overall business of injection molding industry. Incorporating conformal cooling channels in the traditional dies is a highly competent solution to lower the cooling time as well as improve the plastic part quality. In this paper, the thermal and mechanical behavior of cavity and core with conformal cooling channels are analyzed to find an optimum design for molding tools. The proposed design with conformal cooling channels provides a better alternative than traditional die designs with straight channels. This design is further optimized using thermo-mechanical topology optimization based on a multiscale approach for generating sound porous structures. The implemented topology optimization results in a light-weight yet highly effective die cavity and core. The reduction in weight achieved through the design of dies with porous structures is meant to facilitate the adoption of additive manufacturing for die making by the tooling industry.
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).
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.
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.
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.
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.
Additive Manufacturing allows for considerably more form freedom compared to existing manufacturing
technologies but still faces the limitation of building overhanging parts. The overhang limitation in additive
manufacturing prevents the direct production of topology optimized parts. We present an overhang constraint
that incorporates this manufacturing limitation into topology optimization. The overhanging regions in a design
iteration are detected using front propagation and a global constraint is formulated by aggregating the local
constraints within the design domain. Since the constraint is formulated in a continuous manner, it can be
discretized for any type of mesh, and with an arbitrary minimum allowable overhang angle. Furthermore, it is
easily extensible to 3D. The Ordered Upwind Method is used to solve the constraint, and adjoint sensitivities
are used for efficient evaluation. The newly developed constraint is demonstrated on 2D examples having an
unstructured mesh. Overhang free designs are obtained with smooth convergence behaviour.