Optimization is the search for one or more better solutions to a certain problem. Within this sector, an optimizer is a software able to identify, suggest and eventually verify the ideal set of input variables that provides the best design solutions among all those possible. In most cases, the underlying relationships between the control parameters (called inputs) and the measured performances (called outputs) are unknown or difficult to solve. Sometimes, moreover, in order to obtain the answer of the system it is necessary to use complex numerical models that require a lot of time in order to be able to produce the desired output: a typical example is that of the use of simulators of foundry process, in which the result of the simulation, in function of the chosen parameters, is the fruit of a long and complex calculation of 3D thermofluid dynamics. Figure 1 - Optimization process scheme The IMPROVEit optimization software is able to interface with multiple applications, including the FLOW-3D® CAST (Flow Science inc.) process simulator, and connect them together to completely define a workflow that can be run repeatedly and automatically in order to get the best solution in the shortest possible time, understanding the nature and complexity of the problem. Case study: Optimization of the injection phase In this case study, courtesy of FORM S.r.l., during the design of the moulding for battery covers by HPDC, many areas were found in the structure where the amount of porosity from gas was high. It was therefore decided to use the optimization with the aim of reducing defects by acting on the design of the casting channels and optimizing the speed of the piston. For our purposes, the workflow inputs chosen were the values of the piston speed curve in the first phase and a wide range of geometric parameters of the channels managed by interaction between optimizer and parametric CAD software, while the objectives were the best calibration of the arrival of the metal at the casting connections and the reduction of the amount of air trapped in the alloy during this first phase of filling. The flow is structured as follows: the optimizer interacts directly with a parametric CAD software to automatically change the shape of the casting channels and then exports the geometries in STL format; the latter are then used by the process software to simulate the filling, after which the desired outputs are extracted and processed. Figure 2 - Parameters for the optimization of the injection phase, courtesy of Form S.r.l. When there are two objectives to evaluate at the same time, it is possible to find a series of different optimal results of compromise between the two outputs sought, which is called front of Pareto. Since a workflow cycle takes an average of about 20 minutes, it was decided to perform the optimization on a total of 20 calls. On the basis of these calls, the chosen configuration is positioned in the center of the Pareto front and therefore presents a good compromise to have a low and most uniform possible arrival time at the casting attacks, 10% better than the initial setup, and at the same time obtain a minimum quantity of trapped air, 13% lower than the initial data. Figure 3 - Comparison between initial and optimized solution, courtesy of Form S.r.l. This case study therefore shows how the automation and numerical optimization of product design, simulation, interpretation of results and changes, help to save a lot of time and how it is possible to achieve important improvements even in the face of a limited number of calls. … [Read more...]

## Design optimization for mass production

Introduction The development of a product involves various phases of calculation and design that provide a series of predefined steps to follow in order to reach mass production. With this aim in mind and considering the high number of parts to be produced, any material saving is advantageous and relevant from an economic perspective. The parties involved in the production need to reduce the waste material (relevant for the foundry) and to reduce the weight of the components (relevant for the end customer). Optimizing the shape of the product helps both parties (foundry and customer) to reach the right compromise to make the adequate savings while obtaining the highest quality parts. In this article we will show the design optimization process of a foundry product destined for mass production using an optimization software and a process simulator. The aim is to analyze the solidification of the metal present in the system of interest and to evaluate how the optimization helps both parties to benefit from it. Component to produce The component to optimize in this study is produced by sand molded casting technique, one of the oldest, simplest and most economical techniques. The preliminary design phase has provided a prototype in stereolithography format (STL), which is already potentially good for production (courtesy of Flow Science Deutschland). In the image [Figure 1] you can see the feeding system (in yellow) and the geometry of the part to be produced (in red). The weight of the part itself in this starting configuration is 2,197kg, and the whole system weight is 3,126kg. The main objective is, by acting on some details of the geometries themselves, to obtain a total weight of the system as small as possible without having significant porosity in the part. In order to obtain the best possible result, the parameters chosen to be modified are the size of the feeder [Figure 2], the thickness of the vertical wall closest to the feeder and the thickness of the transition zone between the two walls [Figure 3]. Figure 2 - First optimization parameter Figure 3 - Second and third optimization parameters The considered variables are thus potentially multiple and exploring manually all the possible combinations can be a very long and complex work. That is why we have chosen to use a numerical optimizer able to explore the solutions independently. Therefore, IMPROVEit was chosen, which thanks to its simple interface allows to perform both the setup phase and the processing of results easily. FLOW-3D® CAST was chosen as the process simulator for its precision, reliability and simple use in foundry simulations. As for modifying the geometrical shape, the optimization software allows both to interact directly with parametric CAD if the file is in original format, and to modify an STL file directly inside IMPROVEit if, as it is the case in this test, only the latter is available. Once the parameters to be corrected have been selected, the software is able to internally modify the shape of the geometries, launch the solidification simulations interacting with the FLOW-3D® CAST process software using the modified geometries, extract the results of the analyses and process them with suitable mathematical nodes to obtain the right optimized quantity. [Figure 4] shows the workflow of our case study. Figure 4 - Optimization workflow In order to detect the shrinkage porosity dimension present at the end of the solidification simulation, four control volumes divide the geometry in four distinct zones: the top part is in dark blue, the central part in yellow, the left part in cyan and the right part in magenta. According to the customers’ exigences, among those four parts only three are relevant for optimization: the porosity in the top part (dark blue) is not considered. In the initial configuration, the total shrinkage porosity volume in the three control volumes is 581mm3. Figure 5 - Control volumes Execution For the purpose of the optimization process, two objectives and one constraint were chosen: minimizing the feeding system and the part’s weight while having the amount of porosity in the three control volumes below a threshold low enough to be able to consider the part free from visible defects. Setting up an optimization with two objectives and a constraint makes the understanding of the problem complex; nevertheless, the IMPROVEit engine being developed specifically for this type of problem, it allows to obtain an excellent result with just a few calls of the process simulator. Since each optimization cycle lasts only a few minutes, it was decided to allow the execution of fifty cycles. Considerations After fifty cycles, IMPROVEit was able to propose a wide range of solutions that reduce the weight of the system with tolerable thresholds of porosity, which was our objective. Moreover, by analyzing the panorama of the solutions found, it is possible to … [Read more...]