Value Engineering
During the lifecycle of a particular product, companies tend to review the existing design to look out for ways to reduce production cost. Even when coming up with a new product, so many manufacturers go for analyzing the same during its design phase so that it requires an optimum level of cost to produce. This is where Value Engineering comes in. Value engineering is an organized method to improve the “value” of a product or service in the lowest of cost. VE is a systematic approach aimed at obtaining the necessary functions in a product, process, or system at the minimum overall cost, thereby maintaining the quality, reliability, performance, and safety. It provides the substitution of materials and methods with less expensive alternatives, without jeopardizing the functionality. It is emphasized totally on the functions of various components and materials, rather than their physical characteristics. Value engineering is also called value analysis. It was Lawrence Miles who came up with the concept of finding substitute materials for parts unavailable. It was found that substitutions not only reduced cost but aided in a better-finished product. It was this new technique that evolved into value engineering today. The value in VE means two components: The function of a product is the specific task it was designed to perform, and the cost refers to the cost of the item during its life cycle. The ratio of function to cost denotes that the value of a product can be increased by either improving its function or decreasing its cost. In value engineering, the cost related to production, design, maintenance, and replacement are included in the analysis. If we take an example of a new tech product which is being designed and is slated to have a life cycle of only two years; the product will be designed with the least expensive materials and resources that will live up to the end of the product’s lifecycle, saving the manufacturer and the end-user money. This is how product value is improved by reducing costs. It is evident that with the increase in function value and decrease in price, the overall product value increases. Stages of Value Engineering There are three main stages to value engineering, which are: Benefits of Value Engineering Value engineering helps an organization in numerous ways: Value engineering concepts apply to business as well as technical situations and consequently lead management to informed, result-oriented decisions. Value engineering has to be treated as a future investment for gaining technology leadership in the industry.
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What is Mesh and what are the types of Meshing
Table of content Types of Meshing Types of Meshing as per Grid Structure For those acquainted with mechanical design and reverse engineering, they can testify to the fact that the road to a new product design involves several steps. In reverse engineering, the summary of the entire process involves scanning, point cloud generation, meshing, computer-aided designing, prototyping and final production. This section covers a very crucial part of the process — Meshing or simply put, Mesh. To put a simple definition, a mesh is a network that constitutes of cells and points. Mesh generation is the practice of converting the given set of points into a consistent polygonal model that generates vertices, edges and faces that only meet at shared edges. It can have almost any shape in any size. Each cell of the mesh represents an individual solution, which when combined, results in a solution for the entire mesh. Mesh is formed of facets which are connected to each other topologically. The topology is created using following entities: These include: Types of Meshing Meshes are commonly classified into two divisions, Surface mesh and Solid mesh. Let us go through each section one by one. Surface MeshA surface mesh is a representation of each individual surface constituting a volume mesh. It consists of faces (triangles) and vertices. Depending on the pre-processing software package, feature curves may be included as well. Generally, a surface mesh should not have free edges and the edges should not be shared by two triangles. The surface should ideally contain the following qualities of triangle faces: The surface mesh generation process should be considered carefully. It has a direct influence on the quality of the resulting volume mesh and the effort it takes to get to this step. Solid Mesh Solid mesh, also known as volume mesh, is a polygonal representation of the interior volume of an object. There are three different types of meshing models that can be used to generate a volume mesh from a well prepared surface mesh. The three types of meshing models are as follows: Once the volume mesh has been built, it can be checked for errors and exported to other packages if desired. Types of Meshing as per Grid Structure A grid is a cuboid that covers entire mesh under consideration. Grid mainly helps in fast neighbor manipulation for a seed point. Meshes can be classified into two divisions from the grid perspective, namely Structured and Unstructured mesh. Let us have a look at each of these types. Structured Mesh Structured meshes are meshes which exhibits a well-known pattern in which the cells are arranged. As the cells are in a particular order, the topology of such mesh is regular. Such meshes enable easy identification of neighboring cells and points, because of their formation and structure. Structured meshes are applied over rectangular, elliptical, spherical coordinate systems, thus forming a regular grid. Structured meshes are often used in CFD. Unstructured Mesh Unstructured meshes, as the name suggests, are more general and can randomly form any geometry shape. Unlike structured meshes, the connectivity pattern is not fixed hence unstructured meshes do not follow a uniform pattern. However, unstructured meshes are more flexible. Unstructured meshes are generally used in complex mechanical engineering projects. Get access to our mesh tools library today Mesh Tools library offers a comprehensive set of operation for meshes for all your needs. Developed in C++, this library can be easily integrated in to your product. To learn more,
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Point Cloud Operations
No output is always perfect no matter how much the technology has evolved. Even though point cloud generation has eased up manufacturing process, it comes with its own anomaly. Generally, a point cloud data is accompanied by Noises and Outliers. Noises or Noisy data means the data information is contaminated by unwanted information; such unwanted information contributes to the impurity of the data while the underlying information still dominates. A noisy point cloud data can be filtered and the noise can be absolutely discarded to produce a much refined result. If we carefully examine the image below, it illustrates a point cloud data with noises. The surface area is usually filled with extra features which can be eliminated. After carrying out Noise Reduction process, the image below illustrates the outcome, which a lot smoother data without any unwanted elements. There are many algorithms and processes for noise reduction. Outlier, on the contrary, is a type of data which is not totally meaningless, but might turn out to be of interest. Outlier is a data value that differs considerably from the main set of data. It is mostly different from the existing group. Unlike noises, outliers are not removed outright but rather, it is put under analysis sometimes. The images below clearly portray what outliers are and how the point cloud data looks like once the outliers are removed. Point Cloud Decimation We have learned how a point cloud data obtained comes with noise and outliers and the methods to reduce them to make the data more executable for meshing. Point cloud data undergoes several operations to treat the anomalies existing within. Two of the commonly used operations are Point Cloud Decimation and Point Cloud Registration. A point cloud data consists of millions of small points, sometimes even more than what is necessary. Decimation is the process of discarding points from the data to improve performance and reduce usage of disk. Decimate point cloud command reduces the size of point clouds. The following example shows how a point cloud underwent decimation to reduce the excess points. Point Cloud Registration Scanning a commodity is not a one step process. A lot of time, scanning needs to be done separately from different angles to get views. Each of the acquired data view is called a dataset. Every dataset obtained from different views needs to be aligned together into a single point cloud data model, so that subsequent processing steps can be applied. The process of aligning various 3D point cloud data views into a complete point cloud model is known as registration. The purpose is to find the relative positions and orientations of the separately acquired views, such that the intersecting regions between them overlap perfectly. Take a look at the example given below. The car door data sets have been merged to get a complete model.
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Mesh Generation Algorithms
Table of content FAQs Algorithm methods for Quadrilateral or Hexahedral Mesh Algorithm methods for Triangular and Tetrahedral Mesh Mesh is the various aspects upon which a mesh can be classified. Mesh generation requires expertise in the areas of meshing algorithms, geometric design, computational geometry, computational physics, numerical analysis, scientific visualization, and software engineering to create a mesh tool. FAQs Over the years, mesh generation technology has evolved shoulder to shoulder with increasing hardware capability. Even with fully automatic mesh generators, there are many cases where the solution time is less than the meshing time. Meshing can be used for a wide array of applications; however, the principal application of interest is the finite element method. Surface domains are divided into triangular or quadrilateral elements, while volume domain is divided mainly into tetrahedral or hexahedral elements. A meshing algorithm can ideally define the shape and distribution of the elements. A vital step of the finite element method for numerical computation is mesh generation algorithms. A given domain is to be partitioned into simpler ‘elements.’ There should be a few elements, but some domain portions may need small elements to make the computation more accurate. All elements should be ‘well-shaped.’ Let us walk through different meshing algorithms based on two common domains: quadrilateral/hexahedral mesh and triangle/tetrahedral mesh. Algorithm methods for Quadrilateral or Hexahedral Mesh Grid-Based MethodThe grid-based method involves the following steps: Medial Axis MethodThe medial axis method involves an initial decomposition of the volumes. The technique involves a few steps as given below: Plastering methodPlastering is the process in which elements are placed, starting with the boundaries and advancing towards the center of the volume. The steps of this method are as follows: Whisker Weaving MethodWhisker weaving is based on the spatial twist continuum (STC) concept. The STC is the dual of the hexahedral mesh, represented by an arrangement of intersecting surfaces that bisects hexahedral elements in each direction. The whisker weaving algorithm can be explained in the following steps: Paving MethodThe paving method has the following steps to generate a quadrilateral mesh: Mapping Mesh MethodThe Mapped method for quad mesh generation involves the following steps: Algorithm methods for Triangular and Tetrahedral MeshQuadtree Mesh MethodThe quadtree mesh method recursively subdivided a square containing the geometric model until the desired resolution is reached. The steps for two-dimensional quadtree decomposition of a model are as follows: Delaunay Triangulation MethodA Delaunay triangulation for a set P of discrete points in the plane is a triangulation DT such that no points in P are inside the circum-circle of any triangles in DT. The steps of construction Delaunay triangulation are as follows: Delaunay Triangulation maximizes the minimum angle of all the triangle angles and tends to avoid skinny triangles. Advancing Front MethodAnother famous family of triangular and tetrahedral mesh generation algorithms is the advancing front or moving front method. The mesh generation process is explained in the following steps: Spatial Decomposition MethodThe steps for the spatial decomposition method are as follows: Sphere Packing MethodThe sphere packing method follows the given steps: Get access to our mesh tools library today Mesh Tools library offers a comprehensive set of operation for meshes for all your needs. Developed in C++, this library can be easily integrated in to your product. To learn more,
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