Additive Manufacturing the rise of metals in 3D printing

Additive manufacturing is one of the advanced techniques of Industry 4.0 that can manufacture industrial products faster and more precisely as compared to traditional manufacturing processes. Also known as 3D printing, it is a technique that works by turning a digital model of an object into a three-dimensional physical item by adding printable materials layer by layer on its digital design. It helps create complex geometrical patterns that are not possible with traditional manufacturing methods, designing and making lighter components, and controlling various material properties such as density and stiffness. 3D printing has gained popularity rapidly, involving minor prototype construction, fewer dies, and less post-processing. The aerospace and defense industry is experiencing large-scale use of 3D printing with French company Thales Group started a global center of expertise in additive manufacturing in Morocco in 2017. Boeing created its first 3D printed metal satellite antenna for the Israeli company Spacecom in 2019. Airbus used the technology to manufacture the titanium 3D printed bracket on an in series production A350 XWB commercial aircraft in 2017 and has since announced plans to develop 3D printed drones.
Read More

Additive Manufacturing: The past and the prominence of 3D Printing

Manufacturing and construction have witnessed significant reforms in a fast-changing world. Newer processes, machines are coming up with more unique means of operation, management, and increased efficiency. Remember, time is a valuable asset in today’s world.

Additive manufacturing (AM), also known as 3D printing, is a computer-operated approach to construction and industrial production.

Additive manufacturing is a computer-operated and controlled system that creates three-dimensional objects by carefully sequentially depositing various material compositions in layers.
A comprehensive digital layout is fed as design data, and the machine operates accordingly. Additive manufacturing is mainly used for making rapid prototypes and forging complex geometric objects.
The other names for Additive Manufacturing are 3D printing, Additive Layer Manufacturing.

Working Principle

Conventional methods employ lengthy processes which are time-consuming and prone to errors. Traditional methods of creating an object include material removal through machining, milling, carving, shaping, etc.

Additive manufacturing brings in more pro-manufacturing method that differs significantly from subtractive, conventional manufacturing methods.

For example, while the conventional method involves milling a work object from a solid block, additive manufacturing forges the part layer by layer from fine powders fed as materials. Things such as various metals, polymers, and composite materials can be used for 3D printing. The operational directives are provided by computer-aided design (CAD) data or 3D scanners that drive the machine in precise geometric patterns to deposit materials layer by layer.

The primary constituents of additive manufacturing technology are:

  • Computer
  • Computer-Aided Design or CAD software
  • Machine equipment
  • Layering material

Once the CAD data is lodged in, the computer guides AM machine to read the CAD data and lay down layer upon layer of various materials, usually in powdered & liquid form, to create a 3D object as intended.

In simple terms, additive manufacturing works like an “aircraft on autopilot.”

Commercialization of 3D printers

Additive manufacturing is not an archaic process, but rather, it came up in the ’80s. Here is a point-by-point history of AM in chronological order:

The 80’s:

The first commercial use of additive manufacturing with stereolithography from 3D Systems. The SLA-1 was the first commercially released AM machine. Ciba-Geigy partnered with 3D Systems for SL material development and commercialized acrylate resins. DuPont’s Somos stereolithography machine also entered the market in the same year. Japan’s NTT Data CMET and Sony/D-MEC commercialize stereolithography.

The 90’s:

Germany’s Electro-Optical Systems sells the first stereolithography system. Quadrax introduces Nark 1000 SL system. Three AM technologies, fused deposition modeling (FDM) from Stratasys, solid ground curing (SGC) from Cubital, and laminated object manufacturing (LOM) from Helisys, were commercialized. Selective laser sintering (SLS) and Soliform stereolithography system from Teijin Seiki were commercialized. Soligen commercialized direct shell production casting (DSPC), which used an inkjet mechanism. This year saw a bunch of new additives manufacturing systems. ModelMaker from Solidscape, Solid Center from Kira Corp., or EOSINT by EOS were examples. This year saw 3D Systems sell its first 3D printer called Actua 2100 that used an inkjet printing mechanism that deposited wax materials layer by layer. AeroMet was founded as a subsidiary of MTS systems corp. The company developed a laser additive manufacturing (LAM) process that used high-power laser and titanium alloys. Optomec commercializes laser-engineered net shaping (LENS).

The early 2000’s:

This year saw the emergence of new technologies. Quadra by Object Geometries, Sanders Prototype (now Solidscape) by PatternMaster, and Z402C machine by Z Corp. (World’s first commercially available multi-color 3D printer). Generis GmbH from Germany introduced its extensive GS 1500 system. ProMetal installed its first RTS-300 machine in Europe. Stratasys sells its Dimension product for $29,900. Solidscape introduced the T66 product while Phenix Systems of France sold Phenix 900 system for the first time. Later on, Stratasys signs an agreement with Arcam to be the exclusive distributor in North America for electron beam melting (EBM) systems. Dimension 1200 BST, NanoTool, InVision DP, Accura 60 photopolymer, Formiga P 100 laser-sintering system, SEMplice LSM, V-Flash 3D printers, ZPrinter 450, A2 electron Beam melting machine were some of the groundbreaking AM machines introduced in the early 2000s.

The late 2000’s:

EuroMold, SLM Solutions present SLM 280 HL. CRP Technology announced Windform GF 2.0, while 3D Systems unveiled a smaller 3D printer, the ProJet 1000, for $10,900. In 2012, MakerBot released the MakerBot replicator. EasyClad from France introduced the MAGIC LF600 AM machine in 2012. Solidoodle from NY released Soldoodle 3D printer wild Belgium based Materialise introduced Magics 17. The late 2000’s So the growth of additive manufacturing and the 3D printing machine market. The AM or 3D printing Industry witnessed massive investment. In September 2013, Voxeljet announced its $100 million IPO plan. In March 2015, ExOne released Exerial, a large machine with multiple stations to enable continuous production. Early 3D printers were not very light and convenient to handle. It is only after the advent of the 21st century that they have become more affordable, straightforward, easy to operate, and versatile enough to be used in a wide range of operation ranging from tools & Page 4 of 1 component manufacture, electronics, metalwork, polymers, and product prototypes. Past three years, there has been a tendency to employ 3D printing and AM tech in the real estate industry.

We can see how fast Additive manufacturing emerged within just three decades and how it is relevant across multiple industrial verticals today. Whether it is about building prototypes, constructing affordable housing or producing components, AM and 3D printing have offered effective systems that triumph over traditional methods.
This technology enables faster product development and market entry, smoother product customization, and seamless integration at lesser cost and time. Thus, additive manufacturing provides OEM manufacturers an excellent opportunity to unleash their products at a higher rate at much lesser expenses for great returns and better customer benefits while ensuring sustainability.

Reference:

Wohlers, T. and Gornet, T., (2016). History of additive manufacturing, Wohlers Report 2016. Retrieved from https://docplayer.net/13470116-History-of-additive-manufacturing.html

Read More

Design Analysis - FEA, CFD, and Mold Flow Analysis

Over the years, the term “Design Analysis” has found a significant place for itself in the manufacturing sector. Instead of making a prototype and creating elaborate testing regimens to analyze the physical behavior of a product, engineers can evoke this information quickly and accurately on the computer.

Design analysis is a specialized computer software technology designed to simulate the physical behavior of an object.

If an object will break or deform or how it may react to heat are the sort of queries design analysis can answer. Design analysis helps in minimizing or even eliminate the need to build a physical prototype for testing. As a result, the technology has gone mainstream as a prized product development tool and found its presence in almost all sectors of engineering.

This article discusses three major design analysis software, namely:

  • Finite Element Analysis (FEA)
  • Computational Fluid Dynamics (CFD)
  • Mold Flow Analysis
Finite Element Analysis (FEA)

The Finite Element Analysis (FEA) is a specialized simulation of a physical entity using the numerical algorithm known as Finite Element Method (FEM). It is used to reduce the number of physical prototypes and experiments and analyze objects in their design stage to develop better products faster. The term ‘finite’ is used to denote the limited, or finite, number of degrees of freedom used to model the behavior of each element.

FEA will analyze an object in question by breaking down its entire geometry into small ‘elements,’ which are put under simulated conditions see how the elements react. It displays the results as color-coded 3D images where red denotes an area of failure, and blue indicates fields that maintain their integrity under the load applied. However, note it down that FEA gives an approximate solution to the problem.

Mathematics is used to understand and quantify a physical phenomena such as structural or fluid behavior, wave propagation, thermal transport, the growth of biological cells, etc. Most of these processes are described using Partial Differential Equations. Finite Element Analysis has proven to be on of the most prominent numerical technique for a computer to solve these PEDs.

FEA is used in:

Problems where analytical solution is not easily obtained,

And mathematical expressions required because of complex geometries, loadings and material properties.

Computational Fluid Dynamics (CFD)

Computational Fluid Dynamics (CFD) is a specilaized simulation used for the analysis of fluid flows through an object using numerical solution methods. CFD incorporates applied mathematics, physics and computing software to evaluate how a gas or liquid flows and how it affects an object as it flows past. CFD is based on Navier-Stokes equations which describe the way velocity, temperature, pressure, and density of a moving fluid are related.

Aerodynamics and hydrodynamics are two engineering streams where CFD analyses are often used. Physical quantities such as lift and drag or field properties as pressures and velocities are computed using CFD. Fluid dynamics is connected with physical laws in the form of partial differential equations. Engineers transform these laws into algebraical equations and can efficiently solve these equations numerically.The CFD analysis reliability depends on the whole structure of the process. The determination of proper numerical methods to develop a pathway through the solution is highly important. The software, which conducts the analysis is one of the key elements in generating a sustainable product development process, as the amount of physical prototypes can be reduced drastically.

CFD is used in almost all industrial domains, such as:

  • Food processing
  • Water treatment
  • Marine engineering
  • Automotive
  • Aerodynamics
  • Aerospace

With the help of CFD, fluid flow can be analyzed faster in more detail at an earlier stage, than by tesing, at a lower cost and lower risk. CFD solves the fundamental equations governing fluid flow processes, and provides information on important flow characteristics such as pressure loss, flow distribution, and mixing rates.

CFD has become an integral part of engineering and design domains of prominent companies due to its ability to predict performance of new designs and it intends to remain so.

Mold Flow Analysis

Moldflow, formerly known as C-mould, is one of the leading software used in processwide plastics solutions. Mold flow computes the injection molding process where plastic flows into a mold and analyzes the given mold design to check how the parts react to injection and ensure that the mold will be able to produce the strongest and uniform pieces. Two of the most popular mold flow analysis software are Moldflow and Moldex3D used exclusively by many mold makers.

There are three types of Mold flow analysis which are as follows:

  • Moldflow Filling Analysis (MFA): It facilitates visualization of shear rate and shear stress plus determination of fiber orientation and venting. MFA can predict fill pattern and injection pressure while optimizing gating and runner system.
  • Moldflow Cooling Analysis (MCA): MCA specializes in finding hot spots and calculating time to freeze. It helps in determining uneven cooling between core and cavity while specifying required cooling flow rates.
  • Moldflow Warpage Analysis (MWA): Moldflow warpage is all about predicting, finding and determining warpage due to orientation.

We can see benefits of using different analysis procedures that correctly understand the power of the different simulation tools. During the product design, many these methods affect the cost and quality of the product, thereby ensuring the optimum productivity as aimed by the manufacturer.

 

Read More

Future of Reverse Engineering

Reverse engineering found its use in various industries gradually, as more and more industry leaders adopted this approach and implemented the same, thereby easing out their own work-process. Here is a list of industries that use reverse engineering as a part of their methods:

  • Manufacturing/Heavy machine
  • Automotive
  • Software development
  • Military projects
  • Space expeditions
  • Aerospace
  • Architecture
  • Oil & gas
The future

It is the 21st century. These are great times for design engineers. Over the past two decades, their job has been dramatically changed, with the transformation of finite element analysis (FEA) software from mainframe to desktop computer. With the easy availability of computer-aided design software packages, reverse engineering technology has become a practical means to create a 3D virtual model of an existing physical part. That, in turn, has made the use of 3D CAD, CAM, or other CAE applications easier.

The convenience in the usage, affordability and the ability of its software to tightly integrate with a CAD program has made this process a much favored among engineers. At the same time, the costs of scanners and other hardware used to input measurements have been dropping, and the hardware is becoming smaller and easier to use, according to the hardware makers.

Read More

Geometric Dimensioning and Tolerancing (GD&T)

The design model is a depiction of a part design. However, the design model can never be an accurate representation of the product itself. Due to shortcomings in manufacturing and inspection processes, physical parts never match the design model exactly. An essential aspect of a design is to specify the lengths the part features may deviate from their theoretically accurate geometry. It is vital that the design intent and functionality of the part be communicated between the design engineers and the manufacturing unit. It is where the approach of GD&T comes into play.

Geometric dimensioning and tolerancing or GD&T is a language of symbols and standards used on engineering drawings and models to determine the allowable deviation of feature geometry. 

GD&T consists of dimensions, tolerances, definitions, symbols, and rules that enable the design engineers to convey the design models appropriately. The manufacturing unit uses the language to understand the design intent.

To master GD&T, one needs to understand the crucial concepts, which includes:

  • Machining tolerances: Tolerances mean the allowable amount of deviation from the proposed drawing. Machined parts look flat and straight through the naked eye, but if viewed with calipers, one can find imperfections all over. These imperfections or variations are allowed within the tolerance constraints placed on the parts. Tolerances should be kept as large while preserving the functions of the part.
  • The Datum Reference Frame: DRF is the most important aspect of GD&T. It is a three-dimensional cartesian coordinate system. It’s a skeletal reference to which all referenced geometric specifications are related.
  • GD&T Symbols: It is essential to be familiar with numerous symbols and types of applied tolerance in GD&T. The language of symbols makes it easier to interpret designs and improve communications from the designer to the shop. By using GD&T standard, the design intent is fully understood by suppliers all over the world.

  • Feature Control Frame: The feature control frame describes the requirements or instructions for the feature to which it is attached. A feature control frame contains only one message. If a feature needs two messages, the feature would need the corresponding amount of feature control frames for every message required.
  • Basic Dimensions: Basic dimensions are exact numerical values in theory, which defines the size, orientation, form, or location of a part or feature. 
  • Material Condition Modifiers: It is often necessary to state that a tolerance applies to a feature at a particular feature size. The Maximum Material Condition (MMC) allows an engineer to communicate that intent.

GD&T is an efficient way to describe the dimensions and tolerances compared to traditional approximation tolerancing. The engineer might design a part with perfect geometry in CAD, but the produced part, more often than not, turns out to be not accurate. Proper use of GD&T improves quality and reduce time and cost of delivery by providing a common language for expressing design intent.

 

Read More

Mesh - List of operations

Good cell quality of meshes translate into accurate results within optimum time after computation. But more often than not, we get a mesh output, which is far from accuracy. There are number of factors affecting a mesh, that might compromise with the final result. This chapter focuses on the various shortcomings of a mesh and their repair algorithms.

Mesh Decimation/Simplification

Mesh decimation/simplification is the method of reducing the number of elements used in a mesh while maintaining the overall shape, volume and boundaries preserved as much as possible. It is a type of algorithm that aims to transform a given mesh into another with fewer elements (faces, edges and vertices). The decimation process usually involves a set of user-defined quality criteria, that maintains specific properties of the original mesh as much as possible. This process reduces the complexity of a mesh.

Before Mesh Decimation

 

After Mesh Decimation

 

Mesh Hole-Filling

To analyze a mesh model, it must be complete. Often, some mesh models carry holes in them, which must be filled. The unseen areas of the model appear as holes, which are aesthetically unsatisfying and can be a hindrance to algorithms that expect a continuos mesh. The Fill Hole command fills the holes and gaps in the mesh.

Note – The Fill Hole command only works on triangulated mesh and not tetrahedral mesh

Mesh Before Hole Filling

 

Mesh After Hole Filling

 

Mesh Refinement

Certain situations arise which makes us concerned about the accuracy a model in certain areas. Such scenarios prompt us to have fine mesh in those areas to ensure accurate results. However, creating a surface mesh of the entire model with a fine mesh size may ask for unnecessary hours to analyze the fine mesh in those regions where the results are not as important to you. The answer to this issue is the usage of refinement points.

A refinement point identifies a region or volume of space in which a finer mesh has to be generated. Mesh refinement can be defined by identifying an absolute size for the local mesh. Mesh refinement ends up in creating more number of elements in the specified region of the model.

Before Mesh Refinement

 

After Mesh Refinement

 

Mesh Smoothing

Mesh smoothing is also known as mesh relaxation. Sometimes it is necessary to modify that mesh after a mesh generation. It is achieved either by changing the positions of the nodes or by removing the mesh altogether. Mesh smoothing results in the modification of mesh point positions, while the topology remains as it is.

Before Mesh Smoothing

 

After Mesh Smoothing

Read More

Mesh Generation Algorithms

In the previous session, we have learned what Mesh is and 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.

Over the years, mesh generation technology has evolved shoulder to shoulder with increasing hardware capability. Even with the fully automatic mesh generators there are many cases where the solution time is less than the meshing time. Meshing can be used for 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 key step of the finite element method for numerical computation is mesh generation algorithms. A given domain is to be partitioned it into simpler ‘elements’. There should be few elements, but some portions of the domain may need small elements so that the computation is more accurate there. All elements should be ‘well shaped’. Let us take a walkthrough of different meshing algorithms based of two common domains, namely quadrilateral/hexahedral mesh and triangle/tetrahedral mesh.

Algorithm methods for Quadrilateral or Hexahedral Mesh

Grid-Based Method

The grid based method involves the following steps:

  • A user defined grid is fitted on 2D & 3D object. It generates quad/ hex elements on the interior of the object.
  • Some patterns are defined for boundary elements followed by forming a boundary element by applying boundary intersection grid.
  • This results in the generation of quadrilateral mesh model.

Mesh Grid based method

 

Medial Axis Method

Medial axis method involves an initial decomposition of the volumes. The method involves few steps as given below:

  • Consider a 2D object with hole.
  • A maximal circle is rolled through the model and the centre of circle traces the medial object.
  • Medial object is used as a tool for automatically decomposing the model in to simple meshable region.
  • Series of templates for the region are formed by the medial axis method to fill the area with quad element.

Mesh Medial axis method

 

Plastering method

Plastering is the process in which elements are placed starting with the boundaries and advancing towards the centre of the volume. The steps of this method are as follows:

  • A 3D object is taken.
  • One hexahedral element is placed at boundary.
  • Individual hexahedral elements are projected towards the interior of the volume to form hexahedral meshing, row by row and element by element.
  • The process is repeated until mesh generation is completed.

Mesh Plastering method

 

Whisker Weaving Method

Whisker weaving is based on the concept of the spatial twist continuum (STC). The STC is the dual of the hexahedral mesh, represented by an arrangement of intersecting surfaces, which bisect hexahedral elements in each direction. The whisker weaving algorithm can be explained as in the following steps:

  • The first step is to construct the STC or dual of the hex mesh.
  • With a complete STC, the hex elements can then be fitted into the volume using the STC as a guide. The loops can be easily determined from an initial quad mesh of the surface.
  • Hexes are then formed inside the volume, once a valid topological representation of the twist planes is achieved. One hex is formed wherever three twist planes converge.

Mesh Whisker weaving method

 

Paving Method

The paving method has the following steps to generate a quadrilateral mesh:

  • Initially a 2D object is taken.
  • A node is inserted in the boundary and the boundary node is considered as loop.
  • A quadrilateral element is inserted and a row of elements is formed.
  • The row of element is placed around the boundary nodes.
  • Again this same procedure adopt for next rows.
  • Finally quad mesh model is formed.

Mesh Paving method

Mesh Paving method

 

Mapping Mesh Method

The Mapped method for quad mesh generation involves the following steps:

  • A 2D object is taken.
  • The 2D object is split into two parts.
  • Each part is either a simple 2D rectangular or a square object.
  • The simple shape object is unit meshed.
  • The unit meshed simple shape object is mapped in its original form and then joined back to form actual object.

Mapping mesh method

Mapping mesh method

 

Algorithm methods for Triangular and Tetrahedral Mesh

Quadtree Mesh Method

With the quadtree mesh method, square containing the geometric model are recursively subdivided until the desired resolution is reached. The steps for two dimensional quadtree decomposition of a model are as follows:

  • A 2D object is taken.
  • The 2D object is divided into rectangular parts.
  • A Detail tree of divided object is provided.
  • The object is eventually converted into triangle mesh.

 Quadtree mesh method

 

Delaunay Triangulation Method

A 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:

  • The first step is to consider some coordinate points or nodes in space.
  • The condition of valid or invalid triangle is tested in every three points which finds some valid triangle to make a triangular element.
  • Finally a triangular mesh model is obtained.

Delaunay Triangulation maximizes the minimum angle of all the angle of triangle and it tends to avoid skinny triangles.

Mesh Delaunay Triangulation method

Mesh Delaunay Triangulation method

 

Advancing Front Method

Another very popular family of triangular and tetrahedral mesh generation algorithms is the advancing front method, or moving front method. The mesh generation process is explained as following steps:

  • A 2D object with a hole is taken.
  • An inner and outer boundary node is inserted. The node spacing is determined by the user.
  • An edge is inserted to connect the nodes.
  • To start the meshing process, an edge AB is selected and a perpendicular is drawn from the midpoint of AB to point C (where C is node spacing determined by the user) in order to make a triangular element.
  • After one element is generated, another edge is selected as AB and a point C is made, but if in case any other node lets point D within the defined radius, then ABC element is cancelled and instead, an element ABD is formed.
  • This process is repeated until mesh is generated.

Mesh Advancing Front method

 

Spatial Decomposition Method

The steps for spatial decomposition method are as follows:

  • Initially a 2D object is taken.
  • The 2D object is divided into minute parts till we get the refined triangular mesh.

Mesh Spatial Decomposition method

 

Sphere Packing Method

The sphere packing method follows the given steps:

  • Before constructing a mesh, the domain is filled with circles.
  • The circles are packed closely together, so that the gaps between them are surrounded by three or four tangent circles.
  • These circles are then used as a framework to construct the mesh, by placing mesh vertices at circle centers, points of tangency, and within each gap while using generated points. Eventually, the triangular mesh is generated.

Mesh Sphere Packing method

Mesh Sphere Packing method

 

 

 

 Source

Singh, Dr. Lokesh, (2015). A Review on Mesh Generation Algorithms. Retrieved from http://www.ijrame.com

Read More

Mesh Quality

The quality of a mesh plays a significant role in the accuracy and stability of the numerical computation. Regardless of the type of mesh used in your domain, checking the quality of your mesh is a must. The ‘good meshes’ are the ones that produce results with fairly acceptable level of accuracy, considering that all other inputs to the model are accurate. While evaluating whether the quality of the mesh is sufficient for the problem under modeling, it is important to consider attributes such as mesh element distribution, cell shape, smoothness, and flow-field dependency.

Element Distribution

It is known that meshes are made of elements (vertices, edges and faces). The extent, to which the noticeable features such as shear layers, separated regions, shock waves, boundary layers, and mixing zones are resolved, relies on the density and distribution of mesh elements. In certain cases, critical regions with poor resolution can dramatically affect results. For example, the prediction of separation due to an adverse pressure gradient depends heavily on the resolution of the boundary layer upstream of the point of separation.

Cell Quality

The quality of a cell has a crucial impact on the accuracy of the entire mesh. The quality of cell is analyzed by the virtue of three aspects: Orthogonal quality, Aspect ratio and Skewness.

Orthogonal Quality: An important indicator of mesh quality is an entity referred to as the orthogonal quality. The worst cells will have an orthogonal quality close to 0 and the best cells will have an orthogonal quality closer to 1.

Aspect Ratio: Aspect ratio is an important indicator of mesh quality. It is a measure of stretching of the cell. It is computed as the ratio of the maximum value to the minimum value of any of the following distances: the normal distances between the cell centroid and face centroids and the distances between the cell centroid and nodes.

Skewness: Skewness can be defined as the difference between the shape of the cell and the shape of an equilateral cell of equivalent volume. Highly skewed cells can decrease accuracy and destabilize the solution.

Smoothness

Smoothness redirects to truncation error which is the difference between the partial derivatives in the equations and their discrete approximations. Rapid changes in cell volume between adjacent cells results in larger truncation errors. Smoothness can be improved by refining the mesh based on the change in cell volume or the gradient of cell volume.

Flow-Field Dependency

The entire effects of resolution, smoothness, and cell shape on the accuracy and stability of the solution process is dependent upon the flow field being simulated. For example, skewed cells can be acceptable in benign flow regions, but they can be very damaging in regions with strong flow gradients.

Correct Mesh Size

Mesh size stands out as one of the most common problems to an equation. The bigger elements yield bad results. On the other hand, smaller elements make computing so long that it takes a long amount of time to get any result. One might never really know where exactly is the mesh size is on the scale.

It is important to consider chosen analysis for different mesh sizes. As smaller mesh means a significant amount of computing time, it is important to strike a balance between computing time and accuracy. Too coarse mesh leads to erroneous results. In places where big deformations/stresses/instabilities take place, reducing element sizes allow for greatly increased accuracy without great expense in computing time.

Read More

Path to Product Development

If you are an engineering professional, most likely you are aware of how a physical product comes to life. From the early days of sketching and blueprints, manufacturing of a commodity has come a long way. The modern methodology of creating a product has not only changed drastically, but it has become way more efficient and precise in its approach. Today’s engineer lives and thrives in the world of 3-dimensional models. Whatever masterpiece a designer has in his mind, he has the tools and system to give it life. And it is not just limited to inception of a new idea being turned to a product; it has made the art of reverse engineering being implemented more than ever.

So what are the factors that have revolutionized this craft?

It is the safe to say that with the invention of new tools, techniques and computer, the road to new product development has become more smooth, accurate and flexible. Although a professional can get deep into the subject matter, this article gives a brief overview of the product development from technical perspective.

The footsteps to a new product can be summarized in the following sequence.

 

path to product developmentTo put it in words, here is how the entire sequence goes:

  • Scanning: Whether you have an entirely new idea on your mind, or you want to base your idea on an already existing product; you need a reference. Your reference can be either technical manuals from the manufacturer or the physical product itself. The first step is to scan the product using 3D scanners. 3D scanning technology comes in many shapes and forms. Scanners capture and store the 3D information of the product. The scanned information gets stored in the form of closely spaced data points known as Point Cloud.
  • Point Cloud: A point cloud is a collection of data points defined by a given coordinates system. In a 3D coordinates system, for example, a point cloud may define the shape of some real or created physical system.
  • Mesh: Point clouds are used to create 3D meshes. A mesh is a network that constitutes of cells and points. Mesh generation involves point clouds to be connected to each other by the virtue of vertices, edges and faces that meet at shared edges. There are specific softwares for carrying of meshing function.
  • 3D Model: Once the meshed part is generated, it goes through required software applications to be transferred to Computer Aided Design (CAD) tools to get transformed into a proper 3D CAD model. 3D model is the stage where whole sorts of applications such as sewing, stitching, etc, are implemented to create a prototype.
  • Testing: A prototype goes through numerous tests in this phase, to check for limitations and possible calibrations if necessary. This is done to determine the optimum stage where the prototype can be turned to a product.
  • Product: This is where the entire process comes to an end. Once a prototype is evaluated and finalized, it is sent for production in order to introduce it to the market.

 This introductory part gives you a summary of product development and the related technical terms. In the next chapters, we will dive deep and go through all the mentioned stages, one by one.

Read More

Point Clouds | Point cloud formats and issues

Whether working on a renovation project or making an information data about an as-built situation, it is understandable that the amount of time and energy spent on analysis of the object/project in hand can be quite debilitating. Technical literatures over the years, has come up with several methods to make a precise approach. But inarguably, the most prominent method is the application of Point Clouds.

3D scanners gather point measurements from real-world objects or photos for a point cloud that can be translated to a 3D mesh or CAD model.

But what is a Point Cloud?

A common definition of point clouds would be — A point cloud is a collection of data points defined by a given coordinates system. In a 3D coordinates system, for example, a point cloud may define the shape of some real or created physical system.

Point clouds are used to create 3D meshes and other models used in 3D modeling for various fields including medical imaging, architecture, 3D printing, manufacturing, 3D gaming and various virtual reality (VR) applications. A point is identified by three coordinates that, correlate to a precise point in space relative to a point of origin, when taken together.
Point CloudThere are numerous ways of scanning an object or an area, with the help of laser scanners which vary based on project requirement. However, to give a generic overview of point cloud generation process, let us go through the following steps:

  1. The generation of a point cloud, and thus the visualization of the data points, is an essential step in the creation of a 3D scan. Hence, 3D laser scanners are the tools for the task. While taking a scan, the laser scanner records a huge number of data points returned from the surfaces in the area being scanned.
  1. Import the point cloud that the scanner creates into the point cloud modeling software. The software enables visualizing and modeling point cloud, which transforms it into a pixelated, digital version of the project. 
  1. Export the point cloud from the software and import it into the CAD/BIM system, where the data points can converted to 3D objects.
Different 3D point cloud file formats

Scanning a space or an object and bringing it into designated software lets us to further manipulate the scans, stitch them together which can be exported to be converted into a 3D model. Now there are numerous file formats for 3D modeling. Different scanners yield raw data in different formats. One needs different processing software for such files and each & every software has its own exporting capabilities. Most software systems are designed to receive large number of file formats and have flexible export options. This section will walk you through some known and commonly used file formats. Securing the data in these common formats enables the usage of different software for processing without having to approach a third party converter.

Common point cloud file formats

OBJ: It is a simple data format that only represents 3D geometry, color and texture. And this format has been adopted by a wide range of 3D graphics applications. It is commonly ASCII (American Standard Code for Information Interchange).

PLY: The full form of PLY is the polygon file format. PLY was built to store 3D data. It uses lists of nominally flat polygons to represent objects. The aim is to store a greater number of physical elements. This makes the file format capable of representing transparency, color, texture, coordinates and data confidence values. It is found in ASCII and binary versions.

PTS, PTX & XYZ: These three formats are quite common and are compatible with most BIM software. It conveys data in lines of text. They can be easily converted and manipulated.

PCG, RCS & RCP: These three formats were developed by Autodesk to specifically meet the demands of their software suite. RCS and RCP are relatively newer.

E57: E57 is a compact and widely used vendor-neutral file format and it can also be used to store images and data produced by laser scanners and other 3D imaging systems.

Challenges with point cloud data

The laser scanning procedure has catapulted the technology of product design to new heights. 3D data capturing system has come a long way and we can see where it’s headed. As more and more professionals and end users are using new devices, the scanner market is rising in a quick pace. But along with a positive market change, handling and controlling the data available becomes a key issue.

Five key challenges professionals working with point cloud face are:

  • Data Format: New devices out there in the market yields back data in a new form. Often, one needs to bring together data in different formats from different devices against a compatible software tool. This presents a not-so-easy situation
  • Data Size: With the advent of new devices, scanning has become cheaper with greater outputs. It is possible to scan huge assets from a single scan. This has resulted in the creation of tens of thousands of data points. A huge data of points can be challenging to handle and share between project partners.
  • Inter-operability: Integration between new technologies with the existing software can be quite arduous. Although, with careful investment of time and money, the goal can be achieved nonetheless.
  • Access: All the professionals involved in the entire lifecycle of a product can benefit from having access to point cloud data. But multiple datasets in multiple formats usually makes it more of a hassle.
  • Ownership: Who owns point cloud data? In the past, EPCs and the contractors who capture the data become custodians of the information.
  • Rendering: Different formats can result in rendering problems for point clouds.
Read More

Page 1 of 3