Enhance VR with In-process Model for Advance Personalized Learning of CNC programming and OperationMr. Liu Peiling, Principal Research EngineerDr. Liu Kui, Senior Research EngineerMr. Wu Hu, Research EngineerMr. Shaw Kah Chuan, Senior Research Officer

Singapore Institute of Manufacturing Technology71 Nanyang Drive Singapore 638075Tel: 65-67938356 Mobile: 65-90123598 Fax: 65-67916377plliu@simtech.a-star.edu.sg http://simtech.a-star.edu.sg

Keywords: Modeling & Simulation, In-process Model, CNC Machining, Virtual Training

ABSTRACT

Enhance Virtual Reality (VR) for advance personalized learning has been listed as the grand engineering challenge [1]. However, current VR model is not deformable to describe the shape change of manufacturing processes, such as subtractive machining or additive layer manufacturing (LM). Further more, current VR model is not precise enough to simulate the measurement of workpiece, which may go to submicron level. This paper reviewed the current industrial needs of virtual computer numerical control (CNC) training, listed the critical technology issues, traced the 20 years evolution of in-process models of CNC machining, and proposed a new solution. Based on the proposed in-process model, a virtual CNC training system has been developed and used in training courses. Comparisons with conventional on-site manual training and VR based e-learning concluded this new approach could greatly improve safety, increase learning efficiency, and save machine and material.

NOMENCLATUREB-Rep: Boundary RepresentationCNC: Computer Numerical ControlHSM: High Speed MachiningCSG: Constructive Solid GeometryIPM: In-process modelLM: Layered manufacturingMM: Multiple machiningM&S: Modeling and simulation

1. Industrial requirements for virtual training

As the cutting edge of industry, CNC machining produces essential inputs for virtually all types of manufacturing products by providing injection mould, sheet metal die, casting die, jigs and fixtures, and other special

tools. After analyzing the whole design and manufacturing procedures, it was found that:

So called high tech revolution of precision engineering, represented by pervasive use of computer such as CNC control, CAM, HSM, ultra machining, not only reduce the dependence of precision engineering on unskilled workers (e.g. manual polisher), but also create a pool of demand on skilled workers (e.g. CNC machinists), especially those who can operate machining knowledge intensive HSM and ultra precision machining.

In today's competitive world, not only the latest technologies are needed, but most importantly, highly-qualified personnel. This is especially true when it comes to working with CNC machines. Only when CNC machines have been perfectly mastered are high productivity and exceptional quality guaranteed. Skilled workers, especially the machinist who can operate High Speed and Ultra Precision Machine Tool, are playing a key role in current situation.

HSM requires the machinist to know not only how to operate the machine tool but also machining knowledge, in order to plan a successful cutting process. Lacking of skilled worker, especially skilled machinist who can do high speed and ultra precision machining, is a major problem for local industry. Skilled machinists are in high demand in Singapore and Asia, especially in China.

Presently, trainees acquire their operating skills by observing, referring the operation manual and then operating under the guidance of an experienced operator. To make training safer, more economical and more effective, there is an increasing desire to complete initial training away from the operating environment. The training of skilled machinists is still a slow and manual process, which need a lot of machine tools and fixtures etc. The machining job has a traditional image problem of black smith.

It is recognized that ITE schools, industrial training centers, public education facilities, machine tool manufacturers and dealers are having increasing-complexity of training requirement. They require not only training software but also more comprehensive turnkey solutions for CNC training system.

2. Current Status of Virtual CNC Training

Comparing with CNC simulation applications which are expensive and mature, Virtual CNC Training System is still primitive. The NC simulator developers are not very active to provide training system because the training software market is logically smaller than production software. More important, NC simulator developers need to revamp graphics engine or geometry kernel to suit education game use. None of the leading NC simulators has any CNC training capability. This leaves the development of Virtual CNC Training System to machine tool venders and schools who do not have expertise to develop a good graphics engine.

The CNC control vendors developed their own training system. For example, Siemens developed SinuTrain, which is CNC training software. It runs on PC and suitable for training purposes and self-study as it is for writing programs and simulation. It serves for writing and simulating NC programs on a PC, based on the DIN 66025 programming language as well

as the products ShopMill, ShopTurn and ManualTurn+ and language commands for SINUMERIK® 810D, 840D and 840Di controls, all are Siemens products. Programs written with this software can be used on real machines. A prerequisite is that the SinuTrain software is adapted to the SINUMERIK control on which the program is to be executed. This adaptation must be carried out by specially qualified personnel, e.g. from Siemens. It is important to stick to Siemens and the machine-tool manufacturer’s instructions when adapting the software. No liability is accepted by Siemens if these requirements are not adhered.

We evaluated several vender specific Virtual CNC Training System. They have very good GUI which has been customized to vender’s CNC controller, some even have touch tablet that simulate operation panel. However, the cutting simulation is rough and primitive, despite the sound and chip flying animation.

The paper [2] discusses the possibility to use VRML for scientific, educational and even industrial purposes. As an illustration, it showed how VRML can be used as inexpensive means for simulation of one of the most interesting but also most time and resource consuming areas of the computer aided manufacturing (CAM) — machining of complex parts.

There are many research and publications on Virtual CNC Training in last 10 years. Most of the published graphics engines are based on VRML and Java 3D. They explored internet based CNC training and remote NC simulation etc, which are futuristic but not practical at this moment. The computer hardware is very cheap now that there is no need to run a training system over internet. The remote graphics over internet is not necessary [3-4]. Some of them use flash movies such as micro media to do animation, which could only be used to pre-fixed scene.

In VRML, the realization of dynamic material removal during a machining process remains a problem. Some commercial software such as Deneb’s virtual NC can export a VRML animation to describe a machining process. Nevertheless, during the cutting process, the geometry of a workpiece remains unchanged. The reason is that VRML does not support set operations among geometric objects such as union, intersection and difference. This makes it difficult to simulate the change in geometry of a workpiece under cutting.

In layman’s term, the current virtual CNC training systems are educational games that lacking the realistic feeling of machining, which is quite different from realistic simulators, such as the flying simulators that are used to train pilot.

The next generation virtual CNC training is to provide knowledge intensive CNC training, for the future skilled machinist of precision engineering (PE) industry through pervasive physics-geometrical modeling and simulation of multiple machining processes, especially high speed and ultra precision machining. To realize this vision, we need a new in-process model (IPM) that is deformable and precise.

3. In-process Model (IPM) Review

The in-process model represents the state of the product at each step in the machining process. It is a 3D geometrical construct that reflects the results of the machining operations. This model allows the user to visually verify that the machining operations have been defined accurately and that their

sequence is correct. It can be automatically re-generated when there are changes in the product design, machining parameters or sequence of the operations [5]. In this section, the geometric representation techniques of IPMs for traditional manufacturing simulation are presented.

Boundary Representation (B-rep)

The first choice of IPM should be naturally the geometry model used in commercial Computer Aided Deign (CAD) system, B-rep. The benefits of using the same geometry model for CAD as the IPM are obvious. The CAD geometry model is matured and available through CAD development kit, so there is little need to develop a new geometry model kernel. Sharing a common geometry model with CAD, the IPM facilitates seamless integration of CAD-CAPP-CAM.An automatic forging design and manufacture system was developed by the authors in 1986, in which pre-form forging IPMs were the same as the CAD system CV/MUDUSA running on VAX-11/750 computer [6-7]. However, the creation of pre-form forging IPMs took days of calculation and often failed due to Boolean operation failure.With a great deal of research effort in the last two decades, the B-rep geometry model has been improved significant in term of Boolean operation stability, but the B-rep based IPMs are still limited to 2.5-axis milling (Figure 1). Park reported a prismatic IPM generation method that employed a polygon extrusion algorithm to sweep a ball-nose cutter [8].

Figure 1: 2.5-axis IPMs

Section Representation

Since the integrated B-rep IPMs can not be created inside a CAD geometry model, a new, ad-hoc cross-section-wire-frame based approach was proposed in a forging die CAD/CAM (Computer Aided Manufacturing) system [6-7]. The aim was to use a series of paralleled cross-section drawing to represent 3D shapes. Figure 2b depicts the section representation of circled 3D shapes in Figure 2a.The cross section IPM is widely used in many commercial CAD/CAM systems. I-DEAS from SDRC uses water level cross-section as an IPM for generative machining. In a traditional NC programming environment, a significant amount of time is spent trying to visualize the in-process stock as it goes through various process stages. With I-DEAS, the wireframe section in-process stock model can be created for downstream applications such as toolpath generation, process planning, fixture designing, and clamp positioning.

(a)

(b)

Figure 2: Section representation of 3D shape

A part can be sectioned along the X, Y and Z axes (Figure 3). The Z-axis section is usually called water level section. For 3-axis milling, the water level section could have many loops, which causes complications in the set operation between sections. X and Y sections are single half loops and the Z value is unique for every points. Thus simplifying the set operation considerably.

Figure 3: Section representation

A working system for using IPM in pre-forging design is described in [6-7]. A drawing sheet with part sections is first created first using the BACIS command language of CV/MEDUSA CAD system. Since there are many sections in a drawing sheet, each section wire-frame is assigned to a different layer according to its Y distance, and a certain number of sections can be looped through layers. Then each cutter section is moved to its cutter location and compare with the part sections. The overlap between the cutter section and the part section will be removed from the part section. A real milling IPM is obtained from the collection of the result sections.The display of sections is provided by line segments and can be confusing when there are too many lines, i.e. there is a need to render the IPM as a realistic 3D image. In order to calculate the surface normal required for rendering, the section wire frame is divided along the X direction by the same step over of Y direction. A so-called regulated section is formed to

facilitate the calculation of surface normal and interpolation of points between the sections. A given node in one section is linked to a node in the next section. A node’s normal can be calculated from the four neighboring nodes. Figure 4 shows the regulated section representation.

Figure 4: Regulated section representation

The regulated section can also be used to accelerate set operation between cutter section and part section. Calculation of intersections and trimming between two sections are time consuming and the re-ordering of the line segments requires more computing time. This can be improved with the regulated sections, where the line segments are indexed by both cutter section and part section. Only the line segments with the same index are compared and trimmed, there is mo need to trim two line segments. If all the line segments fall on the regulated nodes, there is no need to trim two line segments. The set operation can be simplified to the comparison of two Z values, which is very fast and stable. Hence, the Z map representation of IPM emerges [9].

Z Map

If all the section line segments fall on the nodes, the object surface can be represented by the Z values of the nodes. A map of Z values represents the object geometry. In t computer language terms, the Z map can be expressed as a two-dimension array Z[i, j], where i represents the index in X direction and j represents the index in Y direction. The XY position of the Z map can be calculated by i or j times grid size.

Figure 5: Needle bed sample of classic Z Map model

The best analogy for a Z map is a needle bed, where needles are uniformly distributed over the XY plane (Figure 5). The tip of every needle touches the object surface that it represents. A milling simulation can be seen as the tool cutting through the needle bed. These needles can be described in mathematical terms as z-axis aligned vectors, passing through grid points on the XY plane. A Z map representation can be used effectively for surfaces that are visible looking “downwards” on the XY plane. Since 3-axis milling parts are composed of surfaces visible from the z direction, they can be expressed effectively by the Z map representation. With a Z map representation, the machining process can be simulated by cutting the Z map vectors with the cutter. Figure 6 shows an example of 3-axis milling simulation system that was developed by the first author in 1990. The system was using DOS Extender for Z Map and SVGA for Z Map rendering. The GUI and NC toolpath wireframe display was coded with High C graphics library. The GUI and mouse control developments were very hard job and this was not resolved until the arrival of Windows 95 and OpenGL.

Figure 6: Example of Z Map IPM based milling simulation using DOS Extender and SVGA

The vectors in a Z map have direction and length and are infinitely thin without volume. The top of each vector, where the Z map and object meet, is just a point having no shape. Only at this point the Z map and the object meet with each other. Z map models cannot provide accurate object geometry outside these points. There are many ways of interpolating the geometry between grid points in order to render a Z map model. For example, forming a triangle from three neighboring Z values.

It is obvious that the XY resolution of the Z map grid determines the precision of a Z map model. A finer grid has greater precision but requires increased memory. For a part of 1m*1m, the size of the Z map is 1000x1000 if the precision is 1mm, but it increases to 2000x2000 if the precision is 0.5mm. Reducing the model size and achieving suitable precision becomes a critical issue in a Z map.One of the solutions is to balance Z precision and XY precision. We used an integer array to replace the more common floating array of a Z map, which reduces the Z map size by half. At the same time, this improves the Boolean operation speed because the comparison of integers is much faster than the comparison of floats. The memory requirement of a Z map is halved again by compressing the Z map file section by section, similar to image compression.Because of the simplicity of its data structure and fast computation time, the Z map model is used by most commercial CAM software [10]. However, a Z map can not approximate vertical wall very well since it always has a slope as showed in Figure 7. This is not a problem for forging die design since there are always draft angles in forging parts, but it is a serious problem for milling parts since profiling nearly always creates vertical walls [11].

Figure 7: Classic Z Map model with vertical walls

Extended Z Map

Since the precision of the Z map is determined mainly by XY resolution along the vertical walls, increasing the resolution along these walls while reducing memory is a key issue. Fortuitously, one important feature of 3-axis milling can be leveraged. Viewing from the top, the vertical walls only cover a small percentage of the Z direction projection, so it should be possible to use finer resolution along the vertical walls while maintaining a rough resolution in the planar area. This was the initial idea for an extended Z map.

In our research, at least one grid on a z-map is segregated into sub-cells. Only grids corresponding to intricate features on the surface of an object are assigned sub-cells to improve the representation of object features. Figure 8a illustrates the plan view of the z-map grid with sub-cells 52 the front sectional view, while Figure 8b shows the sectional view.

(a)

(b)Figure 8: Extend Z Map with sub-cells along vertical walls

The size of the grid can be reduced through using sub-cells. But the precision of the XY dimension is still limited by the size of sub-cells. For a sub-cell of 0.1mm, the best precision is 0.1mm in XY plane. There is a need to represent XY dimensions precisely. Instead of using vectors in the sub-cells, we use sticks in the sub-cells that have volumes and surface geometry. A B-rep surface model can be represented precisely using a map of B-rep sticks (Figure 9).

Figure 9: Stick method

Milling simulation with stick method involves Boolean operation between cutter and stick. Figure 10 shows different stick shapes after cutting. The experiments with B-rep stick model are very slow and a huge B-rep model is created. To simplify stick and Boolean operation, a polygon is used instead of real surface in a stick cell. The data structure of a polygon is much simpler than that of a B-rep which needs a group of complicated pointers to maintain a double wing data structure.

Figure 10: Different shapes of stick elements

The real world objects are not always uniform in the XY plane and can be any shape. Nodes are used to enhance sub-cell precision in object face representations. For example, one edge of the sub-cell may have two overlapping nodes to represent a vertical face. The nodes of a sub-cell may not be uniformly distributed over XY plane. Figure 11 depicts an exploded plan view of a portion of the z-map grid with nodes 54. Figure 12 illustrates how stick method represents a circular hole and vertical walls.

Figure 11: Extended sub-cells to approximate vertical wall

Figure 12: Extend Z map to represents a circular hole

Figure 13 shows shop floor examples of extended Z Map IPM based NC simulation and verification that was developed in Singapore Institute of Manufacturing Technology and implemented in precision engineering industry for a decade. The detailed description of the extended Z map IPM can be found in two patents [12].

Figure 13: Extended Z map IPM based NC simulation examples

The limitation of the extended Z map is indeed the ‘stick representation’ of the workpiece, which can only simulate 3 axis machining in a fixed orientation. In practice, even for a 3 axis milling machine, there is a need to machine on six sides. So the stick method could be used to simulate 3 axis machining on one side but cannot be used to train machinist for machining operation, where flip the workpiece is a must.

4. Proposed In-process Model

The term voxel represents a volume element in space decomposition geometrical model schema, just like the term pixel denotes a picture element in raster graphics. Voxelization is the process of converting a 3D object into a voxel model. Volume graphics, voxelization and volume rendering have attracted considerable research works in recent years. However, all of this work is directed at the display of volume data, mainly for medical applications. In this paper a simplified voxel-based IPM is proposed to simulate the multi-machining processes.

Further analyzing the voxel model, the authors of this paper believe the voxel-based volume modeling is a very promising approach to the unified IPM for multiple machining and layered manufacturing simulation. As a natural clone of the LM technology, the voxel model of an object and the

object fabricated using an LM closely resemble each other since both are made of layers of small cells [13].

Figure 14: Voxel model and its implementation in machining simulation

The memory requirements of the traditional voxel models are enormous. There is a need to store the voxel array in compressed form and use algorithms that will operate directly on the compressed data, especially when the material is homogenous, where internal voxel could represented by boundary voxel extension. It is possible to convert the voxel array into some other more compact representations and reconvert them into voxels when required. The original geometric representation must be kept and voxelization algorithms will be used when it is necessary. This is especially valuable since design data are mainly generated from conventional CAD system.

A voxel-based system should be able to update the display at interactive rates. Current graphics rendering systems cannot provide a level of rendering performance on voxel models that is comparable to their polygon-rendering performance. Parallel algorithms and hardware support for volume rendering are the focus of current research efforts. We only render boundary voxel by a patented color list, which effectively avoid expensive ray-casting of huge internal voxels. The rendering of voxel model is easily achieved by rendering a points cloud. However, internal voxel display is not possible with this method and needs more study.

5. Industry Training Applications

Based on this new in-process model, we developed a VR training sysem for training CAM programmer and CNC machinists – QuickCNC. The students can simulate the milling process and save the “machined” model for other downstream machining process. The virtual CNC simulator also allows for different situations to be tested during training, which would be costly if done on the machines.

We developed a set of 12 different machining samples that can be used to show the trainee how the generated toolpath works with cutter under various cutting parameters, which are set by the virtual controller. The trainee can learn many setups in a very short time with home PC. The same learning process will take days and shift in a workshop.

It is quite difficulty to show the effect of a wrong setup or NC code on shop floor. For example, the dial indicator is used in workpiece alignment. In the conventional training class, its leg could be easily broken by a beginner. The fast moving cutter also could hurt trainee. QuickCNC could simulate accident through a virtually broken leg and sound effect. Everyone is safe except a record of errors.

Figure 15: QuickCNC simulates the remaining of stock and scallop height

Figure 16: Machine frame, dial indicator, and control panel

Figure 17: QuickCNC machining example for WSQ courseThe precision engineering Worker Skill Qualification (PE WSQ) Specialist

Diploma is a joint initiative by the Singapore Institute of Manufacturing Technology (SIMTech) and the Singapore Workforce Development Agency (WDA) to provide hands-on training to equip future PE professionals in cutting-edge precision machining processing technologies. This programme is conducted through a series of lectures, lab demonstrations and project attachments in selected industrial applications. However, due to the limited numbers of CNC machine tool CNC machinist in our lab, it is a great challenge to conduct hands-on training for all the 40 students on evening session. This was resolved with the implementation of QuickCNC virtual training system. During the high speed machining course, the WSQ student

learned to use simulator to do virtual machining. 12 sets of high speed machining examples virtually explained different high speed machining strategy. The student also can learn from home PC without spending a lot of time at our lab. Furthermore, the student can control the simulation speed to see the details at certain corner, which is not possible on the real machine. Using QuickCNC effectively reduced CNC training time from weeks long to one evening session.

6. The limitation of the system

Lacking of the dynamic simulation limited the effect of virtual CNC training. During the real machining, cutter always vibrates under different cutting conditions. Long tool may chatter under too deep cuts, which will generate marks on workpiece surface. Cutter wears off during long time of cutting.

Lacking of the fun factor in virtual training is still a problem for promoting machining to video game generation, which may become future machinist and CAM programmer.

7. Conclusion and Further Development Plan

The 3D representation of IPMs is essential for the integration of various activities related to manufacturing process planning, toolpath generation, and machine inspection. With nearly twenty-year research & development on the IPMs for machining process, various M&S methods including B-rep, section method, Z map, and patented extended Z map have been studied, which laid a solid foundation of in-process geometrical model to enhance VR for training. The proposed model is implemented in QuickCNC CNC simulator, which has been used in WDA WSQ High Speed machining training course for quick virtual learning of CAM and CNC operations. QuickCNC can reduce training time and learning curve.

We are developing a realistic machining training that can simulate tool chatter, cutter deflection, and tool wear.

Author informationMr. Liu Peiling has been a CAD/CAM researcher and developer for 25

years. His research interests include geometry modeling, 3D NC tool path generation, high speed machining simulation, CAM optimization, and mould design application. He filed two patents about geometrical representation and mould cavity design method. He took part in many industrial projects and one of his developments QuickCNC has been widely used in Singapore PE industry. He developed Virtual CNC Training Lab which has been implemented in Singapore Precision Engineering and Tooling Association (SPETA) for WDA WSQ CNC machining course.

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