Towards Smart and Competitive Sustainable Machining

Mr. Liu Peiling, Principal Research Engineer

Singapore Institute of Manufacturing Technology71 Nanyang Drive Singapore 638075

plliu@simtech.a-star.edu.sg

Keywords: in-process model, CNC simulation, virtual training，machining model,

ABSTRACT

Computer Numeric Control (CNC) revolutionized the machining technology and has been the cutting edge of digital manufacturing since 1950s. CNC machining model, simulation, verification, and optimization have been a vivid research topic of Smart Machining that automated the CNC programming (CAM) and cutting process, hence greatly increased machining productivity since 1990s. This paper traces back the history of CNC simulation, analysis the different CNC machining models, tested with application examples, and listed different CNC verification industry applications for the last 20 years. The new challenge comes from sustainable manufacturing. Towards smart and competitive sustainable machining, CNC model and simulation will be used to optimize the machining process, where the raw material could be saved through First Part Correct technology, the energy could be saved through cutting speed optimization, and used parts could be saved by remanufacturing.

Introduction

Machining had been a low productivity manual operation until the invention of Numerical Control (NC) during 1940s-1950s, when the hand wheels and levers was replaced by punch tapes control, similar to telegraphs at that time. These early servomechanisms were rapidly augmented with digital computers, creating the computer numerical controlled (CNC) machine tools that have revolutionized the machining process and radically changed the manufacturing industry. Complex 3-D shapes are relatively as easy to cut as plane face, and manual polishing works have been dramatically reduced. CNC was the mother of digital manufacturing revolution.

In 1958 the MIT published its report on the economics of NC. They concluded that the tools were competitive with human operators, but simply moved the time from the machining to the creation of the tapes. NC programming became a bottle neck in machining. Computer Aided Manufacturing (CAM) was developed to quicken and automate this process, where the shape could be defined by Computer Aided Design (CAD) software.

A NC program has thousands lines of tool movement instructions that may contain errors. Following these instructions, CNC machine tool will move blindly, without any check on gauging, overcut, or cutting force. It is not possible to verify code manually, so the NC verification software was developed during 1980s. Initially CAD/CAM geometry model was tested to model machining process but failed, since the in-process geometry of workpiece is deforming but conventional CAD model is static [1]. How to develop a in-process geometrical model (IPM) that could simulate the deforming workpiece has been a research challenge [2].

1. In-process Model (IPM) Evolution

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 [2]. In this section, the geometric representation techniques of IPMs for traditional manufacturing simulation are presented.

1.1 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. However, the creation of B-rep 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 [1].

1.2 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 [6-7]. The aim was to use a series of paralleled cross-section drawing to represent 3D shapes. 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 no 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 [3,4].

1.3 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 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.

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. This is a serious problem for milling parts since profiling nearly always creates vertical walls [5].

1.4 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. 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. The detailed description of the extended Z map IPM can be found in two patents [6].

2. Unified In-process Model of multi machining and layered manufacturing

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.

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.

3. Industry Applications

Based on this new in-process model, SIMTech has developed several practical applications for local mould manufacturers. These include QuickCNC and QuickSeeNC, which provide “What You See is What You Cut” functionality for shop floor machine operators and mould designers. The system starts with a solid model of the machined part and quickly simulates and optimizes machining processes. NC code could be selectively reverse post processed into 3D tool path graphics display and interactively viewed, edited, and optimized. Tool paths and cutting results can be viewed from any viewpoint and checked automatically. The machined part and the design part are compared for the remaining stock and over cut, eliminating the need for a time-consuming test cut. QuickCNC has been adopted by local die and mould makers for its speed and simplicity.

Fig 1: Voxel machining simulation

Fig 2: Display the remaining of stock and scallop height

4. Virtual CNC Training Applications

Based on this new in-process model, SIMTech developed a VR training sysem for training CAM programmer and CNC machinists – Virtual CNC Training Lab. 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.

Fig 3: Machine frame, dial indicator, and control panel

5. Sustainable Machining Technology Challenges

Sustainable machining is a material removal technology that can cut raw materials to precise component with reduced emission of greenhouse gases, reduced use of non-renewable or toxic materials and reduced generation of waste.

Competitive sustainable manufacturing is the fundamental enabler of the transition from economic to sustainable development. It requires transformation of manufacturing industry towards Knowledge-based, High-Value, Competitive, Sustainable Products and Services, Processes and Business Models. The Competitive Sustainable Machining Technology, which is a cost effective subset of Sustainable Machining Technologies, focuses on replacing trial cut and manual training by virtual machining simulation, increasing productivity by high efficiency cutting, and reuse material by re-machining of used component. Competitive Sustainable Machining reduces the cost of metal cutting production and is a cutting edge for Asia manufacturing industry.

Faster High Efficiency Machining to Save Energy

Typically either a single conservative feed rate is used for an entire machining sequence, or a higher feed rate is used but with a very conservative machining strategy. Both methods attempt to ensure that the cutter is not overloaded, but at the expense of very inefficient machining. Both of these strategies result in too slow cutting speeds or too light removal rates that waste time, increase costs, and prematurely wear cutters. Achieving the best feed rates for each cut in an NC program has always been a goal for NC programmers but has traditionally been a very difficult task plagued by a number of problems. First, trying to imagine the cutter contact and cutting conditions or each cut in a large NC program is virtually impossible. Manually inserting different feed rates for each changing condition is not practical. An incorrect feed rate estimate can break the cutting tool, damage the fixture, or scrap the part. Machining simulation can be used to check the cutting force and optimize speed.

Re-machining to Save Material

The most of material and energy are wasted in the in manufacturing processes. These wastes can be saved through re-machining of the damaged component, where the damage can be repaired by welding or thermal spray. However, re-machining is a great challenge for CNC machining since the damaged component geometry is warping. Re-machining techniques allow successful machining when some geometry is unknown, by predicative machining model and simulation, using in-process measurement to close any information gaps.

The programming of most machining operations is based around knowing three geometries: the position of the workpiece on the machine, the starting shape, and the final shape. Re-machining techniques allow successful machining when some geometry is unknown, by predicative machining model and simulation, using in-process measurement to close any information gaps. They are being applied for an increasing number of applications in the manufacture and repair of large and complex components in the aerospace industry.

Towards First Part Correct, Full Automatic Machining, and No man Workshop

The ‘First Part Correct’ idea embodies much of the lean concept that we are attempting to achieve. In the time of High-Mix Low-Volume production, there is no time for trial cut. Towards smart and competitive sustainable machining, CNC simulation will be used to optimize the machining process, where the raw material could be saved through First Part Correct, the energy could be saved through cutting speed optimization, and used parts could be saved by remanufacturing.

6. ConclusionMachining is the cutting edge of industry production and its productivity has been the focus since

industry revolution. Machining technology used to be a craft of machinist, where the precision and productivity depended on the skill of a machinist. NC technology revolutized machining process by shifting the control from machinist to NC programmer, where the process is digital and repeatable. Smart machining built brain (IPM) and eyes (TCM) into machining tool, so it could be run faster. Towards First Part Correct machining, it is possible to machine without human interference. Higher productivity could be achieved with no-man machining operation.

References

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[9] http://www.engineeringchallenges.org