Keywords: CAD/CAM, CAM milling strategies, milling process, CNC, manufacturing. Introduction

Transcription

1 Analysis of Milling Machining Strategies that Conducts to an Optimal Solution C. Carausu 1, D. Nedelcu 1, G. Belgiu 2 Gheorghe Asachi Technical University of Iasi, Romania Politehnica University Timisoara, Romania Abstract. This paper compares different CAM strategies for manufacturing milling machines with CNC. CAM applications manufacturers have different approaches to processing by milling the same part. Although in the end of the milling operation the part surfaces were processed (cleaned) identically by each CAM application, it can make some distinctions. Thus, for each case, the processing time is different. Then, processing regime can be different (cutting depth, feed and speed). We mention that we analyzed CAM applications on the same terms identical: same part, same material, same cutting tool, the same jig and the same machine tool. Finally, each processing is actually obtaining a different piece because the CAM machining strategies are different. Thus, according to every strategy, different accuracies are obtained by processing different roughness, different processing times, different tools consumption and energy consumption. The study is opportune because the manufacturing industry wants to maximize process capacity and minimize costs for manufactured parts of an acceptable quality. The paper presents studies in our research CAD/CAM laboratory. The research results can be used for better election of the CAD/CAM system by type, but also for developing new milling machining strategies that attempt to toward an optimal solution. Keywords: CAD/CAM, CAM milling strategies, milling process, CNC, manufacturing. Introduction There are many CAD/CAM applications that can be purchased on the market today (1, 2, 3). Although their prices vary widely, often there is not a two-way link between price and quality of the software. Managers of companies that use these applications are put into difficulty when it comes to choose CAD/CAM system for their company. What is the CAD/CAM to be chosen, especially when it comes to a new business, which should not continue traditional applications (already acquired for the existing business)? Sometimes the CAD/CAM system is imposed from outside the company (by suppliers or customers). In this case can hardly change anything without technical debates substantiated. Or, another problem arises when the manager must make a decision when it finds a deficiency in production management, and determines that the department of the CNC programming is not effective. It is appropriate to change the system CAD/CAM and replace it with one better? What criteria to make this decision? The study of marketing, technical explanations of the CAD/CAM producer, local engineers of the companies, their preference or existing knowledge in the enterprise are enough to make a decision. But this decision is the correct one without technical and technological foundation? Of course, ultimately it is the decision of the manager, who knows all the inner springs of the business. Further developments will prove whether the choice was right or 1-161

2 wrong (4, 5), but still a scientific tool is very useful in developing decision. This paper aims to shed some light on decision-making by managers. References in this area are quite poor: one of the reasons is we do not have a model to follow and the CAD/CAM systems are used in very different fields. Somehow will choose CAD/CAM system for the wood industry and in a different way will select the one for the injection molds for plastics. But even the same sector, for example in mold industry, in a way it chooses CAD/CAM systems for automotive and otherwise for the electronics industry (eg. mobile phones). A simple solution to reach managers is to test all CAD/CAM systems or as many of them. This solution is useful when time (and money) allows. We have not encountered often in practice this solution, mainly due to the short time, which always put pressure on managers. Obviously the manager of several tools to make the decision: goal programming, learning curves, productivity, decision tables, a decision tree with tabular input, and so on. But these tools are not effective because we do not know how the CAD/CAM system will behave in practice. Are true (real) information provided by the manufacturers? That is why we decided to establish a testing algorithm of CAD/CAM systems. It is not our purpose to give marks to of CAD/CAM systems. Nor is the goal also to achieve a ranking of CAD/CAM systems (from best to worst): as for an enterprise is the best system to another enterprise maybe is a weak, totally unproductive. The Method and Equipment for Testing We selected for demonstration five CAD/CAM systems, among: SolidCAM, Mastercam, Creo, Delcam PowerMill, Siemens NX, Catia and Inventor HSM. Although part of different classes with different prices we tested these applications because are widespread in the industry. We also designated a piece not excessively complicated, but a test piece that exist all necessary features for classic milling operation. The test piece is shown in Fig. 1. Figure 1. The test piece. Workpiece material is steel C45 with Rm = 660. The preform is prismatic dimensions 120 x 90 x 40 mm. We prepared five preform in IT6 precision, with roughness Ra = 1-162

3 1.6 μm. We used for milling operation in our lab the machine-tool type Doosan 650 (fig. 2b), a high productivity vertical machining center who is compact and durable machine created with the combination of optimized function with increased rigidity (fig. 2a). The machine weight is Kg. The high productivity of the milling process is the major principle of the DNM machine tool (8). We chose this machine tool for the reason that we consider the complex technologic elastic system consists of machine tool vise part cutting-tool should interfere as little possible in the CAD/CAM analysis. It is obvious that a manager who has on his workshop other machine tools more advanced or less advanced, newer or older will direct its choice based on that. However, the test is better to use a machine tool range top. a) The core of DNM 650 machine tool b) DNM 650 machine Figure 2. The milling machine tool used in experiment (8) For the cutting tool on this experiment we opted for the solution proposed by the company SECO, namely milling holder R A. This concept provides an ideal balance of high performance and cost effectiveness: strong, reliable pocket seats combined with multi-edge inserts the tool optimize stability and provide true 90 walls (9). Selecting this cutting tool we have been suggested that has the following advantages: inserts has tangentially mounted, the strength providing needed for increased depths of cut with small diameters (fig. 3, radial cutter). The insert for this tool was SECO LOEX TR-M08 MP2500 (9). For the process strategy profile milling, the cutting regime parameters are summarized in Table 1. We specify (obvious) that for all five processed parts, the parameters were used for cutting remained identical. As for the cutting tool we applied SECO technology (10), cutting regime parameters calculation was made using MyPages computing platform

4 Figure 3. The milling tool (9) Table 1. Cutting data (10) Material: C45, Rm = 660 N/mm 2 Number of passes (ae) 1 Radial engagement 5.0 mm (ae) Number of passes (ap) 2 Depth of cut (ap) 6.0 mm Feed/tooth 0.12 mm/tooth Cutting speed 290 m/min RPM 5769 rev/min Feed speed 1385 mm/min Engagement angle 68.0 Average torque 3.45 Nm Average machine 2.60 kw power Metal removal rate 41.5 cm³/min (Q) General contour surface ** Stock of surface (Sf): 5 ** Depth of face (Df): 12 ** Minimum radius in concave corner (Rm): 10 ** System stability: Stable conditions ** Surface condition: Pre-machined ** Tool type: All types included ** Tool unit: Metric ** Backend connection: No preference ** Available RPM: ** Available machine power: 50 KW ** Available torque: 450 Nm The system for measuring cutting forces and moments that develop during the machining process is outlined below: Kistler 9272, a 4-component dynamometer, fig. 4. Kistler charge amplifier ICAM 5073A411, fig. 5. Signal conditioning and data acquisition system National Instruments SCXI 1000 (7). In the milling process, the four voltage signals (forces + momentum) are sent to a National Instruments SCXI The chassis is equipped with all necessarily data acquisition and signal conditioning modules

5 Figure 4. Kistler dynamometer 9272 (6) Figure 5. Kistler charge amplifier ICAM 5073A411 (6) Experiment For the experiment we worked five workpieces and were processed sequentially in the same conditions: same machine tool, the same vise, same ambient temperature, with the same coolant-lubricant, same cutting data, and the same cutting tool. Obviously, the type of tool was the same, but for each of the five workpieces we used a new cutting tool in order to eliminate the wear as a disturbing factor. There have been five numerical control programs (NC) using the five CAD/CAM systems. For programming the CNC machine tool were used cutting data presented in Table 1, and the same tool entry / exit / approaching options. An example of a CAD/CAM system used to create the NC program is shown in Fig. 6. It would be useful to measure the time it takes of programming this piece in each of the five systems, but this is subjective matter, related to local programmer as a person. We annulled this parameter. All data were collected in Table 2. Parameters number shown in this table are obvious and need some explanation. Lines 1 and 2 refers to the momentum and the forces developed during the cutting process, which is fine to be as small as possible. The number of inflection points (line 3) refers whenever it goes into the program from G0 to G1 and G2/G3. It is good to be as small. Surface area overlapped (line 6) refers to the fact that the tool will go through the same area several times, without being necessary. For the other parameters are unnecessary explanations, things are clear. It should also be noted that not all parameters have the same importance and in the table were arranged in a random order. For each parameter / feature were given grades from 1-10, with 10 being the best mark. Also, the paper did not specify the CAD/CAM systems under evaluation, this work is for scientific research purposes only and not commercial

6 Figure 6. A CAD/CAM programming example Table 2. Data measured and collected No Feature or Parameter CAM 1 CAM 2 CAM 3 CAM 4 CAM 5 1 Maximum of forces (F X F Y F Z ) Maximum of momentum M Z Number of NC program s lines Number of inflexion points Number of retraction times Surface area overlapped Surface quality (roughness) Cutting tool wear Time for post-processing the NC file Cycle time Conclusions This paper aims to establish a scientific and practical evaluation of CAD/CAM systems. The literature is not very rich in this area. There are articles on the Internet or in CAD/CAM magazines, but they have more a marketing and advertisements value. This scientific paper is not intended to be a benchmarking for CAD/CAM systems. It leaves it up to the manager and NC programming engineers to choose the appropriate system to their needs. But at the same time, the paper establishes a set of rules and even an algorithm to follow, in stages, to correctly assess a CAD/CAM system. It is our first attempt to clarify things in these complex area. If there will be a request from 1-166

7 the industry, we will develop algorithm for roughing and finishing operations, for 2, 3, and 5 axis milling and turning. Eventually, however, it remains user preferences for a CAD/CAM system or another, and this is hard thing scientifically quantifiable. References 1. Requicha A A G & Voelcker H B: Solid modelling: a historical summary and contemporary assessment. IEEE Computer Graphics and Applications, 1982, 2(2), Jones P F: CAD/CAM: Features, Applications and Management. London, The Macmillan Press Ltd, Musca G et al: Implementing a PLM strategy in collaborative network for products develpment. Academic Journal of Manufacturing Engineering, 2008, 6 (1), Musca G et al: Contributions to computer aided training in CAD, CAM, PLM. Academic Journal of Manufacturing Engineering, 2011, 9 (4), Petruse R E et al: Augumented Reality aided 3D Modelling. Advanced Materials Research, 2014, 1036, *** National Instruments, SCXI-1000, /nid/10676, accessed on *** Kistler, Measuring Systems and Sensors, accessed on *** Doosan, accessed on *** SECO, New product launch tooling introductions and expansions 10. *** My Pages SECO, accessed on