Review of Sensor-Based Approach to Reliable High

High Speed Mach. 2014; 1:1–17

High-speed machining Review Article

Open Access

Jay F. Tu* and Martin Corless

Review of Sensor-Based Approach to Reliable High Speed Machining at Boeing – A Tribute to Jan Jeppsson Abstract: Jan Jeppsson was the key architect of a sensorbased system for reliable implementation of High Speed Machining technologies at Boeing Commercial Airplane Group, resulting in substantial increase in productivity in addition to significant cost reduction. Mr. Jeppsson retired from Boeing in 2003 and passed away on December 31, 2012. In memory of his ingenious contributions to high speed end milling technologies in a real production environment, we present this review paper based on his papers and patents. This paper starts with the chatter and control problems encountered in machining commercial airplane structural components, which could be over 100 ft long, using spindles at speeds over 50,000 rpm and end mills over one inch in diameter and axial length exceeding four inches. Mr. Jeppsson developed a software system, Machining Prediction Software (MPS), to identify chatter-free machining windows for different combinations of tools, machine structures, and spindle speeds. The sensor-based milling control system, denoted as the Jeppsson Controller, is used to achieve highest material removal rate with minimal risk of tool breakages and spindle bearings failures. This paper concludes with tributes from Mr. Jeppsson’s co-workers at Boeing, testifying to his character and integrity as a visionary, a mentor, and a leader. Keywords: end milling; chatter; stability lobe; tool breakage; spindle bearings; feed rate control; chatter suppression; feed rate override; bending moment sensor; torque sensor DOI 10.2478/hsm-2014-0001

*Corresponding Author: Jay F. Tu: Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, USA, E-mail: [email protected] Martin Corless: School of Aeronautics and Astronautics Purdue University, West Lafayette, IN, USA, E-mail: [email protected]

1 Introduction High Speed Machining (HSM) is a machining technology aiming at drastically increasing productivity and quality without increasing production costs. Although fundamental theories of high speed metal cutting were reported in the 1930s, machine tools capable of achieving these high cutting speeds did not exist until the 1980s [1–3]. The aircraft industry was the first to implement the HSM technology, followed by the automotive industry and die/mold makers. The term of HSM in this review paper is defined as machining a specific material with spindle speeds and feed rates significantly higher than those commonly used. To provide a historical perspective of the development of HSM technology, we cite two milestones by Jan Jeppsson at Boeing. In the early 1989, most machine tools in use were equipped with a 3300 RPM, 15 HP spindle. In 1996, in less than seven years, these machines had three 10,000 RPM, 100 HP spindles [4]. Today, it is not uncommon to have spindles with speeds exceeding 30,000 RPM and power over 150 HP in actual production in the aerospace industry, while even higher powers and speeds are being evaluated in the laboratories. This paper focuses on the obstacles and solutions in industrial implementation from the perspective of airplane manufacturers. This perspective is often unknown to researchers in academia and the scale of the problems encountered in an actual production setting in the aerospace industry is usually impossible to duplicate in university research laboratories.

2 Main Implementation Obstacles in HSM HSM technology is still evolving and there are many problems to be solved, in particular under the very high power and high loading machining conditions commonly en-

© 2014 Jay F. Tu and Martin Corless, licensee De Gruyter Open. This work is licensed under the Creative Commons Attribution-NonCommercialNoDerivs 3.0 License.

2 | Jay F. Tu and Martin Corless countered in aircraft manufacturing with very large workpieces. These problems include tooling, balancing, thermal and dynamic behavior, and reliability of machine tool components. In the aerospace industry, the use of long tools to generate deep pockets and thin walls also present great challenges, involving intertwined functions of many process parameters, such as depth of cut, spindle speed, cutter dimension, material hardness, feed rate, tool wear, tool breakage, cutting force, structural resonance, control stability, etc. The great concern is that these new problems at high speeds can lead to rapid spindle failures and to scrapped parts, both are very costly to manufacturers [5].

2.1 Chatter and Spindle Failures One of the main problems is chatter. Generally, chatter is described as a self-generated or self-excited vibration in a closed-loop system [6–9], formed with an active chip-cutting process and a passive structure of the cutter/spindle/machine [5]. The chatter problem is compounded in a real production environment in the aerospace industry due to the large parts and the large variety of spindle/tool/structure combinations needed for production. When the chatter frequency is close to the resonance frequency of the structure, the deflection of the cutter-holder-spindle shaft structure is often so large that bearing forces exceed the allowable limits, leading to overheating and/or “lock up” of spindle bearings [5]. To make things worse, the stiffness of the spindle is not constant over the wide variation of temperature, speed, and bearing wear encountered in HSM [10]. Rigid preloading is often required in order to provide high spindle stiffness for high speed end milling applications to resist high cutting forces in both radial and axial directions. At high speeds and high cutting forces, bearing preload can increase tenfold in rigidly preloaded bearings due to thermal distortion, resulting in significant changes in spindle stiffness and thermal preload instability [11–17]. Although many researchers have been successful in characterizing chatter for a specific setup in the laboratory, Jeppsson recognized that, to avoid chatter, cutting parameters, such as axial and radial depths of cut, feed rate and spindle speed, must be selected using the dynamic information of the actual cutter/spindle/machine and the part structure in the real production setup. As a result, a database was needed, which led to the development of the Machining Prediction Software (MPS) at the Boeing Company [18]. The MPS system has been used to design new cutters and to predict chatter at Boeing for machining weak part structures, such as spar chords, when

they are clamped on one leg with a dovetail, and T-chords used for attaching the lower wing surface. The development and implementation of such a database also led to a new set of problems when shop technicians were required to operate complicated modal analysis tools, such as tap tests and spectrum analyzers. To overcome this implementation problem, the team led by Jeppsson developed another system to perform a modal analysis of at least one remote structure across a wide area network, so that a central processing element, instead of shop technicians, can receive the tap test data and perform modal analysis and machining condition prediction without the need to train many operators in many facilities located over a large geographic area [5]. The MPS system will be described in more details in later sections.

2.2 Conservative Machining Conditions for Avoiding Tool Breakage The second important problem in implementing HSM technologies is the tendency of the operator to run the machine conservatively to avoid tool breakage. In his paper on adaptive control of milling machines [19], Jeppsson described a few unfortunate situations in airframe part manufacturing which occurred before the development of his adaptive controller (denoted as the Jeppsson controller in this review paper) for controlling the feed rate. First, there were huge varieties in aluminum part numbers, 50,000 part numbers are not unusual. Aluminum allows a wide feed rate range between 20 to 60 inches per minutes (IPM) vs 5 IPM which is typically used for steel. Due to this large number of parts and the wide range of feed rates, detailed calculation of feed rate for every cut sequence was not feasible and the machinist often chose a safe (i.e., slow) single feed rate for a whole section based on the piece of the section requiring the slowest rate. The machinist was expected to override it for higher feed rates for different sections of the parts but the decision was difficult, because the change from a heavy to a light cut section could occur within a second. In reality, the machinist soon learned what the safe setting of the feed rate was for a major section and left it unchanged, leading to conservative machining conditions and low productivity in machining these airplane workpieces, whose length could exceed 100 feet. In this context, Jeppsson pointed out that the “safe setting” was based entirely upon subjective judgment from the vibration and noise caused by machining forces, which further lead to more conservative feed rates. Another complication in airframe part manufacturing is the extensive use of end mills, over 50% of them be-

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ing extra-long mills, very different from other industries where face milling, boring and drilling are more common. In these other machining processes, the control of the machining load via controlling the spindle power is often adequate [20–22]. However, the spindle power information was proven to be unreliable in controlling end milling processes with extra-long cutters [18]. Due to the rotational inertia of the spindle motor, the spindle power measurement only provides a signal which is related to the average cutting force over several revolutions of the cutter, not the instantaneous force magnitude. However, the force variation of the cutter can change significantly within one revolution at high spindle speeds.

Fig. 2. Resultant milling force with a radial force component and a tangential component [25].

2.3 End Mill Wear and its Detection Fig. 1. Variation of instantaneous force on an end mill cutter during one revolution [19].

This problem of large force variations within a revolution in end milling with the same average is illustrated in Figure 1 [19]. In the three cases shown in Fig. 1, the spindle power is the same, equivalent to the average cutting force; however, the peak cutting forces are very different due to different radial depth of cuts. A spindle power based control scheme would try to keep the spindle power the same by increasing feed rates when the radial depth of cut is smaller, thus unintentionally causing the peak cutting force to increase several times, potentially leading to tool breakage. These incorrect control problems become worse when the cutter becomes dull or clogged by chips. The reason for the inadequacy of the spindle power measurement is due to the fact that it only relates to the tangential component of the cutting force, incapable of responding to the radial components of the cutting force, which could be abnormal, sometimes destructive (Fig. 2). This fact was recognized in some other approaches in which it was proposed to combine the current information of the servo motors and the spindle motor for determining different cutting force components [23, 24].

The third major problem facing HSM is rapid wear of cutting tools. A cutting tool gradually becomes dull with use and when it becomes too dull, it can undesirably affect the final dimensions and finish of the work piece. As described above, tool wear can also cause abnormal and sometimes destructive cutting forces in high speed end milling. An operator often detects tool wear using subjective judgment of tool noise and heat dissipation and stops machine operation for the purpose of inspecting both the tool and the finish of the part. This again leads to conservative feed rates, unnecessary machine down time, and premature tool replacements [25]. A typical solution is to develop statistical data to predict tool life and replace the tool without inspection, as commonly practiced in the automotive industry. Two common tool wear detection methods in end milling are based on: 1) a tool’s acoustic and/or mechanical vibration characteristics; 2) spindle power. The first approach has received a large research effort [26–32]. However, the implementation of a vibration/acoustic monitoring system in the working environment has been slow mostly because the vibration signatures can be very different for different types of milling operations with different tools [25]. The drawback of the spindle power sensing method was discussed in the previous section. To overcome the above difficulties in detecting tool wear, Jeppsson set out to develop a new sensing scheme which is capable of detecting tool wear as it occurs during milling. His scheme will be discussed in details in Sec-

4 | Jay F. Tu and Martin Corless tion 3.6. His idea was based on the observation that the radial force component of the milling force (Fig. 2) is sensitive to tool wear but the tangential component remains relatively constant even in the presence of substantial tool wear. This is the reason why a torque/spindle power based system is not effective in detecting tool wear because the radial force component does not contribute to the spindle torque. To distinguish the radial force component from the tangential component, one could measure the total resultant force and the spindle torque. The spindle torque (or power) measurement could be used to calculate the tangential component, while the total cutting force, also known as the side load, can be determined by measuring the bending moment on the spindle (Fig. 3). This bending moment is very large in the presence of the extra-long cutters used in machining airframe components and can lead to tool/machine damage if not properly regulated. By measuring both the bending moment and the spindle torque, one can calculate the radial force component, which yields an indicator for tool wear. This tool wear indicator will be consistent across different machining conditions and setups (see Section 3.6).

Fig. 3. Bending of an end mill cutter due to the resultant side force [25].

2.4 Process Time Constant and CNC Controller Delay The fourth major problem with HSM is related to the interface issues for different machine tool controllers from different makers. Milling machines controlled by numerical control (NC) systems were first introduced for commercial use in the early 1960’s. When digital computers became widely available, Computer Numerical Control (CNC) systems were standardized with specific programming languages to control the machining parameters such as feed rate. However, it is quite cost prohibitive for individual feed rates to be calculated for all the cutting sequences encountered during a particular milling operation in the aerospace industry, which typically manufactures a large number of different parts in very low volumes. As a result, many systems in the aerospace industry are programmed to uniform feed rates such as 40 IPM for aluminum and 5 IPM for steel workpieces, regardless the cutting sequence [33]. Of course, this leads to either an overaggressive feed rate, resulting in too much cutting force to damage the cutter, or a conservative feed rate for unsatisfactory productivity. In order to control the feed rate actively, one must recognize the delays involved to avoid controller instability. There are two types of delay in a CNC milling system. One comes from the dynamic behavior between the feed rate and the milling force due to the deflection of the extra-long end mill cutter, while the other is due to processing and computing time of the CNC controller. As shown in Figure 4, at steady state, when the feed rate is constant, the average milling force is constant to cause a constant tool deflection (Fig. 3). However, if the feed rate is suddenly reduced to zero as shown at point 70 in Fig. 4, the milling force does not immediately become zero because the tool is still bent and the force only goes to zero when the tool resumes its straight form. As a result, there is a settling time delay between the feed rate and the milling force. This settling time delay can be estimated by experiments to determine the time constant (TTMC) as shown in Fig. 4. This dynamic relationship between the feed rate and the milling force must be considered in the control of the milling force or the controller could become unstable, causing catastrophic failures. Due to the wide adaption of CNC machines, and later the open architecture controllers [34–37], it is advantageous to implement a feed rate controller as an add-on device so that it can be easily retrofitted to an existing machine on the production line or to new machines from different machine tool makers. However, every CNC controller has a delay due to its programming overhead. For

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3.1 Machining Prediction Software (MPS)

Fig. 4. Process time constant between feed rate and the milling force [33].

example, when a measurement is taken at one instant, the corresponding control command is expected to be issued almost at the same time. However, due to the programming overhead, the actual command will be issued with a delay at some later time. This delay should be within the sampling period of the measurement system. This delay combined with the process settling time delay above could lead to instability of the control system [38].

3 Sensor-Based Approach to Reliable High Speed Machining at Boeing From the discussion above, it is very important to recognize the four major implementation obstacles and the perspective of users of HSM technology in actual production setups. For this reason, many techniques and research results presented in the literature, while impressive in the laboratory setting, may not be effective or practical for implementation in the aerospace industry. As a result, the solutions adopted by Boeing, one of the largest aircraft manufacturers, are worthy of publication not only for their practical usefulness but also for their technical insights, of which academic researchers are often unaware. In the following sections, this paper examines some of the solutions at Boeing, sometimes in comparison with those presented in the literature, to broaden the perspective of the HSM technology.

The chatter problem in machining, either in turning or milling, has been explored very extensively in the literature. It is commonly recognized that Tobias [6–8], Merritt [9], and Tlusty and Polacek [39] were among the first to provide explanations of regenerative chatter as stability problems in closed-loop feedback systems. Subsequently, many researchers obtained more elaborated regenerative models for end milling to account for the rotating cutter, multiple cutting edges, the cutter angle, the rise and fall of cutting forces, radial and axial depth of cuts, structural dynamics, time delay, workpiece flexibility, etc. [40– 46, 48, 50–59]. Jeppsson published a very important paper in 1990 at the Advanced Machining Technology III Conference by Society of Manufacturing Engineers, titled “Prediction of chatter in milling with helical end mills” [18]; however, it went mostly unnoticed, perhaps due to its being a conference paper, not widely available. This paper, though ground breaking, has been rarely cited. In fact, there are only two citations based on a scholar google search. However, this paper is important and ahead of its time because it addresses very practical problems encountered in the aerospace industry where long end mill cutters are used, as discussed in Section 2.1. This paper established the theoretical and practical foundations for all Boeing HSM solutions that followed.

Cutter Bending and Avalanche Chatter One of the most important contributions of this 1990 paper by Jeppsson in milling chatter is that it addresses the effects of the cutter deflection (Fig. 3), helical cutting edges, and the tool rotation. This tool deflection issue is very critical to the implementation of HSM in the aerospace industry because extra-long cutters are used (see discussion in Section 2). Many milling chatter papers published after Jeppsson’s paper still considered only short cutters by assuming that the chip thickness is the same along the axial direction of the cutter. By addressing tool deflection, Jeppsson identified a new mode of chatter as the major cause for many problems in heavy cuts with long end mills. He denoted it as “Avalanche Chatter”, which no papers had discussed before and have rarely discussed since. Strictly speaking, the avalanche chatter is not a regenerative type of chatter. The avalanche chatter was described by Jeppsson [18] as follows: “The work reported here clearly demonstrates, by theoretic models and by verification through tests, that one mode of chatter, here called avalanche chatter, is the main

6 | Jay F. Tu and Martin Corless reason for many problems in heavy cuts with long end mills. No papers have yet been found dealing with this type of chatter in milling, even though an equivalent form of chatter in turning has been briefly mentioned (Tobias, 1965). Experienced machinists also recognize that two distinct types of chatter can occur: avalanche and regenerative.” “The avalanche chatter is caused by a static force pattern on the edges, which bends and twists the cutter so that, under certain conditions, the chip thickness tends to increase. This in turn leads to more deformation, and the edge digs into the surface until the radial relief area of the edge prevents further penetration. At that instant, the edge snaps very rapidly out of the cutter, and the cycle (called limit cycling) repeats itself if the conditions remain the same.” “This tendency of an edge to dig in or “catch” on the surface is of course very commonly observed when using many other tools, such as simple hand tools. That this type of chatter is not a dynamic problem is evidenced by the fact that it can be observed even at the lowest spindle rotation speed. However, the amplification of the limit cycling motions and forces is on the order of 10 to 50 times when they have a frequency close to that of the mechanical resonance system. Several modes of oscillations can easily be excited by the large force fluctuations caused by the chatter.” “Once an edge has made a groove in the surface, this acts as trigger points for the avalanche cycle of the following edge, and in this sense one could say that this is also regenerative chatter, but to avoid confusion with dynamic stability type chatter, the term “regenerative” is still used only for one type.” There are several factors important for the occurrence of avalanche chatter. First, the relationship between chip thickness and the radial cutting force in milling is not linear due to the finite size of the cutting edge, typically 0.0004 inch (0.01 mm) for a sharp tool. For example, in up milling, a cutting edge enters the material at nearly zero chip thickness and exits with a larger chip thickness depending on the feed rate and the radial depth of cut. Due to this nonlinear effect, when the chip thickness is small, the finite radius of the cutting edge causes a negative rake angle and thus a higher Chip Ratio (radial cutting force over chip thickness). Jeppsson’s measurement shows that the chip ratio usually increases linearly with cutting speed in machining aluminum, up by 50% until the cutting speed reaches 150 feet per minute (46 m/min). The indication of this large chip ratio at small chip thickness is that the radial cutting force could be substantial as soon as the cutter enters the material. Typically, the milling force is assumed to be zero when the cutter just enters the material.

Figure 5 is a recording of the milling force during avalanche chatter when cutting with a 0.5 inch diameter by 3 inch long flute cutter. The large spikes in Fig. 5 are due to the cutter snapping off the workpiece. A frequency spectrum analysis of Fig. 5 reveals that the harmonics of the forces are below 300 Hz while the cutter resonance is about 850 Hz; therefore, cutter resonance does not contribute to this type of chatter.

Fig. 5. Force recording of avalanche chatter (Jeppsson, 1990)

Static Force Model and Avalanche Chatter Criteria A static force model was proposed by Jeppsson [18] to determine the static milling force by considering tool bending, tool twist, tool runout, cutting edge radius, cutting edge helical angle, tool rotation, tool clamping, cutting speed, and feed per tooth for both up and down milling processes. In order to calculate the cutting force, a cutter must be divided into many small sections, both axially and rotationally, to account for different chip ratios. In [18], 72 angular positions, covering a sector of 5 degrees each, are used and the thickness of the axial slice is determined by the helical angle to match 5 degrees in each slice. This model is considered as static because the force is assumed to be dependent on the chip thickness, but not linearly. Most papers on milling chatter assume that the milling force depends linearly on the chip thickness without considering the effect of the finite cutting edge radius size as described above. After identifying this new mode of chatter, Jeppsson established an avalanche chatter criteria based on his static force model to check if the milling force will cause a divergent tool deflection, indicating the occurrence of avalanche chatter. The limiting radial depth of cut for avalanche chatter for each specified feed per tooth can

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then be determined and the results are shown in Figure 6. Based on Fig. 6, avalanche chatter can be avoided if, for example, the radial depth of the cut is controlled to be lower than 0.09 inch when the feed per tooth is 0.001 inch. In practical implementation, Jeppsson also found out that avalanche chatter was critically affected by tool holder design. To avoid the avalanche chatter, the tool holder must be stiff in both torsion and bending modes. This observation led to modifications in tool holder design at Boeing.

Fig. 7. Static and dynamic forces on the rake area, calculated [18].

Fig. 6. Avalanche chatter limit defined by radial depth of cut vs feed per tooth [18].

Dynamic Force Model One unique aspect of the treatment of regenerative milling chatter by Jeppsson is his inclusion of a dynamic force component in the total milling force. This addition is different from most milling papers which assume that the force is statically proportional to the chip thickness. On top of the static force calculated based on the nonlinear static force model, Jeppsson proposed that there was also a dynamic component which was related to the radial velocity of the cutter and the damping force due to the workpiece sliding over the flank area and rake area of the cutter, as well as the rate of change in chip thickness. The total milling force was then the combination of the static and the dynamic forces. Examples of static and dynamic forces versus chip thickness are shown Figure 7, which clearly shows that the total milling force is not simply proportional to the chip thickness. Again, the complexity of this overall milling force model, published in 1990, is ahead of its time and it plays a critical role in the success of the MPS system at Boeing. Interested readers are suggested to read the original paper for more details.

Regenerative Chatter Prediction The inclusion of a dynamic force component has a very important effect on the prediction of regenerative chatter. The classical lobing diagram and its variations for predicting regenerative chatter usually indicate stable milling regions in a plot of axial depth of cut versus spindle speed for a specific radial depth of cut. In these chatter prediction lobing diagrams, the results typically indicate that if the milling is conditionally stable then one has a stable milling process with a small axial depth of cut up to the onset of chatter when the axial depth of cut reaches a critical value. When the axial depth of cut exceeds the threshold, the process becomes unstable. However, in reality, it is found that stability can be re-established when the axial depth is raised above a certain value, above the threshold, at the same spindle speed and radial depth of cut. This behavior cannot be predicted by the classical lobing diagram and its variations. This problem with classical lobing diagrams is likely due to the assumption that the milling force is merely statically proportional to the chip thickness. Recognizing this fact, as well as considering a multi-mode dynamic model of the cutter/spindle system (instead of the typical simple second order mass-spring-damper model), Jeppsson opted to use a Nyquist plot for stability analysis of the entire milling system. This approach provides the flexibility to incorporate a more complete description of the part/cutter/spindle dynamic system (denoted by the mechanical resonance system in Figure 8), different process delays (denoted by the delay function), and a more accurate milling cutting mechanism (denoted by the process force generator) for a real production environment in the aerospace industry. Again, the obstacles are due to large parts and a large variety of spindle/tool/structure combinations needed for production. In MPS, the mechanical system is no longer a simple mass-spring-damper system as in most milling chatter papers, but an experimentally determined transfer func-

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Fig. 8. Block diagram of the entire milling system with process delay, cutting mechanism, and mechanical system [18].

tion through the tap test (to be discussed further in the next section) for different cutter/spindle/part/fixture combinations [60]. The Machining Prediction Software (MPS), discussed in the previous sections, contains several modules, developed over several improvement cycles, to take in all the necessary information (Figure 9) to predict stable milling conditions. The MPS also has an interactive user interface to allow the machinist to use it in actual production lines.

Fig. 9. Machining Prediction Software implemented at Boeing for stable milling prediction [61].

The first module of the MPS system allows the user to enter the “best guess” data on a setup menu and the user can change the feed, speed, type of cut, process delay mode, angular positions, axial depth of cut and radial depth of cut interactively, while observing a Nyquist plot, which predicts if chatter will occur or not. If chatter is predicted, the regenerative chatter frequency is displayed. For example, if HSM of aluminum is analyzed, the user can use this software module to find an optimal speed to avoid chatter at a maximum cross section. Once this condition is identified, another software module is used to produce the process conditions for the selected setup. The process conditions include forces, bending moments, bearing loads,

and cutter deflection. The cutter forces in radial and tangential directions are displayed for different rotational positions from 0 to 360 degrees. The cutter deflection also includes the dynamic deformation due to high speed spindle rotations. The user can then change depths of cuts, feed and speed again to ensure the forces and deflections are not excessive, and the stability can be re-examined. The software also allows the user to set up a sequence of cuts, such as one roughing cut, followed by a finishing cut and then one or more spring passes. The spring passes are important for cuts with long axial depths, particularly in hard metals such as steel and titanium where cutter deflection can cause inaccuracy. The material left due to cutter deflection on the preceding pass is taken into account when calculating the deflection for the current pass [61]. In addition to the above typical process parameters which can be defined by the user, the MPS system is also capable of examining the effects of process parameters which are not controllable by the user, such as spindle/cutter runout, tool wear, and the change of cutter/spindle dynamics due to bearing wear, speed, thermal preload, etc. Finally, because the MPS is used in actual production lines, it has to consider other practical implementation problems in addition to chatter. The process conditions must also ensure that the lives of the spindle, the cutter, and other important machine components are not shortened. Therefore, six process constraints are checked over a range of axial and radial depth of cut for specific feeds and spindle speeds. These constraints include a bending moment limit, bearing load limit, spindle horse power limit, avalanche chatter limit, regenerative chatter limit, and tool deflection limit. Note that Jeppsson did not attempt to suppress chatter even though he must have been aware of various passive and active chatter suppression schemes proposed in the literature, such as active damping and spindle speed control [62–71].

3.2 A Brief History of MPS Implementation at Boeing It is of interest to the HSM community to learn how new technology can be incorporated into a real production environment, in which more than just technical problems must be overcome. In his paper, “Sensor Based Adaptive Control and Prediction Software – Keys to Reliable HSM” [61], published in 1999 at the APEX’99 Machining & Metalworking Conference, Jeppsson provided the follow-

Review of Sensor-Based Approach to Reliable High Speed Machining at Boeing

ing brief history and struggles on the implementation of MPS at Boeing. The work on MPS started in middle of 1989 when HSM was not yet implemented at Boeing’s shops in Auburn, Washington, USA. Therefore, MPS was applied in the lower speed range used in the shop at the time. The first acceptance of MPS was not until August 1992 when it correctly predicted the regenerative and avalanche chatter of a particular cutting setup. After it was accepted, the implementation had to be carried out through NC programming and the training of NC programmers was started on a very small scale. “After some time, it was obvious that most programmers did not use MPS before they had run into chatter or other problems during tape tryout (TTO). MPS was not used as intended, to deliberately optimize selection of cutters and cross sections before writing the program itself. The reason for this was the extreme pressure to produce part programs, even if not 100% optimal and even if several cycles of TTO adjustments were needed.” Early in 1993, Boeing installed a new machining cell containing two large three-spindle machines of 10,000 RPM and 100 HP for the wing manufacturing shop. “As of June of that year, no parts had been produced because of chatter problems. Attempts to cut the parts had instead destroyed six spindles over a half year period. This poor result was a good demonstration of the drawback with HSM – the difficulty for most programmers and machinists to avoid chatter without using analytical software like MPS. After that first experience, the programmers asked for MPS to be used in their cell, and very quickly good parts were made. In spite of that, it was very soon realized that the spindle tapers wore out within only 20 to 30 hours of machining, necessitating disassembly and re-grind, a very costly operation.” “This fact demonstrated another drawback of HSM – that in many cases one is forced to accept a compromise between material removal rate and spindle life. This is because the forced vibrations from the cutting edge hitting the parts excites the cutter-holder structure so much that the allowable bending moment at the gage line is exceeded. This limit, based on experience data, is as low as 6000 in-lb for a 50 taper interface.” As a result, “only 10 HP can be applied to the cutter on many cuts” even though 100 HP is available. Therefore, MPS “had to be expanded to also predict bending moment at the gage line and also the load on the front bearing” and “amplification of forces due to structure resonance had to be taken into account.” After MPS had been applied to many other HSM cells, often it was still used “only as a trouble-shooting tool”, not “for planning

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of the machining operation”, as intended. A large effort to train NC programmers and shop personnel was started in November of 1999. As the consequence of the above success, the use of MPS has been expanded at Boeing. For example, “MPS has also been used to design new cutters with inserts, which are now used for spar chord machining. These cutters replaced large, in house cutters with brazed on carbide edges.” MPS has been also used to predict chatter for “machining weak part structures”, such as spar chords and Tchords. “As the stock material is cut away, the part gets weaker in the middle span area, so chatter develops. Using the MPS program with part dynamics data from a tap test resulted in correct speed prediction.”

3.3 Milling Force via Bending Moment Measurement As mentioned several times in previous sections, one unique aspect of Jeppsson’s work is his consideration of the total tool cutting force and its effect on the tool deflection (Fig. 3). In fact, the total cutting force and the tool deflection interact with each other to affect the chatter characteristics and possibly leading to tool breakage. It became obvious that a sensor must be developed to measure a signal which is closely related to the total cutting force so that it could be regulated via feedback control to prevent overloading the tool. He started working on this problem at the beginning of 1982 and the evaluation of his adaptive milling control system started but was interrupted due to many unrelated machine maintenance problems and a long strike in 1989. The interruptions allowed him to start working on the MPS system. There were a few sensors available at the time, one of them was the Promess sensor which was a set of strain gages mounted on the spindle bearing outer ring [72–74]. The Promess sensor was effective in determining the internal bearing preload and the external loads in different directions in a real production environment for preventive maintenance [14, 15], and for characterizing unstable thermal preload characterization [12]. However, this sensor could not be reused after the bearings failed. Also, the cost of the sensor and its installation was substantial. Although many other sensor schemes have been presented and reviewed in recent years [75–82], Jeppsson’s approach still stands out as one of the simplest, most sensitive, and cost effective methods. Jeppsson’s idea is very simple. Because long cutters are used, the bending moment supported by the spindle is proportional to the cutting force at the tip of the cut-

10 | Jay F. Tu and Martin Corless ter. The spindle housing, therefore, becomes an ideal location to mount strain gages to measure this bending moment and mounting is easy without an elaborated process as required by the Promess sensor. The sensitivity is high because the distance from the housing to the cutter tip amplifies the moment and the response time is short because a strain gage is pretty much a zero-order sensor dynamically. It can also be adapted to almost any spindles from any vendors. This bending moment sensor design is disclosed in a patent (U.S Patent # 4,698,773, [33]) granted to Jeppsson in 1987. Figure 10 is a schematic of this sensor design.

Fig. 11. Bending moment measurement and feed rate control command versus time in second during high speed milling of 30-mm deep pocket in steel block [38].

Fig. 10. Strain-gage based bending moment sensor mounted on the spindle housing [25].

A bending moment measurement history during high speed milling of a 30-mm-deep pocket in a steel block with a Mori Seiki SH630 machining center is shown in Figure 11 [38]. This was a rough cut sequence. The nominal feed rate was 500 mm/min (∼20 in/min), the cutter was 4-flute solid carbide coated tool of 25 mm (∼1 in) diameter and 50 mm (∼2 in) long, and the spindle speed was 1,450 rpm for rough cuts and 5,000 for finish cuts. During rough cuts, the maximum radial depth of cut was 2 mm. The gage line distance was 4.4 in. The bending moment was regulated to be less than 8,000 in-lb, which is equivalent to a 1,800 lb side force. As shown in Fig. 11, the cut started with a thin section initially, for which the resulting bending moment was below 8,000 in-lb. There

was also a brief period before two second mark that the bending moment was nearly zero, indicating that the tool and the workpiece were not engaged, i.e., air cutting. Because the bending moment was well below the set point, the feed rate was increased to 750 mm/min or 150% of the programmed nominal rate until shortly before the 4th second when a brief thick section was encountered. This thick section caused the bending moment to increase from about 4,500 in-lb to over 8,000 in-lb at the 4th second. During this increase, the feed rate was reduced to keep the bending moment from increasing further. Even though overshoot was observed, it was limited to about 10%. As soon as the cut of this thick section was completed at about 4.6 second mark, the feed rate was restored to 150% override until the next thick section was encountered at about the 5th second. From the 5th second on, an increasingly thicker section was encountered and the bending moment again increased rapidly from 1,000 in-lb to exceed 8,000 in-lb within one second. The feed rate was reduced down to only 15% of the nominal feed rate. From the 12th second on, the section of cut became gradually thinner and 150% override was resumed at the 13th second. The bending moment could have continued to rise and damaged the spindle if the feed rate had not been regulated. The above feed rate control was accomplished automatically via a control scheme, denoted as the Jeppsson Controller in the paper by Tu, Corless, and Jeppsson [38], which will be described in details in the next section. This feed rate override control system eliminates conservative machining described in Section 2.2.

Review of Sensor-Based Approach to Reliable High Speed Machining at Boeing

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3.4 Robust Control of High Speed End Milling with Unknown Process Parameter and CNC Delay Jeppsson’s nonlinear, robust controller for milling based on measuring side load (Figs. 10 and 11) was inspired by Mathias [83–85], which controlled the milling process based on the measurement of cutter side load by sensing the deflection of the spindle shaft and the balls in the front bearing. However, Mathias’ approach cannot handle the case in which the bearing dynamic conditions change substantially as in the case of HSM. Adaptive milling control schemes were also presented in early 1980s [86–88] and later years [89, 90, 92–94] to address the nonlinearity in milling. Jeppsson’s milling control approach stands out for its effectiveness at controlling high speed end milling for the actual production process in the aerospace industry where many problems are present such as tool compliance, servo controller delay, and unknown process parameters due to wide variation in cutting conditions, very high cutting forces, and large spindle power. It was developed in 1982 and has been implemented at Boeing since 1989. We denote it as the Jeppsson Controller for its unique practical and theoretical approach. The success of this closed-loop milling control has significantly reduced failures of high speed spindles at Boeing by more than 90%. Again, Jeppsson’s milling control was ahead of its time. Its stability was later analyzed in [38]. Figure 12 is a representative setup of the Jeppsson Controller. In Fig. 12, a pocket is machined by an end mill and it takes several machining steps for completion. In this figure, d is the cutter diameter, Dr is the radial depth of cut, Da is the axial depth of cut, N is the spindle speed, and V is the feed rate. The tangential milling force is Fx and the radial milling force is Fy, both of them contributing to the bending moment measured by the strain gages mounted on the housing. The Jeppsson Controller sends override commands to the CNC controller to change the feed rate based on the bending moment measurement. The aim of the Jeppsson Controller is to achieve the highest possible feed rate without overloading the spindle. Conventional closed-loop control approaches, such as PID controllers, use the difference between the force set point and the measured force to regulate the feed rate through a fixed or adaptive gain scheme of the controller. However, the output force responds to a change in feed rate, which is further determined by the cross section of cut (i.e., the radial and the axial depth of cut). Based on the orthogonal cutting model, this phenomenon can be explained as follows: the feed rate determines the feed per tooth which is

Fig. 12. The Jeppsson Controller for controlling high speed end milling [38].

equivalent to maximum possible chip thickness; the feed per tooth and the radial depth of cut determines the actual maximum chip thickness. The actual chip thickness along with the axial depth of cut, which is equivalent to the width of cut in the orthogonal cutting model, determines the actual maximum cutting force. The cutting force in milling is not constant due to variation in chip thickness. It is the maximum cutting force the Jeppsson Controller intends to regulate. As shown in the top view of Fig. 12, during the current pass, the radial depth of cut (Dr ) increases from zero to a maximum and down to zero again. Because the cross section of cut is for all practical purposes unknown, the relationship between the cutting force and the feed rate is often unknown. This unknown relationship represents an unknown process gain (cutting force over feed rate) which can have large variations due to a large variety of cutting conditions. As a result, conventional feedback controllers using a fixed gain scheme are often unsatisfactory due to their inability to compensate for this large variation in process gain. As shown in the top view of Fig. 12, end milling is used to cut a pocket into a steel block. In practice, many passes are needed to cut this pocket into the desired profile. As a result, during each pass, the radial depth of cut is often unknown and not constant. The Jeppsson Controller aims to cut the material at the maximum feed rate when the radial depth of cut is thin and then reduce the feed rate accordingly when the radial depth of cut increases to keep the cutting force below a set point. In this way, maximum possible material removal rate can be achieved without the risk of damaging the spindle. Figure 13 illustrates the block diagram of the Jeppsson Controller. The Jeppsson Controller is an add-on controller which issues a feed rate override command, u, to override the programmed feed rate, Vcnc , by the CNC controller. The

12 | Jay F. Tu and Martin Corless override command is expressed in percentage, i.e., when u = 100%, there is no override action. Hence, when u = 150%, it indicates a 50% increase of feed rate over the programmed feed rate. The actual feed rate command sent to the servo will be Vcnc *u. Input to the Jeppsson Controller is a desired cutting force, Fs , and the measured cutting force, F, converted from the bending moment measurement. A significant delay usually occurs in the CNC controller between an override command issued by the Jeppsson Controller and the corresponding feed rate command issued by the CNC controller to the servo system. This delay can cause instability. The servo controller drives the spindle system and achieves an actual feed rate, V. The actual control action of the Jeppsson Controller is illustrated in Fig. 11 for milling a pocket in a steel block as described in the previous section.

α, which is a function of the sampling period T, the process damping and the cutter stiffness. The process damping and the cutter stiffness are affected by the setting of the milling process (axial and radial depths of cut) and can have a large variation, over several orders of magnitude. The process damping for a specific axial and radial depth of cut can be estimated via the process time constant as shown in Fig. 4 but in practical application of the Jeppsson Controller, it is assumed to be unknown and to have a large variation. Therefore, the Jeppsson Controller must be robust and ensure that the closed loop system is stable about a desired equilibrium over this large variation of the process parameter. Figure 14 demonstrates that the eigenvalues of the Jeppsson Control system are within −1 and 1 for a large range of α from very small (nearly zero) to very large (100). Results from actual implementation of the Jeppsson Controller are consistent with the stability analysis.

Fig. 13. The block diagram of the Jeppsson Controller for controlling a high speed end milling process [38]. Fig. 14. The variation of system eigenvalues with the process parameter [38].

Stability of the Jeppsson Controller The discrete Jeppsson controller is described by   Fs u ( n ) = u ( n − 1) y (n)

(1)

Where y(n) is the current measurement of the cutting force. Interestingly, the Jeppsson Controller is not in the typical form which considers the difference between the desired force, Fs and the measured force y(n). Instead, it uses the ratio between Fs and y(n). The readers are referred to Tu, Corless and Jeppsson (2004) for a detailed stability analysis of the Jeppsson Controller. Based on this analysis, the stability of the Jeppsson Controller depends on the value of a process parameter,

Even though the Jeppsson Controller has excellent robustness, its performance is still affected by the process parameter. A large α value represents a light cutting condition where both the axial and radial depths of cut are small. According to Fig. 14, when α is large, the eigenvalues only change slightly; therefore, the convergence rate of the closed-loop system is not affected significantly by α. On the other hand, when α is small, it represents heavy cutting conditions and the eigenvalues can change substantially, causing substantial changes in the convergence rate of the Jeppsson control system.

Review of Sensor-Based Approach to Reliable High Speed Machining at Boeing

CNC Delay and Controller Saturation As described in Section 2.4, the Jeppsson Controller is an add-on device that can be integrated with different CNC controllers and machine tools from different tool makers. Therefore, the delay caused by the CNC controller must be taken into account in the stability analysis of the Jeppsson Controller. When considering the delay time in the stability analysis, it was proven that the closed-loop system is stable for a CNC delay up to about 90% of the sampling period T. For the version used in IMTS’98, the sampling period was 50 ms, while the CNC delay was 10 ms; therefore, the CNC delay is not long enough to cause instability. However, CNC delay time is reduced with CNC controllers using newer and faster computers. In addition, the Jeppsson Controller is now implemented using a DSP plug in board in a PC and is capable of communicating with a CNC controller via a high speed serial bus or other interface to further reduce CNC delay time. Finally, in actual implementation, the controller in Equation 1 must be modified when y(n) gets close to zero, e.g., when cutting air; therefore, the lower limit of y(n) is assumed to be 1% of Fs . Also due to the limit of the servo system to control the feed rate, there is an upper limit on the override command, which is capped at 150%. Both of these two saturations affect the performance of the Jeppsson Controller, but in simulations, the Jeppsson Controller still performs very well when the cutting condition is changed from cutting air to cutting thin sections within 0.1 second and from cutting thin sections to thick sections within 1.2 second.

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was granted a US patent for this new tool wear detection technique in 1989 (US Patent 4,802,095). The capability of this tool wear detection technology was demonstrated at IMTS’98 on two machine tools, Mori Seiki SH630 and Makino MC1013 [61]. As shown in Fig. 15, four cuts were made on a 24 inch long aluminum bar, 7075T651 with a 3-flute cutter with 1 inch diameter and two inch flute length. The spindle speed was 8000 RPM and the programmed feed rate was about 200 IPM. The first three cuts were made with sharp tools, while the fourth cut was made with a dull tool having a wear land of 0.004 inch. In the first cut, the radial depth of cut was 3 mm and the axial depth of cut increased linearly from 0 to 50 mm. The second cut made a return trip and had similar changes in the axial depth of cut. In the third cut, the axial depth of cut was fixed and the cutting was stopped to replace the sharp tool with a dull tool. The feed rate override was 100% for the first two cuts, 80% for the third cut, and 30% for the fourth cut to maintain the bending moment under the limit. The tool wear indicator, which is the ratio of the radial for cutting force to the tangential force as defined above, showed a consistent value of 1.2 for all three cuts with the sharp tool and 2.5 for the dull tool. Remarkably, the tool wear indicator value is insensitive to the changes in cutting process parameters with the sharp tool, which provides a validation of the effectiveness of this tool wear indicator.

3.5 Tool Wear Detection In HSM, even a slight tool wear of 0.004 inch, considered minor by many machinists, can cause a large overload in the cutting force. As a result, the federate needs to be reduced to prevent overloading the cutter and the spindle when the cutter is dull. The relationship between feed rate and the bending load becomes a potential indicator for tool wear and this technique is different from the previous work reviewed in Section 2.3. This technique is also suitable as an in-situ tool wear detector during milling. Specifically, the bending moment and the spindle power are used together to calculate the radial cutting force, which is proven to be most sensitive to tool wear, and the tangential cutting force, which is less sensitive to the tool wear. From cutting with sharp cutters, the ratio between the radial to the tangential component of the cutting force can be obtained and is used as an indicator for tool wear. Jeppsson

Fig. 15. Four different cuts with a sharp and a dull tool to demonstrate the effectiveness of the tool wear indicator [61].

3.6 Monitoring other Process Problems The signal measured by the strain gages mounted on the spindle housing can also provide information for many other process problems. By examining the frequency spectrum of the measurement from one of the strain gages, some frequency signatures can detect unbalance of the

14 | Jay F. Tu and Martin Corless cutter/holder setup, spindle runout, regenerative chatter, and impending bearing failure. When regenerative chatter occurs, the strain gage measurement shows unusual harmonic peaks unrelated to the cutter’s flute number. For example, without chatter, the signal has a large peak at the 3rd harmonic when a 3-flute cutter is used. Other peaks are multiples of the third harmonic, i.e., 6th , 9th , etc. When chatter occurs, peaks show up between these specific harmonic peaks. The operator then needs to adjust the spindle speed to render the 3rd harmonic peak to match the chatter peak. Then, the chatter will likely stop. However, if the cross section of cut is too large, there is no speed at which the chatter will go away except for extremely low speeds such as 100 to 200 RPM, which is no longer in the HSM range [61]. If the chatter frequency is too high for the spindle speed to match the 3rd harmonic peak, the operator could try to match the 6th harmonic but there is a smaller chance of success [61].

4 Jeppsson, a Trail Blazer and a Mentor with an Enormous Intellectual Capacity Both authors of this paper have had the honor to work with Jan Jeppsson on projects funded by Boeing. The first author visited Boeing many times between 1996 and 2002. To say that Jan’s intellectual capacity and willingness to share were impressive is a gross understatement. In the appendix, a letter written by one of his closest co-worker at Boeing, Dr. Xu, is attached. A brief quote of this letter is cited here: “Jan was a mentor to many engineers within Boeing and across the industry. When high speed machining technology was still new in industry, many engineers received their first high speed machining lesson from Jan. In order to implement high speed machining into production, Jan worked closely with NC programmers, production leads, manufacturing engineers and maintenance technicians to introduce the high speed machining concept and resolve problems in every step of the production. In the modern manufacturing industry, many aerospace parts are manufactured outside the company by suppliers. Jan frequently traveled to the suppliers’ facilities to teach high speed machining and help implement it into their facilities. Jan was respected and beloved by many of his colleagues at Boeing. In particular, Jan was very popular in production shops where he spent a lot of time implementing high speed machining into production. He became good

friends to many on the shop floor, from factory directors to machine operators. His in-depth knowledge of high speed machining also won his reputation in academia. He collaborated with several professors in research and development and jointly published papers to contribute to the engineering society.”

5 Concluding remarks Jan Jeppsson had made ingenious contributions to the HSM technology in solving two of the most difficult problems, chatter prediction and milling feed rate control, for the actual production process in the aerospace industry with workpieces over 100 feet long. However, his work is rarely cited in the literature. With this inaugural paper for the Journal of High Speed Machining, the authors would like to use the contributions of Mr. Jeppsson as an inspiration for future articles published in this Journal to address innovative HSM solutions with both practical and theoretical insights.

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Review of Sensor-Based Approach to Reliable High Speed Machining at Boeing

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Review of Sensor-Based Approach to Reliable High Speed Machining at Boeing

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Appendix: A: A testimony on Jeppsson’s contribution from his colleague at Boeing.

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