Controlling chatter in milling is a significant MRO/MROP supply chain solution. By some measures, cutting tools are the largest product segment in MRO. Cutting tools represent 24.1% of industrial distribution sales with the next largest category reaching only 9.9%. Milling, which is the focus of this paper, is the largest cutting tool category at 40.2% of the market. Improving milling operations will therefore have a very large impact on the MRO spend and the overall efficiency of a manufacturing plant.
What is chatter?
Chatter is a self-excited vibration that can occur during machining and become a common limitation to productivity and part quality. The onset of chatter during machining is primarily a function of the variation in chip thickness that occurs due to vibration of the tool. The flexible tool engages the workpiece and, due to the cutting force, begins vibrating. This vibration is imprinted on the machined surface. In milling, the next tooth on the rotating cutter over- cuts this wavy surface produced by the previous tooth. This wavy surface varies the instantaneous chip thickness which, in turn, modulates the cutting force and the cutter vibration creating a feedback mechanism we hear as chatter. Efforts to avoid chatter, by slowing down the process, can lead to underutilization of the machining system by a factor of five or more. The variation in chip thickness per tooth described above leads to uneven tool wear and premature replacement or failure. Chatter in milling, and efforts to avoid it, is estimated to cost manufacturers over $100 Billion in lost productivity Worldwide.
With the advent of industrial vending machines and tool data management systems, manufacturers are getting near real time visibility into their cutting tool consumption, perhaps for the first time. What is discovered is that cutting tool use spikes dramatically, even if the part output remains relatively stable. Why is this? Cutting tool consumption is dynamic, subject to constant variation, rather than being static and controlled. An example of a static product is a cap screw. If a part requires four screws and the customer produces 1000 parts per month, the supplier will need to deliver 4000 screws each and every month. Easy to forecast, procure and deliver.
That same part may require 100 carbide endmills to machine those 1000 parts one month, need 200 the next and only 80 the month after that. Let’s assume that the customer maintains one month’s worth of inventory on hand. In order not to risk a stock-out and a stoppage of production, their stock level will be based on the worst case scenario, that is, the highest usage rate or 200 endmills. This means excessive inventory costs of as much as 60% in this example. Also, if there is a stock-out and the end user maverick buys endmills from a second supplier to fill the shortfall, the vending machine software does not know this and its optimum inventory level is never updated. Future stock-outs and production stoppages are inevitable.
The reasons for this variation can be traced back to supply chain fragmentation, lack of standards and tool control, but it is most likely due to chatter and the response to it.
A Wikipedia article entitled “Speeds and Feeds” describe the current method;
“In CNC machining, usually the programmer programs speeds and feed rates that are as maximally tuned as calculations and general guidelines (with charts and formulas) can supply. The operator then fine-tunes the values while running the machine, based on sights, sounds, smells, temperatures, tolerance holding, and tool tip lifespan".
Hardly sound repeatable.
Dr. Scott Smith, Professor and Department Chair of Engineering at the University of North Carolina at Charlotte likes to say, “Random processes produce random results”. This randomness of change at the CNC machine by each operator makes accurate forecasting and optimizing of the cutting tool inventory levels virtually impossible. Variation also comes in the form of suppliers. The cutting tool industry is highly fragmented with no one manufacturer having a greater than 20% market share. The supply channel is equally fragmented with many competing distributors, as described below:
“...a large, fragmented industry characterized by multiple channels of distribution. We believe that there are numerous small retailers, dealerships and distributors that supply a majority of the market. The distribution channels in the MRO market include retail outlets, small distributorships, national, regional and local distributors, direct mail suppliers, large warehouse stores and manufacturers’ own sales forces.”
What this means is that due to multiple sources, pricing or backorders, substitution of tools, toolholders and inserts are a frequent occurrence. Tool assembly dimensions are not tightly controlled as on-machine probes and presetting machines connected to the CNC control allow tool length or diameter variations to be automatically compensated. Therefore, tool assemblies become frequently ad-hoc, with varying individual components and/or dimensions. Though similar, slight changes in design, dimensions or geometry will create a frequency change at the tool point. Different toolholders have different stiffness and damping properties, as do machine tools and their spindles. Workpiece materials have different properties that impact tool point behavior. Due to breakdowns or bottlenecks, jobs, part programs and tooling are moved from one machine to another. Any of these changes will result is a change in the tool point dynamics and in the stable speeds or “sweet spots” for that particular application. The process moves from stable to unstable and chatter occurs. Trial and error tweaking at the CNC control, as described above, injects variation into the performance of the operation and the consumption rates of the tools fluctuate. As previously stated, there are scientific solutions to this problem. A recent review in the International Journal of Machine Tools & Manufacturer cited 174 published peer-reviewed research papers on the subject of chatter and Machining Dynamics.
Positive impacts to the supply channel using the science of Machining Dynamics include:
Lock-in Business – With Machining Dynamics analysis, tool performance can be maximized, tool life extended (since all teeth will be cutting equally) and total costs dropped, thus erecting an enormous barrier to competition.
Vending Machines – By using Machining Dynamics analysis, predictable cutter/insert consumption can be realized, reducing the size and cost of safety stocks while minimizing the risk of production stopping stock-outs and emergency deliveries. Machining Dynamics is an ideal pairing with tool vending.
Tool Trials – Machining Dynamics analysis eliminates the need for trial and error tool testing. Current methods of introducing new products require the customer to take their machine out of production and provide no guarantee of improved performance. A day or more of an application engineer’s time is also wasted on failed trials. Even if you win, significant costs have to be recovered before the new order is profitable. A quick (>3 minute) test will yield the optimized potential for the new tool and/or toolholder in that machine and in that application. Results will be known without making a single cut. If you cannot win, you can change the tool configuration to one that will.
Resharpening - Tool resharpening is a favorite cost saving measure, but because of the aforementioned science of Machining Dynamics, the change in dimensions from the subtractive grinding of the cutting tool edges to restore sharpness will change the tool point frequency and may move the process from stable to unstable. Often resharpened cutters are automatically operated at far slower speeds than new thus lowering productivity. Utilizing Machining Dynamics analysis, loss of performance can be minimized or a strategy to use only new cutters justified.
Tool Substitution – Sometimes the desired cutting tool is not available. Replacement tools often result in compromised performance, requiring significant manual adjustments at the CNC control, resulting in lost production and slower cycle times. The substitute tool can be measured with a Machining Dynamics test and optimal parameters calculated, minimizing any loss of production and downtime.
Mandated Cost Reduction – Instead of relying on pricing concessions from suppliers or reduced margins to meet required cost reduction targets, improved throughput can be achieved through Machining Dynamics analysis. Substantial hard and soft cost savings can be quantified and validated.
Gain Sharing – Significant performance improvements are not only attainable, but can be accurately predicted with quick and non-invasive Machining Dynamics tests. Terms where the financial gain from the improved output is shared can be negotiated with minimal risk to the supplier and to the customer. “Big Bites” in productivity are realized immediately, with on-going, science-based “kaizen” or continuous improvement.
Six Sigma, Lean and Green – Machining Dynamics analysis eliminates variation in tooling performance. It also reduces waste from downtime, scrap, secondary finishing, trial and error testing or tweaking and premature tool wear. More efficient tool point behavior also consumes considerably less energy.
SOURCES: 2010 Profit Report – Industrial Supply Association, Dormer/Sandvik D.World n.01-2009, http://en.wikipedia.org/wiki/Speeds_and_feeds, page last modified on 31 March 2011 at 05:43, Frost & Sullivan World Machine Tool-Cutting Tool Market Report - 2004, MSC 2010 Annual Report, Chatter in Machining Processes: A Review by Guillem Quintana and Joseph Ciurana, International Journal of Machine Tools & Manufacturer 51
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