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What VLM Can Do VEXTEC’s patented Virtual Life Management system simulates the true degradation physics of materials at the microstructural level. The VLM system uses that data to predict – with an extraordinarily high degree of accuracy – the life cycle of a particular component made from that material. The system can also combine that information with data from all the other components in a product to predict that product’s overall reliability. As a result, VEXTEC is the only company that can rapidly and accurately predict product life cycle behavior – even before that product is ever built. With the Virtual Life Management system, for the first time, you can run your business with complete, accurate visibility. There is nothing more valuable because this information has profound economic consequences for every aspect of your business. Traditionally, companies made estimates of future product behavior by looking at historical data. Warranty terms and costs, maintenance schedules, product performance, etc., were all determined by what happened in the past. Unfortunately, this information has very little, if any, bearing on what’s going to happen in the future. Using historical data to make predictions about the future like driving down the highway looking only in the rear view mirror. You know where you’ve been. But you have no idea see where you’re going. VEXTEC changes that, forever. Because everything you’re doing can be done better with Virtual Life Management from VEXTEC. The story of the fleet’s life cycle is told by simulating the individual systems – each made up of individual components working in combination. Overall system failure is nothing more than the failure of any one of a critical number of parts. VEXTEC can determine the behavior and life cycle of any part, and from that, predict system and fleet performance.
VEXTEC requires very little data to produce highly accurate results. Here’s an example of a fleet analysis made with just a handful of customer usage data points. This VLM simulation quantifies how the true physics-based relationships of material, design and customers usage directly affect fleet performance. The fleet represented by this figure contains a mix of high and low daily users. The figure shows a clear difference between weighting the average fleet daily usage as high over low, because as the 3-D figure shows, at a specific threshold speed, warranty failure and cost significantly accelerate. Again, VLM quantifies this so the OEM can decide what modifications to make—whether different price points should be used for the various fleet customers, design changes should be initiated, or performance restrictions should be imposed. This kind of information never existed before—unless it was after the fact. No one even thought to ask the questions this data answers, because it was simply impossible to provide. But VEXTEC’s Virtual Life Management system changes that. In fact, armed with this data, and the simulation it’s based on, VEXTEC customers not only know how their products are going to behave in the field, they can also make “what if” adjustments to the simulation to see how different usage patterns, warranty terms, and performance affect their bottom line.
Maintenance & Logistics Forecasting
Virtual Life Management can help you predict and cut your warranty costs, create a more efficient maintenance schedule, and more. Having the information you need about how your products are going to behave in the field can profoundly affect how you schedule and pay for maintenance. Virtual Life Management simulations can tell you—with a very high degree of accuracy—which parts are going to break down and when. Armed with that information, you can build maintenance schedules around what you know is going to happen, rather than what happened 12 months ago, or what your best guess might be.
In this example, a VLM simulation predicts how the relationships between failure (and cost) and customer usage change over time. Here, VLM was used to predict usage patterns and their associated costs two years into the future. The simulation shows that although low volume customers are not a significant failure concern in 2007, the second figure shows they become a concern two years from now regardless of average operating speed. Given the OEM knows who these low volume usage customers are, they can plan for how many spare parts will be needed, when, as well as the required maintenance resources. These aren’t back-of-the-envelope estimates based on historic maintenance statistics. They are accurate forecasts of the future based on the exact physical relationships between the varied stresses of customer usage and the product’s makeup.
When your sales strategy requires you offer extended warranty period coverage, do you really know the extent of the financial obligation you’re incurring? Do you really know the warranty costs associated with a new product? And, what would it be worth to you to have those answers, and many more like them, beforehand, rather than having to explain those unexpected costs to your shareholders in your 10K filings? With VEXTEC’s Virtual Life Management system, an accurate indication of warranty obligation can be determined before the first product is ever sold. VLM can simulate the actual physics behind the failures of individual products for each alternative warranty period under consideration. Obligating yourself to more warranty payouts through an extended warranty coverage period can be a sound strategic decision, as long as you know your pricing or increased sales volume will more than make up for it. But don’t guess at the numbers using some contrived formula built purely on the statistics of the past. If the physical relationships that are going into the future product are different from those products of the past (which is almost always the case) then that contrived formula will be little better than guesswork disguised as “strategy.” Here’s a real life example: The sales team at a major OEM made a decision to increase the warranty coverage on a manufactured product. The decision helped to sell more product, but bottom-line results kept diminishing. The VLM simulation explained why. The results showed that for some customers, the impact of doubling the warranty coverage period was basically nil, and if the bulk of the customer base could be shown to exhibit that usage pattern, then the warranty coverage increase would be economically viable.
But in this case the OEM had a disproportionately large number of specialized customers. For those customers, the simulation showed that a warranty cost extension would almost double the payout obligation. These kinds of major bottom-line decisions don’t have to be made in the dark. Now with VLM, you can have the facts, and armed with those facts, every decision can turn out to be a good one.
Trade Study Problem Mitigation
Employing Virtual Life Management not only identifies problems BEFORE they happen, it also gives you the information you need to fix them. Once a product simulation is constructed, any number of business decisions or product engineering and manufacturing trade studies can be quickly produced. As this real life example below shows, the proper “fix” might come from any number of different functions within your organization. In this case the OEM had a product fleet of several thousand individual units. Although the initial sales profit number looked fantastic, the VLM simulation forecasted a more than 30% reduction in net profit due to high warranty payouts during the coverage period. VLM showed how the warranty impact could be almost cut in half by addressing the problem from either the business strategy or product engineering. The business strategy fix entailed changing the warranty coverage policy by lowering the [AP1]warranty offering price and tightening the limitations on policy coverage. The engineering fix turned out to be a relatively simple design change which reduced the stress imposed on the product during customer usage.
Physical testing has been the traditional means for ascertaining durability before product launch. But it has never been economically feasible nor practical to test every single part to gain a true insight for the durability of the product. Instead, the protocol has been to pick some hopefully representative samples, run as many tests as the time and cost allow, and basically hope for the best. At best, physical testing is and always will be inconclusive because only a few parameters can be examined (illustrated by the red circle in the figure), within a practical budget and timeframe. But that was then.
Even with all its limitations, physical testing becomes more and more expensive, while computer processing costs continue to decrease. But even though it makes good business sense to replace the total dependence on the former with some reliance on the later purely on the basis of the cost comparison between the two methods, that still doesn’t take into account the flexibility and the depth of information computer simulation can provide. By comparison, instead of isolating a few risk factors and testing for those, VLM addresses Full Spectrum Variability™ (FSV) by predicting the impact of ALL the factors that determine the fleet durability of your product. These factors include variability introduced by three broad factors: 1) your materials in their design configuration, 2) the way all your different customers use the product, 3) business factors including pricing, costs, and logistics. By measuring all these factors and calculating their relative impact, VEXTEC can provide you with a complete picture of your product’s life cycle, before the product is ever made.
Virtual Life Management analysis allows you to get answers to questions you were never even able to ask before. For instance, the accompanying chart shows how VLM simulations allowed a manufacturer to compare different total cost of ownership (TCO) scenarios by comparing the product offerings of two different suppliers. The results were surprising, and financially rewarding. Suppliers A and B each supply a Component X to an existing fleet. There’s a huge differential in the cost of the two components, but there’s also a big difference in the quality of the two parts. The component from Supplier A lasts more than twice as long. Even so, the predicted fleet cost in this scenario is $150 million, quite a bit more than the lowest cost supplier is able to provide. And, in the absence of any other information, most purchasing departments would make the obvious choice.
But let’s say your purchasing department has access to warranty cost information based on a VEXTEC simulation that models the aftermarket costs associated with both supplier’s parts. Once again, the results are clear, but the choice is just the opposite. Because instead of awarding the contract purely on the basis of price, your purchasing department can award it based on warranty savings. In which case, you could put $22 million right on the bottom line.
By the way, this example isn’t something we just made up. This is data from a real life deployment, with real life results.
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