WO2007031138A1 - Procede et dispositif permettant de prevoir la fiabilite - Google Patents

Procede et dispositif permettant de prevoir la fiabilite Download PDF

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Publication number
WO2007031138A1
WO2007031138A1 PCT/EP2006/006906 EP2006006906W WO2007031138A1 WO 2007031138 A1 WO2007031138 A1 WO 2007031138A1 EP 2006006906 W EP2006006906 W EP 2006006906W WO 2007031138 A1 WO2007031138 A1 WO 2007031138A1
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WIPO (PCT)
Prior art keywords
load
time
product
test
errors
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PCT/EP2006/006906
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German (de)
English (en)
Inventor
Harald Ihle
Peter Lindenlaub
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Daimler Ag
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Publication of WO2007031138A1 publication Critical patent/WO2007031138A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M99/00—Subject matter not provided for in other groups of this subclass
    • G01M99/007—Subject matter not provided for in other groups of this subclass by applying a load, e.g. for resistance or wear testing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"

Definitions

  • the invention relates to a method and a device for predicting the reliability of a technical product.
  • Reliability means an average number of errors related to a load on the product during its use.
  • a method with the features of the preamble of claim 1 is known from WO 2005/033649 Al.
  • a component is subjected to a trial.
  • the test is carried out according to a predetermined test program.
  • This experimental program determines the sequence and duration of each experiment.
  • individual tests are carried out as time-tapping experiments, so that the respective specified test duration corresponds to a longer service life of the component. It is calculated which reliability for the component is detectable due to the predetermined experiment.
  • K. Denkmayr "The AVL Reliability Engineering Process for Motor and Drive Train Development", VDI Report 1713, 2002, p. 27 - 32, K. Denkmayr et al .: "The Load Matrix - The Key to the" Intelligent “Endurance Run, Motortechnische Zeitschrift (MTZ), Issue 11/2003, S. 924 - 928,
  • No. 6,502,018 B1 describes how a model is set up that describes the behavior of a technical product (there: a locomotive) with a sensor.
  • the model is calibrated in a trial using sensor data.
  • the calibrated model is used to monitor the technical system.
  • the invention has for its object to provide a method having the features of the preamble of claim 1 and an apparatus having the features of the preamble of claims 14 and 15, which allow early prediction of reliability.
  • the method predicts as the reliability an average number of errors related to a load of the product during its use.
  • the product is subjected to stress in at least one trial. This trial extends over a given period of time. A quotient of the number of errors related to the load during the test and the number of errors related to the load during use is determined.
  • a first and a second time of the time period are specified, wherein the second time is after the first time.
  • Measured as an actual load is a measure of the load that the product is exposed to during the test until the first time point. Furthermore, it is counted how many errors occurred in the experiment until the first time.
  • a target load a measure is given as to which load the product will be exposed to during the test between the first time and the second time.
  • An expected number of errors between the first and the second time is given or predicted in dependence on the target load.
  • Reliability is determined using the actual load, the counted number of errors up to the first time, the target load, the expected number of errors between the first and second times, and the quotient predicted.
  • the method predicts the reliability using a measured actual load as well as a counted number of actually occurred errors.
  • the invention shows a way to systematically calculate the predicted reliability.
  • the prediction of the reliability includes actual values which were measured up to the first point in time, and not just plan values which are determined before the start of the experiment.
  • the method according to the invention makes it possible to reschedule the continuation of the experiment after the first time, if necessary, e.g. For example, by supplementing the experiment with additional individual experiments.
  • the method according to the invention provides a reliability characteristic already at the first time and not only after the end of the experiment.
  • this reliability characteristic does not refer to the first time but to a future second time.
  • the first time method using the previous trial history predicts the future reliability at the second time.
  • the method according to the invention can be carried out at any desired first time and provides a prediction for any second time.
  • the procedure shows a systematic way to decide at first whether the further trial program can continue until the second time as planned or whether rescheduling is required at first.
  • Redesigning may be required, in particular, if the method predicts a reliability that is less than a predetermined target reliability at the first time.
  • the continuation of the present until the first time make measurements dependent.
  • Such a rescheduling can consist, for example, of the fact that at the first time the test program is modified so that the product is subjected to a higher load than originally planned until the second time point.
  • the method provides a prediction of reliability that will be detectable at the second time. This forecast is valid at least if the test program is carried out until the second time as planned at the first time. The method thus makes it possible to avoid "over-testing" in which the product is tested more than necessary.
  • the quotient between the number of errors related to the load during the test and the number of errors related to the load during use is preferably in the form of a convolution factor.
  • a convolution factor - or another form of connection - makes it possible to interpret the individual experiments as time-consuming experiments. This saves time and makes it possible to predict reliability earlier.
  • the design with the quotient makes it possible to use a different measure of the load in the experiment than the load measure to which the reliability is related.
  • the Raffungsmine then has a dimension, z. For example, 1000 kilometers per vibration cycle.
  • the quotient is determined empirically in two preliminary experiments. This approach of finding the quotient saves the need to set up and validate an analytical model of the loads in the experiment and in use.
  • the method can also be used, conversely, to specify a value for the reliability and, at the first time, to determine whether, if so, and if so, at what second time, this predefined reliability value is predicted.
  • the method can also be used to back off when the trial should have begun in order to predict a desired demonstrable reliability.
  • FIG. 1 shows an exemplary load-time function for a component
  • Fig. 3. the time course of the detectable error rate before the start of the experiment according to the planning of Fig. 2;
  • FIG. 4 shows the time profile of the accumulated equivalent travel distance according to a modified planning, the first time being in August 2005, as well as dashed lines showing the time course of the equivalent distance of FIG. 2;
  • FIG. 5 shows the time course of the detectable error rate according to the equivalent distance of FIG. 4;
  • FIG. 6 shows the time course of the actual and planned equivalent journey according to an alternative modified planning, the first time being in August 2005;
  • FIG. 7 shows the time profile of the detectable error rate according to the time course of the equivalent travel distance of FIG. 6;
  • FIG. 8 shows the time profile of the accumulated equivalent travel distance according to the planning of FIG. 6 and, for comparison purposes, the time curve of the equivalent travel distance of FIG. 4 with the first time in November 2005;
  • the term "error” is understood as meaning a deviation of the behavior of a component from the required behavior According to DIN EN ISO 8402, a viewing unit has an error if one of the quality features of the viewing unit assumes an undesired value.
  • a “degradation" of a component is understood to mean a deviation of a quality value from a desired value or desired range.
  • the degradation may be a physical and / or chemical change of the component. If the degradation of a component has progressed so far that the component does not fulfill its required function at all or only to a limited extent and / or provides cause for a complaint, then there is an error
  • the use of a component can cause its surface to corrode, which is a degradation. If the corrosion layer is thicker than a predefined threshold value and / or the corroded area is larger than a predetermined barrier, then the component has an error.
  • the method is used in each case once for different components of a truck. At least one fault type can occur on each of these components. It is possible that different types of errors occur on the same component.
  • relevant component-fault type combinations are selected.
  • an FMEA is used to determine in advance which component-fault-type combinations are relevant and therefore to be taken into account.
  • Such FMEA is z. B. from WO 2005/033649 Al and DE 19713917 Al known.
  • the process is then executed once for each selected component-fault type combination. It is possible to generate different predictions for different component-error type combinations.
  • the method In order to apply the method to a selected component-defect-type combination, several components are tested in the actual experiment. For example, several identical components are tested. The experiment is carried out over a longer period of time. The experiment includes n individual experiments in which each one of the same components is tested. In some of these n individual tests, one copy of the component is installed in each truck. These trucks with the built-in components are driven over longer journeys in the test and / or subjected to extensive stress on test benches. In other individual tests copies of the components in test benches are subjected to the loads which are similar to the loads during the journey. This z. B. components installed in a trial. The surface of the silencer body component can corrode, which is a degradation of the component, which can lead to the failure of the silencer body visibly corroded.
  • Fig. 1 shows an example of a stress-time function for a muffler. The time is plotted on the x-axis, and on the y-axis a time-varying vibration acceleration in [g].
  • Test runs with n4 components are carried out in a test set-up. In this case, several thousand load changes are carried out for two months each.
  • test stands and test drives are carried out in a very humid environment, eg a climatic change chamber.
  • loads are simulated.
  • a simulation model is used, which simulates the loaded component on a data processing system.
  • the simulation simulates which degradations trigger these loads. Errors are counted by evaluating simulation results.
  • the values measured during the test or computed in the simulations are used to predict values for the reliability of a selected component-fault type combination during productive use. Each prediction thus refers to a component and a type of error.
  • the reliability is related to a measure of the load to which the component is exposed.
  • a measure of the load on the component in this example, both during the tests and during its use, the route in km traveled by a truck with the component is used. Instead of the route can also be z.
  • B. use the hours of operation or the number of load changes as a measure of the load.
  • the experiment is preferably carried out as a time-trial experiment.
  • the trucks are driven over rough terrain with many uneven bumps causing vibrations.
  • the trucks are predominantly on flat stretches, z. B. removed roads, driven. Therefore, in at least two preliminary experiments, a gathering factor r is determined.
  • This refraction factor r is then used in the actual experiment.
  • This refractive factor r generally varies from component-fault type combination to component-fault type combination.
  • the rapping factor r refers to a type of test and may vary from one type of trial to another.
  • the rapping factor r has the following meaning: A degradation of the component due to a load of x km in the test corresponds to a degradation by a distance of r * x km during later use , To put it simply: x km of the test load as much as r * x km during later use.
  • the product r * x km is referred to below as the equivalent route.
  • At least one parameter for the load to which the component is exposed in the actual test and during use is specified or determined.
  • This load characteristic may be the above-introduced measure of the load to which the reliability relates.
  • the Load characteristic as well as the load measure the distance traveled.
  • the load characteristic is a parameter which is more correlated with the degradation and thus the error frequency and is harder to measure than the load measurement.
  • the load characteristic is the number of operations that trigger the degradation.
  • the load characteristic characterizes the driveway, z. B. a straight ahead on a developed road, an uphill on a developed road or drive on a dirt road.
  • Two other examples of the load characteristic are the engine speed of the truck and the relative humidity around the muffler.
  • the component is part of the engine or, for other reasons, is exposed to the speed-dependent vibrations of the engine and the air humidity. It is possible to specify several load characteristics, z. B. engine speed and distance.
  • the range of values of the at least one load characteristic is subdivided into k subregions Tb_l,..., Tb_k.
  • z. B the residence time in the climate change chamber, the route or the travel time.
  • a proportion of n_5 (1) of 23% means that the load parameter in the first preliminary test was over 23% of the total travel distance or travel time in the partial area Tb_5. For example, the relative humidity over 23% of the journey in the Tb_5 range was between 80% and 90%. Thus becomes a stress collective determined, to which the components are subjected in the first pre-trial.
  • n_p, q (l) is measured corresponding to which the first load parameter Kg_a has a value in the partial range Tb_p (a) and the second load parameter Kg_b has a value in the partial range Tb_q (b).
  • a parameter for the degradation of the component is specified or determined.
  • the wear that occurs on the component due to the load, or the voltage occurring on the component are examples of this characteristic.
  • d_5 is the average corrosion of a given component at a relative humidity of between 80% and 90%.
  • the corresponding measurements and / or calculations for the same degradation parameter, the same at least one stress parameter and the same reference are performed in a second pretrial experiment.
  • the component is subjected to stress during use.
  • the truck is driven over a much longer travel distance or travel time in high engine speeds than in use and also in the second preliminary test. Try or stay exposed to high humidity for a significantly longer time.
  • the degradation D1 in the first preliminary test is preferably calculated according to the following calculation rule:
  • the degradation D2 in the second preliminary test is preferably calculated according to the following calculation rule:
  • the gathering factor r is then calculated according to the calculation rule
  • the reliability of a component relative to a type of error is indicated by means of the error rate.
  • This error rate is limited to a given observation period, eg.
  • a defect rate of 100 ppm per year means that, on average, 100 out of every 1 million identical components that are used at the same time are used, for example one year, and in faulty components per one million parts per million (ppm) are within one year, an error of the type of error occurs.
  • the error rate is related to the distance traveled until an error occurs on average as follows: dist a
  • dist_a is the average distance traveled in [km] traveled by a lorry over a period of 1 year and MTTF (mean time to failures) is the mean distance traveled in [km] until the occurrence of an error
  • MTTF depends on the component Error type combination, therefore, the designation MTTF [J] is used for the MTTF value of the jth combination.
  • a first quantity indicative of the load of the product during its use and a second size indicative of the load of the product during the trial are used.
  • the first size used is the distance traveled during use in [km]. This route is in the use of the component, the route that covers the truck with the component.
  • the second size used in this example in most of the individual tests is the route, which, depending on the design of the individual test, covers the truck or which is simulated on the test bench or in the simulation. In some individual tests, the number of load changes is used as second size.
  • the gathering factor in this embodiment is the quotient of the load during the test, characterized by the second size, and the load during use, characterized by the first size.
  • the following factors are calculated for the component-error type combination "muffler causes noise":
  • the total load in the experiment therefore corresponds to an equivalent distance dist_ges a [j] ( ⁇ ) until the time ⁇ during the use of the component of the jth combination.
  • the first variable for example, the number of events that occurred during use of the component, which cause a degradation of the component and which can therefore cause a fault of the type of fault, can be used instead of the travel distance.
  • Such events are z.
  • the second size can be used according to the number of events in the actual experiment.
  • the method is repeatedly used in the exemplary embodiment for each component-error type combination.
  • Each application takes place at a first time ⁇ l.
  • This time ⁇ l acts as the first time of the claims.
  • the tested components were exposed to a total load equivalent to an equivalent travel distance of dist_ges_a [j] ( ⁇ l) until time ⁇ l.
  • the first time ⁇ l is, for example, in the first half of the period over which the experiment extends.
  • f_ges [j] ( ⁇ 2; ⁇ l) is meant the total number of all errors of the type of error of the jth combination expected according to a prediction in the period from ⁇ l to ⁇ 2.
  • the increase in the degradation of the component in the period between .tau.l and .tau.2 is first predicted.
  • This planned load in this example depends on the equivalent distance traveled or another load factor. Parameter. Depending on this degradation increase, it is predicted how many errors will occur in the period between ⁇ l and ⁇ 2.
  • models are preferably used. The first model describes the connection between the load and the degradation, the second model the relationship between the occurrence of errors and the degradation.
  • a prediction value for the reliability which is achieved when the test is continued up to several second times is calculated.
  • ⁇ 2 be such a time.
  • dist [i, j] ( ⁇ 2) dist_plan [i, j] ( ⁇ 2; ⁇ l) + dist [i, j] ( ⁇ l)
  • dist_a [i, j] ( ⁇ 2) dist_plan_a [i, j] ( ⁇ 2; ⁇ l) + dist_a [i, j] ( ⁇ l)
  • the equivalent route, which is planned from the beginning to the completion of the ith A single test should be completed in order to test the final combination is called dist_plan_ä [i, j].
  • the barrier ⁇ is now for example 0.1. The case distinction ensures a stable prognosis even in the case that only a few percent of the i-th individual experiment was completed.
  • dist_plan [i, j] ( ⁇ 2; ⁇ l)
  • the actual travel distance in the ith attempt is called the jth combination.
  • dist_ges_ä [j] ( ⁇ 2) dist_ges_ä [j] ( ⁇ l) + dist_plan_ges_ä [j] ( ⁇ 2; tL)
  • the error behavior of a component is preferably described statistically by a parametric error occurrence model, for example by a Weibull distribution.
  • the Weibull distribution was first presented in W. Weibull: "A Statistical Distribution of Wide Applicability," J. Appl. Mechanics, Vol. 18 (1951), pp. 293-297 is described in detail in RA Abernethy: The New Weibull Handbook, 4th ed., 2000.
  • a time constant error rate ⁇ [j] is assumed for the jth combination and the exponential distribution is used as the error occurrence model.
  • a time-dependent estimated value MTTF '[j] ( ⁇ 2; ⁇ l) for the parameter MTTF [J] is then calculated according to the calculation rule dist _ ges _ ä [j] ⁇ ⁇ ) + dist _ plan _ ges _ ä [j] ( ⁇ 2; ⁇ l)
  • MTTF '[j] ( ⁇ 2; ⁇ ⁇ ) f__ges [j] ( ⁇ l) + f_ges [j] ( ⁇ 2; ⁇ l) + ⁇ .
  • f_ges [j] ( ⁇ l) is the total number of all the errors of the j-th component-error-type combination that have occurred in all trials up to the time ⁇ l.
  • f_ges [j] ( ⁇ 2; ⁇ l) the total number of all errors of the j-th combination that will occur according to the prediction in the period from ⁇ l to ⁇ 2 is designated.
  • the denominator can never be zero.
  • an estimate ⁇ '[j] ( ⁇ 2; ⁇ l) which depends on the two times ⁇ 1 and ⁇ 2 is calculated, in accordance with the calculation rule
  • the reliability is predicted using the distribution function F (t).
  • F (t) the distribution function
  • a failure probability U [j] U [j] ( ⁇ 2; dist_a, ⁇ l) is predicted according to the calculation rule
  • this method is performed once for each of the m component-error type combinations.
  • These m predictions can be compared.
  • it can be found out at the time ⁇ 1 which component-error-type combination at the time ⁇ 2 will have a low predicted reliability.
  • a maximum error probability ⁇ which lies between 0 and 1 and therefore between 0% and 100%, specified. Common values for ⁇ are 0.1 or 0.05 or 0.01, ie 10%, 5% or 1%.
  • the confidence level 1- ⁇ denotes the statistical reliability with which the reliability is predicted.
  • Exponential distribution is used as the error occurrence model.
  • ⁇ 1 is assumed.
  • MTTF '/ / (f 2- a ⁇ l) diSt - geS - d ⁇ ' K ⁇ l ) + dist - plan - ges - d ⁇ ' K r2> rl )
  • MTTF '[j] ( ⁇ 2; ⁇ ⁇ ) f_ges [j] ( ⁇ l) + f_ges [j] ( ⁇ 2; ⁇ ⁇ ).
  • an estimated value ⁇ '[j] ( ⁇ 2; ⁇ l) for the time constant error rate ⁇ [j] is calculated therefrom.
  • an estimate of the achievable reliability is determined.
  • a Weibull distribution is used instead of the exponential distribution.
  • the shape parameter ⁇ is assumed to be known. The following calculation rules use the individual equivalent routes of the n individual tests.
  • a lower limit MTTF '[j] ( ⁇ , ⁇ 2, ⁇ 1) for the MTTF value MTTF [J] is calculated according to the calculation rule
  • a required reliability must be demonstrated for each of the m component-fault-type combinations. This reliability must be proven in the form of a required maximum error rate.
  • the required maximum error rate in this example is 150,000 ppm per year for the combination "muffler housing visibly corroded.” For example, with 1 million muffler housings per year, a maximum of 150,000 housings per year may be visibly corroded per year.
  • the required reliability values as well as the reliability values predicted in FIGS. 2 to 9 are purely hypothetical values, which serve exclusively to illustrate the exemplary embodiment. Actual ppm setpoints and proven ppm actual values are orders of magnitude below these hypothetical values.
  • the second times ⁇ 2 are respectively entered.
  • the respective first time ⁇ l is indicated by an arrow.
  • the trial will begin in February 2005.
  • the plan is to complete the trial in December 2006.
  • the total accumulated equivalent travel distance dist_ges_a [j] ( ⁇ 2) is plotted in [km] indicating the total trucks in the trial until the respective second time ⁇ 2 have completed or will cover according to the plan.
  • a plan before the start of the experiment is illustrated.
  • the first time ⁇ l is so z.
  • the diagram of FIG. 2 shows the respectively planned equivalent travel distance dist_ges_a [j] ( ⁇ 2) up to the respective instant ⁇ 2.
  • U U [j] ( ⁇ 2; dist_a, ⁇ l) for the jth combination at the respective time.
  • FIGS. 4 and 5 illustrate the changed planning and a result of this changed planning.
  • the first time ⁇ l is now after the beginning of the experiments, z.
  • the first time ⁇ l is now after the beginning of the experiments, z.
  • the first time ⁇ l is now after the beginning of the experiments, z.
  • z For example, in August 2005. Up to this time, no errors were measured in the trial. 4 shows the time course of the accumulated equivalent travel route. Until the first time in August 2005, this is the actual equivalent distance (product of the actual distance to the first time and the factor of refraction), then the planned equivalent distance.
  • the originally planned time profile of the accumulated equivalent travel distance which has already been shown in FIG. 2, is shown in dashed lines in FIG. 4.
  • 5 shows the time profile of the predicted error rate.
  • the measurement result is used that no error of the type of fault has occurred up to the first time.
  • the time curve of the error rate predicted in accordance with the original planning which was already shown in FIG. 3, is shown in das
  • FIGS. 6 and 7 show an alternative continuation of the experiment. Also in this example, the first time after the beginning of the experiments, z. For example, in August 2005. Up to this time, no error type errors were measured in the trial. However, a smaller overall journey was actually covered by the first time than originally planned. This also reduces the equivalent distance.
  • FIG. 6 shows the time profile of the equivalent travel route according to the alternative course. Until the first time in August 2005, this is the actual equivalent distance (product of the actual distance to the first time and the factor of refraction), then the planned equivalent distance.
  • the originally planned time course of the equivalent travel route which has already been shown in FIG. 2, is shown in dashed lines in FIG.
  • Fig. 7 shows the time course of the predicted error rate.
  • the measurement result is used that no error of the type of fault has occurred up to the first time.
  • the time curve of the error rate predicted in accordance with the original planning which has already been shown in FIG. 3, is shown in dashed lines in FIG.
  • FIG. 8 shows the time course of the equivalent distance according to the alternative planning of FIG. 6.
  • the first time is at the end of November 2005.
  • the equivalent distance is shown in FIG the actual equivalent distance (product of the actual distance to the first time and the factor of refraction), then the planned equivalent distance.
  • the equivalent route of Fig. 4 was shown in dashed lines.
  • FIG. 9 shows the detectable error rate predicted in the experiment of FIG. 8.
  • two errors were counted before the first time in November 2005.
  • the predicted error rate deteriorates significantly.
  • the course of the detectable error rate of Fig. 5 is shown in dashed lines in Fig. 9.

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Abstract

L'invention concerne un procédé et un dispositif permettant de prévoir la fiabilité d'un produit. Le produit est soumis, au cours d'au moins un essai, à une contrainte. Une relation entre la contrainte au cours de l'essai et la contrainte lors de l'utilisation ultérieure est déterminée. On mesure, en tant que contrainte réelle, une grandeur correspondant à la contrainte à laquelle le produit est exposé pendant l'essai jusqu'à un premier temps déterminé. On détermine le nombre d'erreurs apparues jusqu'à ce premier temps. On détermine comme contrainte de consigne, une grandeur correspondant à la contrainte à laquelle le produit sera exposé, pendant l'essai, entre le premier temps et un second temps donné ultérieur. La fiabilité est prévue avec utilisation de la contrainte réelle, du nombre d'erreurs déterminé jusqu'au premier temps, de la contrainte de consigne, du nombre d'erreurs attendues entre le premier et le second temps et de la relation.
PCT/EP2006/006906 2005-09-13 2006-07-14 Procede et dispositif permettant de prevoir la fiabilite WO2007031138A1 (fr)

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