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Robust Optimal Design of Multi-Body Systems
Abstract
Techniques in robust optimal design of multi-body systems are presented.In order to define the concept of robust optimal design, a performancevariance minimization method is applied on variations of designvariables. The regression model is estimated through a response surfacemethodology to evaluate the performance variance of multi-body systems.The experiments necessary for the response surface methodology are notconducted through physical tests but through nonlinear multi-bodydynamic simulation. The techniques presented are applied to arotary-type compressor in order to apply them to the robust optimaldesign of a weight balancer for use in vibration control and to show theeffectiveness of the techniques.
... Later, there is an attention of many researchers to synthesize the six-bar steering linkages, which can satisfy the Ackermann principal for some orientations. Optimization of steering error between actual steering linkage with rack-and-pinion and Ackermann principal has been studied by many researchers [2][3][4][5][6][7][8]. From my review of literatures found that the optimization problems have been only studied to minimize the steering error [2][3][4][5][6][7][8][9] and link-length sensitivity [1,7] with or without the normalized link length variables. ...
... Optimization of steering error between actual steering linkage with rack-and-pinion and Ackermann principal has been studied by many researchers [2][3][4][5][6][7][8]. From my review of literatures found that the optimization problems have been only studied to minimize the steering error [2][3][4][5][6][7][8][9] and link-length sensitivity [1,7] with or without the normalized link length variables. The most optimization problems are a single objective, except the work by Hanzaki et al. [1], they used weight sum to combine sensitivities to be an objective. ...
... Optimization of steering error between actual steering linkage with rack-and-pinion and Ackermann principal has been studied by many researchers [2][3][4][5][6][7][8]. From my review of literatures found that the optimization problems have been only studied to minimize the steering error [2][3][4][5][6][7][8][9] and link-length sensitivity [1,7] with or without the normalized link length variables. The most optimization problems are a single objective, except the work by Hanzaki et al. [1], they used weight sum to combine sensitivities to be an objective. ...
At the present, human's life needs to have more facilities and safety. In daily life, we regularly use vehicles. When we talk about the safety in driving cars, there is nothing more important than the steering systems, which work properly in order to maintain themselves to be in safety condition. A steering system is the mechanism to control car to the direction that the driver wants. From these reasons, that became the objective of this research that is required to synthesize the steering mechanism, which has minimum steering error against the Ackerman's theory. The optimization problem is a single objective optimization of the steering error. The optimization constraints are assigned that based on the limitations of steering mechanism. The design variables are tie rod (L t), steering arm (L a), and the distance between the front wheel kingpin and rack (H). The optimizer is used to find the optimum result is the optimization toolbox in Matlab, which is called fmincon. The study found that the optimum design variables are L a = 300 mm, L t = 300 mm, and H = 229.3795 mm, which had minimum of the maximum steering error when comparing with Ackerman's theory is 0.0836 ๐. From the steering error is obtained from the designing, it showed that the proposed of designing method is an efficient method to reduce the steering error, which can reduced the skidding and wear of the tires.
... At present, the turning radius is an important characteristic of a steering mechanism because a nimble turn in traffic jam of a small car is one of the most essential characteristics of modern small eco cars. From the literature, it is found that most researchers performed single objective optimization, which has an objective function as a steering error [2,3,5,6,[10][11][12][13][14] and link-length sensitivity [1,2,4,15] while design variables were link lengths with or without normalization. For bi-objective optimization cases, Hanzaki et al. [1] and Shou et al. [13] used a weighted sum method to solve the problem whereas the design objectives are sensitivities [1] and the Ackermann steering error and the change of toe-in angle during wheel jumping [13]. ...
... It is shown in Ref. [22] Algorithm 1. Function evaluation. Input x = {L a , L t , H} T , W t , W b , L r , D Output f 1 , f 2 , constraints 1: If one of the conditions (13)- (15) holds, assign f 1 , f 2 ® ¥. ...
In this paper, multi-objective optimization of a rack-and-pinion steering linkage is proposed. This steering linkage is a common mechanism used in small cars with three advantages as it is simple to construct, economical to manufacture, and compact and easy to operate. In the previous works, many researchers tried to minimize a steering error but minimization of a turning radius is somewhat ignored. As a result, a multi-objective optimization problem is assigned to simultaneously minimize a steering error and a turning radius. The design variables are linkage dimensions. The design problem is solved by the hybrid of multi-objective population-based incremental learning and differential evolution with various constraint handling schemes. The new design strategy leads to effective design of rack-and-pinion steering linkages satisfying both steering error and turning radius criteria.
... Note that the application of the RDO approach requires three main elements such as a formal decision model, the robustness criteria, and scenario planning [65]. Even though the RDO techniques have been further improved during the past decade, while few researches [66,67] were provided for its application on the multi-body dynamic system. More specifically, only aleatory uncertainty were covered. ...
... ß composes of the partial regression coefficients, while ε indicates the random errors. The minimisation of ε yields the ß values, which are given by [25]: ...
An important design challenge of modern vehicles is mass reduction. Hence in many cases, mechanical design of vehicle components covers different optimization processes. One important structural optimization technique which is highly utilised in weight reduction applications is the topology optimization. This paper contains a multi-stage optimization based on the topology and design optimizations. During this study, the mechanical design of a rear axle-chassis connection bracket is achieved. First of all, the design load of the bracket was determined through a multibody dynamics analysis. This load case was determined among various driving conditions and the most critical load case was indicated as the design load of the bracket. This process was executed by using Adams/Car™ software. Subsequently, a design volume for the bracket was decided, which specifies the domain of topology optimization that will be employed later on. The determination of the design domain was made by considering the structural position of the design component, the neighbor components of the rear axle and the chassis. In this manner, the basic shape and dimensions of the bracket were created. The unnecessary volume of the draft design, which is not properly loaded under the design conditions was determined and removed from the design by means of topology optimization. The topology optimization was run in topology optimization module of ANSYS® Workbench 18.2 finite element analysis (FEA) software package. In the light of the primary shape obtained from the topology optimization study, a producible initial design model was built. This model was then subjected to FE analysis under the same circumstances with the draft model, in order to perform strength and deformation assessments of the initial design. Correspondingly, the critical regions were determined where stress concentrations were observed. The model was updated in a way that the stress values were reduced in these regions through the response surface methodology (RSM). The comparisons between the result and the initial geometries reveal that the mass of the connection bracket was reduced by 63%. Besides, the total deformation which was dropped by the design optimization is 13% lower than the initial design that was generated with the influence of topology optimization result.
... Principal target of the response surface experiments is to obtain a proper model to estimate and analyze the relationship between design variables and system response. Regression model for a second order response surface can be expressed in matrix form as [9]: ...
Computer-aided design phases of the steering linkage of a passenger bus are presented. In the first part of the study, proper joint positions of the mechanism which satisfy the kinematic requirements such as, acceptable toe deviation and steering error ranges, were determined. For this purpose, a rigid multibody model of the mechanism was built by taking the physical design restrictions of the front axle into account. Subsequently, a response surface methodology (RSM)-based kinematic optimization study was carried out by using Adams®/Insight software. In order to determine the service forces acting on the structural elements of the linkage, a full multibody dynamics (MBD) model of the bus was also composed. By using this model, standard lane change maneuver was performed. Furthermore, the theoretical steering torque at the tire contact patch, necessary to steer the front wheels of the bus at zero speed, was calculated. Force analysis of the linkage was also performed for this condition. In the second part, mechanical design of the full steering mechanism was carried out for critical design load. Finite element analysis (FEA) was implemented to predict the stress concentration regions of the primary design model for the selected load cases such as zero speed steering, lane change and braking. Design optimization of the linkage components were also carried out by using ANSYS® Workbench™ software. Hence, optimal shapes of the structural elements, which satisfy the design targets such as minimum equivalent stress and maximum stiffness, were determined. According to the results obtained from this study, the steering linkage satisfies the safety condition for critical load cases.
... Principal target of the response surface experiments is to obtain a proper model to estimate and analyze the relationship between design variables and system response. For a second order response surface, regression model can be expressed in matrix form as [8]: ...
Conceptual kinematic design and optimization stages of the multi-axle steering mechanism of an 8x8 special purpose vehicle are summarized. In the first part of the work, pre-kinematic design of the steering mechanism was composed. In the second part, the kinematic model of this mechanism was created by using Adams ® /View multibody systems software. In order to perform the kinematic optimization study, MBS model of the full vehicle was also built. Steering mechanism was optimized in terms of Ackermann error via Adams ® /Insight tool by taking the physical design constraints such as the position of the steerable wheels into account. Optimal hardpoint positions of the swing arm which interconnects the steer axles for simultaneous steering were also determined. In the last part of the study, toe deviation characteristics for steer axles during the wheel travel were obtained. Numerical results showed that it is possible to satisfy the βF ≤ ± 0.5° condition for the Ackermann error in the full steering ranges of the inner wheels of steer axles. None of the internal angles of the mechanism exceeds the value of φi = 165º for this steering condition. Moreover, toe angle deviation of the axles remains below the value of Δβv ± 0.25º for displacement of the wheels of zP = ± 100 mm.
... Principal target of the response surface experiments is to obtain a proper model to estimate and analyse the relationship between design variables and system response. For a second order response surface model, the regression model is defined in general form as [5] ...
In the scope of this work, mechanical design stages and the structural optimisation process of a relay lever that will be used as one of the main load carrying members of a passenger bus multi-link steering system are summarised. In the first stage of the study, design load of the steering mechanism was determined. For this reason, two different methods were used: the bore torque approach and the multibody dynamics (MBD) analysis of the steering mechanism. Therefore, a full-scaled multibody model of the passenger bus was built and analysed for a chosen critical driving manoeuvre via Adams/Car™ module of MSC. Adams™ commercial software package. Primary mechanical design of the part was composed with the use of the load model which gives greater reaction forces. Finite element analysis (FEA) of the draft design was also implemented to determine the possible stress concentrated regions. In order to obtain the appropriate relay lever structure which satisfies minimum stress concentration and minimum deformation under the selected design load, a response surface methodology (RSM)-based optimisation study was also carried out. Results of the optimisation process showed that the final structure of the relay lever satisfies the strength requirements for the chosen critical load case.
... Principal target of the response surface experiments is to obtain a proper model to estimate and analyse the relationship between design variables and system response. For a second order response surface model, the regression model is defined in general form as [19]: ...
A response surface-based design application to obtain an optimum multi-link steering mechanism is presented. Design problem is essentially established on two main goals: minimum deviation of toe angle (βV) during the wheel travel and optimum steering error during the steering angle (βL) range of the wheel. In the first stage, a complete multibody model of the suspension system including the steering mechanism was composed by using MSC.Adams® software. In order to identify the most effective parameters among the tie rod co-ordinates on βV deviation, a Full Factorial Design (FFD)-based Design Sensitivity Analysis (DSA) was carried out via Adams/Insight multi-objective optimisation tool. Central Composite Design (CCD) was also implemented to find out the optimum position of the tie rod. In the final stage, optimum hardpoint positions of the steering mechanism were searched by a combination of sweep study (SS) and CCD to provide the minimum deviation of Ackermann error. The optimisation results show that it is possible to reduce the maximum steering error (MSE) of the system up to 89.6 % in comparison with the parallel arm base mechanism by using the proposed methodology.
... In fact, the concept of robust design is not new in other fields. It is defined as ''The objective of robust optimal design is to optimize the design variables such that the variation in performance, based on the variation of design variables and noise factors, becomes minimal" [5]. ...
... Or ces incertitudes peuventêtreélevées en cas de fortes variabilités de la répartition spatiale de la masse des configurations du système et induire de fortes variabilités sur la réponse dynamique du système multicorps. Un autre pan de recherche relatifà la quantification des incertitudes dans les systèmes multicorps concerne les méthodes de conception robuste où l'accent est mis sur la sensibilité de la réponse du système aux variables de conception (voir par exemple [261,141,214,143,70,211,92,198]). Là encore, ces travaux ne concernent pas les incertitudes relatives aux solides rigides eux-même. ...
Ces travaux de recherche s'intéressent de manière générale à la quantification des incertitudes et à la réduction de modèle pour la modélisation numérique des systèmes dynamiques. Dans une première partie, on s'intéresse à la quantification des incertitudes pour les systèmes multicorps. Pour ce type de système, les incertitudes concernent les paramètres du modèle. Ces incertitudes sont liées soit à une variabilité naturelle, soit à un manque de connaissance sur ces paramètres. On s'intéresse en particulier à la modélisation des incertitudes relatives à la distribution de masse des solides rigides. Afin d'être compatible avec le formalisme de la dynamique des systèmes multicorps, cette modélisation est construite directement au niveau des propriétés globales d'inertie des solides rigides. Dans la partie suivante, on s'intéresse à la modélisation et à l'identification en inverse des incertitudes dans les structures déformables pour lesquelles, en plus des incertitudes sur les paramètres, il existe des incertitudes de modèle induites par les erreurs de modélisation (discrétisation, choix de la loi de comportement, ...). Pour prendre en compte ces deux types d'incertitudes, une approche probabiliste mixte paramétrique/non paramétrique est utilisée. L'accent sera mis sur l'identification des hyper-paramètres du modèle stochastique en utilisant des mesures expérimentales. Le troisième partie de ces travaux présente une nouvelle méthodologie d'analyse dynamique des structures à forte densité modale. Celle-ci est basée sur une séparation global/local de l'espace des déplacements admissibles via la résolution de deux problèmes aux valeurs propres séparés, permettant ainsi de construire un modèle réduit des déplacements globaux de petite dimension puis, si cela est nécessaire, de prendre en compte les contributions locales par une approche probabiliste. Enfin, la quatrième partie de ces travaux concerne cette fois-ci l'aléa du chargement appliqué. On s'intéresse en particulier à la génération d'accélérogrammes pour la construction de chargements sismiques. On présente une nouvelle méthodologie de construction et de génération d'accélérogrammes, en grande dimension stochastique, permettant de prendre en compte des propriétés physiques et des spécifications issues de l'ingénierie sismique directement au niveau de la loi de probabilité du processus stochastique modélisant l'accélérogramme.
... In the context of multibody dynamics, the parametric probabilistic approach of uncertainties consists in modeling the uncertain parameters of the multibody dynamical systems by random variables 1,4,10,12,15,18,19,22 . Therefore, the quantities of interest and the performance function become random variables, and a probabilistic robust design method 3,5,7,9,11,13,14,17,25 has to be used. ...
This research is devoted to the robust design of multibody dynamical systems, that is to say to the optimal design of a multibody system which is carried out using an uncertain computational model. The probabilistic model of uncertainties is constructed using a probabilistic approach yielding a stochastic differential equation with random initial conditions. Then the robust design of the multibody system, in presence of uncertainties, is performed using the least-square method for optimizing the cost function, and the Monte Carlo simulation method as stochastic solver. The application consists in a simple multibody model of an automotive vehicle crossing a rough road and for which the suspensions have to be designed in order to optimize the comfort of the passengers.
... In addition, the sensitivity minimization, which is carried out in this paper as a part of optimization process, is also new in the context of rack-and-pinion steering linkage design. Such minimization of both the objective function and the sensitivity has been considered important in the literature of robust optimal design [6,7]. In summary, the contributions of the paper are A simple generalized methodology for the optimization of a rack-and-pinion linkage for both CTO and STO is proposed. ...
In this paper, the combined kinematic and sensitivity optimization of a rack-and-pinion steering linkage is performed. This steering linkage is the most common steering system used in passenger cars. Although, the steering linkage has received a lot of attention for the minimization of the steering errors, no attempt has been made so far to investigate the sensitivities of optimum dimensions relative to variation of link lengths. The kinematic optimization of the linkage is carried out using three homogenous design parameters. The objective of the proposed optimization is to minimize maximum steering error during cornering. This is followed by a sensitivity analysis to predict how the steering error is affected by manufacturing tolerances, assembly errors, and clearances resulting due to wear. Since the optimized kinematic error is very sensitive to the variations of the linkage parameters, the kinematic and post-optimal sensitivity optimization of the steering linkage is performed in an integrated manner. The methodology proposed in this work helps the designers of rack-and-pinion steering linkage to choose the linkage parameters whose maximum steering error (MSE) and sensitivity are minimum.
... Nowadays an engineer not only has to design a reliable mechanical system, but also predict what kind of faults may appear in a system and what steps should be taken to reduce their influence on performance. There are two methods used to fulfil this demand: robust design [11,15] and implementation of a special system that allows self-repair. In the following chapters the second method will be discussed. ...
This paper presents theoretical background and results of experimental research into fault detection, isolation and restoration (FDIR) system for rotating machineries created in Department of Robotics and Mechatronics, AGH University of Science and Technology in Cracow. The presented FDIR system solution concerns the problem of automatic balancing of rotating systems while in operation. Simulations and experimental results proved that application of the presented solution leads to a reduction in the vibrations caused by imbalance, without hindering service. A mechatronic approach to the design process makes this process more effective.
In the traditional design of a vehicle suspension system, mechanical parameters, such as spring stiffness and tire radial stiffness, are determined before optimizing the coordinates of suspension hard-points based on handling and stability. However, the mechanical parameters of vehicle suspension systems vary with repeated changes in ambient temperature and loading conditions. Consequently, the original hard-point coordinates cannot guarantee satisfactory handling and stability after long-term vehicle use. To address this issue, an A0 class vehicle with a MacPherson suspension was modeled in ADAMS/Car and was validated against the results of field tests. The relationships between the maximum absolute values of front wheel alignment parameters during parallel wheel travel analysis and the coordinates of suspension hard-points, spring stiffness, and tire radial stiffness were determined using support vector regression. Next, a multi-objective optimization function was formulated based on the interval analysis method. Finally, a novel double-loop multi-objective particle swarm optimization algorithm was designed for global optimization of hard-point coordinates. The ADAMS simulation results indicated that, compared with the vehicle with the original hard-point coordinates, the double-loop multi-objective particle swarm optimization algorithm, the traditional multi-objective particle swarm optimization algorithm, and the genetic algorithm can effectively reduce the variation ranges of front wheel alignment parameters, regardless of the values of the mechanical parameters. It also showed that the double-loop multi-objective particle swarm optimization algorithm performs better than the traditional multi-objective particle swarm optimization and the genetic algorithm with both the original and changed mechanical parameters. Except for an increase in the variation range of the caster angle by 9.24–10.69%, the variation ranges of the toe angle, camber angle, and kingpin inclination angle under various mechanical parameters using the double-loop multi-objective particle swarm optimization algorithm were observed to be reduced by 50.45–79.39%, 1.84–4.24%, and 2.11–2.96%, respectively. Last but not least, the proposed double-loop multi-objective particle swarm optimization algorithm provided better handling, stability, and ride comfort values than the traditional multi-objective particle swarm optimization algorithm and the genetic algorithm.
Mechanical design and optimisation processes of an axle beam which is the main load carrying part of the heavy commercial vehicle solid front suspensions are summarised. Firstly, basic dimensions of the beam was determined by taking the design limitations such as chassis height, ground clearance and the load capacity into account. Finite element (FE) analyses were applied to the draft design for selected standard load cases. Maximum stress concentration was detected at the neck region of the beam for cornering and braking manoeuvre. Equivalent stress was decreased at the critical regions of the axle beam with the help of a Design of Experiments (DOE)-based optimisation study. Factor of safety of the optimal design was obtained as 1.5 for cornering and braking condition.
Conceptual kinematic design study of a double wishbone suspension that will be used as the front axle of a 40 metric tonnes capacity articulated heavy commercial vehicle is summarised. Design problem is basically established on two main goals namely, minimum deviations of the wheel track and the camber angle under all drive and load conditions. In the light of the design constraints such as the ground clearance of the tractor, chassis location, structural elements of the wheel-end package and the steel wheel, the possible design volume of the suspension was predicted. Subsequently a primary kinematic model of the suspension was built via Adams/Car™ multibody dynamics (MBD) software and the deviation characteristics of this model were computed in case of wheel jounce and rebound. Targeted optimal ranges of the kinematic parameters during the wheel travel were also obtained by using response surface methodology (RSM). For this purpose, a central composite design (CCD) - based multiobjective optimisation process was performed to the primary model by using Adams/Insight™ tool of MSC.Adams® commercial software. 3D plots of the kinematic parameters including the effects of the wheel travel and wheel steering are presented for primary and optimised designs. Results showed that the optimal geometry of the double wishbone suspension obtained from the multiobjective optimisation study satisfies the track change limitation given in the literature.
Aiming at the electromechanical coupling system dynamics optimization of spindle unit of refitted machine tool for solid rocket, the optimization modeling is presented on the basis of system differential equations. The research job in the paper reveals that the global optimization efficiency can be enhanced greatly, when the weight value of the swarm particle algorithm can be changed with special exponential function. So, a kind of new particle swarm algorithm, Exponential inertia weight Particle Swarm Optimization (EPSO), is formed by adopting exponential inertia weight function. Based on above research job, the optimized design parameters of the spindle unit of refitted machine tool for solid rocket are obtained in limit time period, and the engineering problem of dynamic optimization of electromechanical system is solved successfully by the method of EPSO. The results are the innovative achievements in the field of mechatronics, and have broad application prospects in the design of robots, NC machine, and electromechanical equipments.
A new kind of exponential inertia weight particle swarm algorithm is presented and the astringency analysis is finished in the paper. The results of application example proved that practical optimization parameters can be obtained in limited time by the method, and it is a kind of effective way to solve such kind of problem.
Vibration measurements have been used to reliably diagnose performance
problems in machinery and related mechanical products. A vibration data
collector can be used effectively to measure and analyze the machinery
vibration content in gearboxes, engines, turbines, fans, compressors, pumps and
bearings. Ideally, a machine will have little or no vibration, indicating that
the rotating components are appropriately balanced, aligned, and well
maintained. Quick analysis and assessment of the vibration content can lead to
fault diagnosis and prognosis of a machine's ability to continue running. The
aim of this research used vibration measurements to pinpoint mechanical defects
such as (unbalance, misalignment, resonance, and part loosening), consequently
diagnosis all necessary process for engineers and technicians who desire to
understand the vibration that exists in structures and machines.
Keywords- vibration data collectors; analysis software; rotating components.
Ausgangspunkt dieser Arbeit ist die Einsicht, dass die Prüfplanung in ihrer bisherigen Ausgestaltung den Ansprüchen der heutigen Zeit nicht gerecht wird. Die Globalisierung der Märkte, Dynamisierung der Produktlebenszyklen und die stetig steigenden Ansprüche der Kunden führen zu tief greifenden Veränderungen. Die Unternehmen reagieren mit einer Anpassung der Aufbau- und Ablauforganisation Prozessabläufe werden modifiziert, Unternehmensstrukturen adaptiert. Die Prüfplanung ist von diesen Veränderungen, abgesehen von einer IT-Unterstützung einzelner Funktionen, weitgehend unberücksichtigt geblieben. Stetig steigende Rückrufe konstatieren, dass Produkte mit Qualitätsmängeln den Weg auf den Markt finden auch in sicherheitsrelevanten Bereichen. Weniger transparent sind die Auswirkungen, die Produkte hervorrufen, wenn interne Umsatz- und Gewinnziele nicht erreicht werden. Die Ursachen liegen zum einen in den Kosten notwendiger Nachbesserungen, um die Mängel zu beseitigen, zum anderen substituieren Käufer Produkte, wenn die Merkmale nicht voll ihren Anforderungen entsprechen. In dieser Arbeit wurde die modulare Prüfplanung entwickelt, die der Globalisierung der Märkte, Dynamisierung der Produktlebenszyklen und den stetig steigenden Ansprüche der Kunden gerecht wird: Integriert in die Prozesskette der Produktentstehung, orientiert an den Kundenwünschen, basierend auf QM-Methoden und alle notwendigen Fachabteilungen involvierend. Das Konzept umfasst die fünf Module Planung, Entwicklung, Anlauf, Serie und Einsatz, die entlang des Produktentstehungsprozesses positioniert werden. Unter Rückgriff auf die drei Gestaltungsdimensionen: Funktionen der Prüfplanung, Einsatz der QM-Methoden und Expertise der Fachabteilungen werden die Module aufgebaut. Die Erstellung und Konkretisierung eines Prüfplans erfolgt damit begleitend zur Produktentstehung. Während in den ersten Modulen bereits bei der Ableitung von Prüfmerkmalen die Kundenwünsche berücksichtigt werden, binden die Folgenden, die im Laufe der Entwicklung und Produktion gewonnenen Erkenntnisse in die Prüfplanung ein. Abschließend werden im Modul Einsatz die Prüfmerkmale sowie die Prüfnotwendigkeit unter Rückgriff auf Felddaten bestätigt, um die Prüfanweisung bei Bedarf zu überarbeiten. Die in sich abgeschlossenen Module bauen aufeinander auf die Zielerreichung wird durch Quality Gates sichergestellt. Die inhaltliche Reife wird dabei während der Durchführung aus Sicht der Lieferanten und zum Ende eines Moduls aus Kundensicht bewertet. Reagiert wird bei Abweichungen mit der Definition von Maßnahmen, deren Umsetzung im Weiteren kontrolliert wird. Starting point of this paper was the insight that inspection planning in its current state does not satisfy todays needs. The globalization of markets, dynamic sampling of product life cycles and the continuously increasing demands of customers lead to deep changes. Companies react with adaptation of both structural and process organization processes are being modified, internal structures redefined. The inspection planning was not yet considered except of IT support in some single functions. Steadily increasing product recalls state that products with failures are given into the market even with security relevant failure. Less visible are the impacts caused by products which lead to lower sales volume or benefits. The causes are one the one hand the costs for amendments, to abolish the failures. On the other hand customers substitute products if the features do not match their needs. In this paper the modular inspection planning was developed, considering globalization of markets, dynamic sampling of product life cycles and the continuously increasing demands of customers: Integrated in the chain of production, strictly orientated to customer needs, based on methods of QM and involving all necessary departments in a company. The concept consists of fife modules planning, development, ramp-up, serial production and application which are positioned along the chain of production. The modules are based on the three dimensions: functions of inspection planning use of QM methods and expertise of departments. The creation and development of the inspection plan is parallel to product development. While the first modules consider customer need when defining the inspection features the following modules integrate the information gained during development and production. Eventually the module application verifies the inspection plan and starts rework if necessary. The internally closed modules are based upon another the achievment of objectives in ensured by Quality Gates. The maturity of content is assessed from the point of views of internal supplier at the beginning and internal customers at the end of each module. If deviations occur actions are defined and permanently monitored to ensure that the targets will be met.
In this study a method for a robust design of mechanisms is proposed. The method used in the experimental analysis and quality engineering is applied for mechanisms design. A mathematical model for a mechanism is estimated by the response surface analysis and the estimated model is used in minimization of the variance. Using this result, robust design can be carried out. The method can be applied for general mechansims. Furthermore because the method can be used in the design stage using the computer model, improved quality and lower cost of the product is achieved even in the design stage.
This paper discusses response surface methodology (RSM) as an
efficient approach to parametric model building and design optimization.
Application of RSM is presented for torque optimization in spindle motor
design. A window-zoom-in method is studied to improve the optimization
procedure. Finite-element analysis and RSM using mixed resolution
central composite design are utilized to determine the optimum torque
performance. Analysis of variance summaries and response surface plots
help to locate the parameter settings to produce parts with the desired
quality
An alternative to Taguchi's robust parameter design has been recently presented. However, neither Taguchi's approach nor the alternative approach is capable of dealing satisfactorily with the frequently encountered siutations in which all the noise variables cannot be studied simultaneously. Based on the ideas from response surface modeling, linear models theory, and random effects models, we provide a method for estimation in the robust parameter design in such situations.
This paper describes a general, rigorous approach for robust optimal design. The method allows a designer to explicitly consider and control, as an integrated part of the optimization process, the effects of variability in design variables and parameters on a design. Variability is defined in terms of tolerances which bracket the variation of fluctuating quantities. A designer can apply tolerances to any model input and can analyze how the tolerances affect the design using either a worst case or statistical analysis. As part of design optimization, the designer can apply the method to find an optimum that will remain feasible when subject to variation, and/or the designer can minimize or constrain the effects of tolerances as one of the objectives or constraints of the design problem.
Taguchi's experimental system is used to develop robust processes, that is, processes which are insensitive to variations in uncontrollable variables, such as environmental variables. Taguchi's recommended designs can be considered to be response surface designs. These designs are compared to composite designs, which are classical response surface designs, and a new class of composite designs having mixed resolution is suggested as a competitor to Taguchi designs. An example is given of types of problems where it is better not to achieve a robust process, and customizing for specific customers can lead to greater customer satisfaction. An introduction to response surface methodology and to screening designs is used to set the stage.
The problem of designing mechanical systems or components under uncertainty is considered. The basic idea is to ensure quality control at the design stage by minimizing sensitivity of the response to uncertain variables by proper selection of design variables. The formulation does not involve probability distributions. It is proved, however, that when the response is linear in the uncertain variable, reduction in sensitivity implies lesser probability of failure. The proof is generalized to the nonlinear case under certain restrictions. In one example, the design of a three-bar truss is considered. The length of one of the bars is considered to be the uncertain variable while cross-sectional areas are the design variables. The sensitivity of the x-displacement is minimized. The constrained optimization problem is solved using a nonlinear programming code. A criterion which can help identify some of the problems where robustness in design is critical is discussed.
Measures of the quality of prediction at locations on the surface of a hyperspherc are presented. These measures are used to form a graphical method of assessing the overall prediction capability of an experimental design throughout the region of interest. A plot of the spherical variance and the maximum and minimum prediction variances for locations on a sphere against the radius of the sphere. a vuriance dispersion graph. is used to give a comprehensive picture of the behavior of the prediction variances throughout a region and hence of the quality of the predicted responses obtained with a particular design. Such plots are used to investigate and compare the prediction capabilities of certain response surface designs currently available to the researcher.
This paper is a reflection on where response surface methodology (RSM) is at this point and what will likely be future directions. The emphasis in the last two decades on robust parameter design has brought attention to RSM as an alternative methodology for variance reduction and process improvement. While computer generated design technology has been beneficial to those who are interested in constructing RSM designs, changes are needed in this area to allow consideration of design robustness rather than design optimality. RSM is moving into areas involving the use of generalized linear models (GLM's), and optimal RS designs for these areas are either difficult or impossible to implement by the user. Example applications of GLM's include logistic and Poisson regression. Other RSM areas that will enjoy use by practitioners in the twenty-first century include multiple responses and nonparametric and semiparametric methods. In addition, design and analysis techniques for cases where natural restrictions in randomization occur need to be addressed further and communicated to users.
A Japanese ceramic tile manufacturer knew in 1953 that is more costly to control causes of manufacturing variations than to make a process insensitive to these variations. The Ina Tile Company knew that an uneven temperature distribution in the kiln caused variation in the size of the tiles. Since uneven temperature distribution was an assignable cause of variation, a process quality control approach would have increased manufacturing cost. The company wanted to reduce the size variation without increasing cost. Therefore, instead of controlling temperature distribution they tried to find a tile formulation that reduced the effect of uneven temperature distribution on the uniformity of tiles. Through a designed experiment, the Ina Tile Company found a cost-effective method for reducing tile size variation caused by uneven temperature distribution in the kiln. The company found that increasing the content of lime in the tile formulation from 1% to 5% reduced the tile size variation by a factor of ten. This discovery was a breakthrough for the ceramic tile industry.
The concept of quality loss introduced by Taguchi is employed in the synthesis of designs that are insensitive to variations in controllable variables and uncontrollable parameters. A new design approach that achieves robustness by minimizing the expected value of a loss function based on a design's performance characteristic, and which is applicable to a general design situation, is proposed. The design constraints are stated in terms of their expected values. Both design variables and parameters are assumed to fluctuate about their nominal values. To ensure that in the pursuit of robustness, product performance is not compromised, the procedure constrains the expected value of the performance characteristic at its target value. Constraint violations that might be caused by fluctuations in design variables, or parameters, or both, are handled by reducing the feasible design space with the addition of a constraint sensitivity term, obtained using a linear statistical analysis. Two scenarios- one of which is applicable when the tolerances of the design variables are fixed, and the other to situations where the tolerances are treated as unknowns, are considered. The mechanics of this approach is illustrated by solving two examples. The first example involves the determination of the shape and configuration variables of a two bar truss; which is to be designed for minimum weight while being subject to stress constraints. The second example is a minimum cost welded beam design problem: where the dimensions of the weldment and the beam are found without exceeding the limitations staled on the shear stress in the weld, normal stress in the beam, buckling load on the beam and tip deflection of the beam. The utility of the robust design method and the reasons for its choice over a conventional design procedure are discussed. The methodology presented in this work is expected to be useful in designing robustness in machines, structures and other products where the system can be modelled using algebraic equations.
Cet article traite d'un compresseur rotatif destiné au conditionnement d'air. Les vibrations du compresseur sont analysées théoriquement et expérimentalement. On examine les caractéristiques des vibrations en régime permanent, lors des opérations de démarrage et d'arrêt. On indique une méthode simple de prévision des vibrations pour chaque régime de fonctionnement.
This paper describes model based operation planning for pocket milling operations. The tool path and cutting conditions are determined based on the geometric model of workpieces and the physical models of the cutting process. The tool path is generated by using the Voronoi diagram of a cutting area. Cutting conditions to achieve the maximum metal removal rate are determined by evaluating the physical models of cutting torque, chatter vibration, and machining error. To maintain a favorable cutting state, the radial depth of cut is controlled by modifying the tool path distance at the circle path segment and by adding additional tool path segments at the corner. Examples are shown to demonstrate the effectiveness of the method.
On the dynamics of a rotary compressor: Part 1 — Mathmatical modeling
- S K Padhy