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The production with high quality at the lowest production time can be a key means to success in the competitive environment of manufacturing companies. Therefore, in recent years, the need for extra precise and high-speed machine tools has been impressively increased in manufacturing applications. One of the main sources of errors in the motion of high-speed spindles is the occurrence of non-repetitive runouts (NRRO) in the bearing. The NRRO can be caused by some factors such as the form of balls, the waviness of rings, the number of balls, and the permutation of one or two balls in the ball bearing. In this paper, a Taguchi-based approach is proposed for the optimal design of high-speed spindle bearings by minimizing the NRRO in the machine tools compatible with corresponding standards. First, the optimal design of the high-speed spindle bearings to minimize the NRRO is formulated.

The desired milling process with high material removal rate (MRR) and low surface roughness of the product can be achieved only if machining chatter is absent. Incorporating chatter into the optimal selection of the machining parameters leads to a complex problem. Therefore, the approach of selecting conservative intervals for the machining parameters is usually employed instead. In this paper, a practical approach is proposed to specify the optimal machining parameters (depth of cut and spindle speed) in order to maximize MRR and minimize forced vibrations by considering machining chatter. Firstly, the worst-case scenario-based optimization problem in terms of the surface quality is solved to find the critical time at which maximal amplitude vibrations occur. Then, the time dependency of the problem is eliminated. Secondly, the multi-objective optimization is conducted to achieve the Pareto Optimal Front (POF).

Operational modal analysis techniques classically have been developed based on the assumption that the input to the system is a stationary white noise. While, in many practical cases, the systems are excited by combination of white noise and colored noises (harmonic excitations). Consequently, in conditions where non-white noises are present, the existing OMA methods cannot completely distinguish between the system poles and the induced poles due to colored noises. In order to overcome this weakness of OMA methods, some researches have been conducted in the field. In this paper, a new method is proposed for identifying the modal parameters of the system under the unknown colored noises, based on the Power Spectral Density Transmissibility (PSDT) function. In this work, the proposed methodology is established upon applying the auxiliary force, which can re-excite the system under operational conditions.

A mechanical system inherently affected by the conditions, factors, and parameters of uncertainties. Without including the uncertainty effects in the design procedure, the designs may not be robust and reliable. Robust design optimization (RDO) method is a procedure to find the insensitive design with respect to the variations. On the other hand, reliability is measured by the probability of satisfying a specific design criterion. Therefore, a reliable design is a design that satisfies the specified criteria even with some uncertainties in variables and parameters. Reliability-based design optimization (RBDO) is an optimization procedure that incorporates reliability requirements to find the proper design. Since RDO and RBDO are usually the expensive computational approaches, the Reliability-Based Robust Design Optimization (RBRDO) may be difficult to apply. In this paper, a new model for the reliability based robust design optimization is introduced.

Tolerance allocation is a key tool to reach a product with the minimum cost and the maximum performance. Since the thermal effects can cause the dimensional and geometrical variations in the components of mechanical assemblies, the tolerance allocation may be inefficient in the optimal tolerance design at the nominal conditions without including the thermal impacts. In this paper, a new optimal tolerance design of mechanical assemblies with the thermal effects is proposed. According to the proposed method, the tolerance allocation procedure is modeled as a multi-objective optimization problem. The functional objective, the manufacturing cost, and the quality loss function are considered as the corresponding objectives multi-objective optimal tolerance design problem. Using the computational results from the finite element simulations and based on the Artificial Neural Network (ANN) method, the design function as functional objective can be modeled.

Operational modal analysis based on power spectral density transmissibility functions (PSDT) is a powerful tool to identify the modal parameters with low sensitivity to excitations. The rotor systems may have the asymmetric damping or stiffness matrices which can lead to increase the difficulties of the identification procedure. In this paper, a new method is proposed to identify the modal parameters of the asymmetric rotary systems by the operational modal analysis based on the power spectral density transmissibility functions. For pole extraction from the PSDT function, a proper parametric identification method such as the Poly-reference Least Squares Complex Frequency-domain method (PLSCF) or poly-Max method can be used. Then, the rotary system poles can be identified from a Stabilization Diagram (SD) with overestimating the system model order. The proposed algorithm is validated by a computer simulation.

Kinematic accuracy of the robot end-effector is decreased by many uncertainties. In order to design and manufacture robots with high accuracy, it is essential to know the effects of these uncertainties on the motion of robots. Uncertainty analysis is a useful method which can estimate deviations from desired path in robots caused by uncertainties. This paper presents an applied formulation based on Direct Linearization Method (DLM), for 3D statistical uncertainty analysis of open- loop mechanisms and robots. The maximum normal and parallel components of the position error on the end-effector path are introduced. In this paper, uncertainty effects of both linear and angular variations in performance of spatial open-loop mechanisms and robots are considered.

This paper presents a novel model-based algorithm which is able to detect and isolate major faults assigned to the gas exchange path of a gasoline engine both in the intake and exhaust sides. The diagnostics system is developed for detection and isolation of these faults: air leakage fault between the compressor and the air throttle, exhaust manifold pressure sensor fault, wastegate stuck-closed fault and wastegate stuck-open fault. Sliding mode observers (SMOs) are the core detection algorithms utilized in this work. A first order SMO is designed to estimate the turbocharger rotational dynamics. The wastegate displacement dynamics coupled to the exhaust manifold pressure dynamics is estimated using a second order SMO. Verified with experimental data from a modern TC gasoline engine running in a test cell, the two sliding mode observers are then used in a strategy to detect the faults in the gas exchange path.

The design process always has some known or unknown uncertainties in the design variables and parameters. The aim of robust design is minimization of performance sensitivity to uncertainties. Tolerance allocation process can significantly affect quality and robustness of the product. In this paper, a methodology to minimize a product's sensitivity to uncertainties by allocating manufacturing tolerances is presented. The robust tolerance design problem is formulated as a multi-objective optimization based on the combined function-uncertainty-cost model. Genetic algorithm is utilized to solve the multi-objective optimization and a case study is presented to illustrate the methodology.

One of the main problems associated with design of fault detection (FD) strategy is availability of first generation engine. To solve this problem a methodology based on a virtual engine platform is proposed in this paper. This approach allows designing an FD algorithm in early stages of engine development. The application of this methodology is illustrated on a modern turbocharged gasoline engine by investigating the effect of a leakage in the exhaust manifold. Experimental results show good ability of the virtual engine platform to predict the effect of the leakage fault on the engine performance. Moreover unexpected results of exhaust manifold leakage effects are presented which are very useful for designing a leak detection strategy.

The process capability indices are widely used to measure the capability of the process to manufacture objects within the required tolerance. Fit quality is mainly dominated by the distribution of fit dimensions, i.e., a gap dimension. As the fit dimensions are very difficult to be measured in mass production, they are not to be considered as a direct inspection objective. The quality inspection and evaluation relative to fit quality are focused on whether the processes of assembly requirements are conformed with their specification limits respectively. Fit quality specification can be indicated by the process capability indices of mating parts. In this paper, the statistical-based process capability analysis method is presented to estimate ability of manufacturing process for considering of assembly requirements and fit quality in a mechanical assembly with asymmetric tolerances.

A theoretical forming limit stress diagram (FLSD) for necking prediction which is based on the strain gradient theory of plasticity in conjunction with the M-K approach was represented and used in tube hydroforming. This approach introduces an internal length scale into conventional constitutive equations and takes into account the effects of deformation inhomogeneity and material softening. The nonlinear second order ordinary differential equation of the thickness of tube has been solved by collocation method. It has been shown that this method overcomes the imperfection sensitivity encountered in the conventional M-K method. The predicted FLSD has been compared with published experimental hydroforming stress limit diagram and good agreement was found between them. The purpose of this work is the implementation of the forming limit stress diagram determined by the proposed methodology to obtain suitable load path in tube hydroforming.

In this research a computer model based on elasto hydrodynamic fluid film lubrication is developed in order to calculate the torque transmission efficiency of a half-toroidal CVT variator. Validation of this model is verified by comparing the experimental and the model results. Sensitivity of torque transmission efficiency to eleven parameters is investigated. These parameters are: dimensionless roller curvature, aspect ratio, half cone angle, fluid viscosity index, pressure constant for Roelands model, input rotational velocity, absolute viscosity at atmospheric pressure, Young modulus of disks and power rollers, Poisson ratio of disks and power rollers, number of power rollers and variator cavity radius. The fractional factorial design 2k- p is employed for sensitivity analysis.

In this research, the handling behavior of an intermediate class passenger car has been optimized by altering its front suspension parameters. For this purpose, a validated virtual model of the car, constructed by Adams/Car software, has been used. The utilized objective function is a combination of eight criteria indicating handling characteristics of the car. To reduce the amount of optimization parameters, a sensitivity analysis has been done by implementing the Design of Experiments method capabilities. Optimization has been done using the Response Surface Method. The obtained optimization results show a considerable improvement in the system response.

In this research, important parameters of a rack and pinion steering system in dynamic steady state and transient responses have been investigated. For this purpose, virtual model of a medium passenger car in ADAMS/Car has been used. The model has up to 121 kinematic degree of freedom and includes all components of the rack and pinion steering system. Several different experimental test results have confirmed the validity of the model. Sensitivity analysis have been done based on design of experiments (DOE) method. Two level fractional factorial designs have been selected for this purpose. Steady state cornering and step steer input are the analysis that used for this research. Understeering coefficient, steering wheel torque and steering sensitivity are obtained from the steady state cornering analysis, while the step steer analysis yields yaw velocity overshoot, yaw velocity rise time, lateral acceleration overshoot, lateral acceleration rise time and roll angle overshoot.

In this paper, development of a MATLAB-based computer environment for optimization of EMS calibration is presented. The objective is to eliminate the complicated and tedious calibration process on chassis dynamometer or at least reduce the time required. In this way, first a black-box model of engine is developed. Then this model is linked to ADVISOR -the renowned vehicle simulation software- to obtain an integrated engine-driveline model. This model is used in the optimization process, which includes different optimization techniques.

Design of a fuzzy controller for active suspension of a compact car is the topic of this article. The car dynamic model used for this purpose is very large and completely nonlinear. A large part of this model namely the car basic dynamics is constructed in ADAMS software which in excess of considering the components in their real working conditions, it includes parameters such as flexibility of parts and joints. The hydraulic system of the active suspension system is modeled in Matlab and the two softwares are linked to form the complete car model. Using control methods on the basis of neural network and fuzzy logic, a controller is designed that can eliminate roll over of the car in sever driving conditions.

This paper focuses on design and modeling of anti-roll system for a subcompact passenger car. The system consists of Hydraulic Assisted torsion bars on car suspensions, a hydraulic power unit, and controls. A 158 degrees of freedom model of the car basic dynamics is made in ADAMS software. A bond graph model of the hydraulic anti roll system is contracted and its state equations are entered into MATLAB/Simulink. The two software are linked and a complete model is made for study and controller design. This paper introduces the method as a useful tool for vehicle dynamics studies and discusses the problems and advantages of the method.

Genetic Algorithm is applied to the physical parameter estimation of a full vehicle nonlinear multi-body ride model. Beforehand unity of system representation (identifiability) and sensitivity analysis for determining the effects of parameter changes on the response of the vehicle is discussed. A random road profile is designed as a persistent excitation. Input-output data required for the identification is obtained from ADAMS/CAR simulations of a more complex model. Robustness of the identification method is studied by adding different noise levels to the ADAMS output signals. Validation of the results is carried out by comparison of the identified model outputs with experimental measurements done on the same vehicle, which its ADAMS model was available. Test was performed on the Schenck hydropuls road simulator. Accuracy of estimated parameters is evaluated by information available from other sources such as technical drawings and performance tests of the vehicle parts.

This paper implements a derivative free optimization method called ‘Genetic Algorithm’ to estimate the parameters of a four wheel three degrees of freedom vehicle handling model. At first the model is developed containing a non-linear tire model called ‘Fiala’. Then an error function is defined and ‘Genetic Algorithm’ optimization method is introduced and applied to minimize the error, Finally verification of parameter estimation is checked.