Katia Lucchesi Cavalca

Availability optimization with genetic algorithm

This paper presents an availability optimization problem of an engineering system assembled in a series configuration which has the redundancy of units and teams of maintenance as optimization parameters. The objective is to reach the maximum value of availability, considering installation and maintenance costs, weight, volume and available maintenance teams as constraints. The optimization method uses a genetic algorithm (GA), which is based on biological concepts of species evolution. It is a robust method, because it does not converge to a local optimum. It does not need the use of differential calculus, facilitating the computational implementation. The final results are significantly indicative about the fitting of the GA parameters and the application of the methodology to solve engineering design problems involving systems availability.

Maintenance resources optimization applied to a manufacturing system

This paper presents an availability optimization of an engineering system assembled in a series configuration, with redundancy of units and corrective maintenance resources as optimization parameters. The aim is to reach maximum availability, considering as constraints installation and corrective maintenance costs, weight and volume. The optimization method uses a Genetic Algorithm based on biological concepts of species evolution. It is a robust method, as it does not converge to a local optimum. It does not require the use of differential calculus, thus facilitating computational implementation. Results indicate that the methodology is suitable to solve a wide range of engineering design problems involving allocation of redundancies and maintenance resources.

Combined application of QFD and VA tools in the product design process

The aim of both value analysis (VA) and quality function deployment (QFD) is to reduce waste by avoiding redesign and providing optimal location of costs in general. To satisfy the consumers most important needs, the VA prioritizes the increase in the cost of the product and not the subsequent price rise. QFD aims at generating clear engineering needs from consumer requirements thus, minimizing the reprojecting cost (“cost” should read “waste”) and changes in the products. The existing common concepts between two design tools, QFD (the project tool) and VA (the product optimization tool) motivated this study. QFD establishes a link among parameters such as the consumer needs, engineering requirements and a comparative analysis of the consumer perception against that of rival companies. The VA prioritizes a rise in the aggregate value (perceived by the consumer) by optimization development and production costs. The proposed methodology is capable of integrating these two tools, integrating costs with product development (“for the consumer”) for a joint analysis. This way it is possible to establish optimum cost values for each engineering requirement. It is also possible to evaluate the cost of each product function. Furthermore, the methodology provides a tool that supports decision making in product development and projects. This work evaluates the integrated use of the QFD and VA tools. Employing a survey that was carried out which intended to reveal the young male consumers’ requirements concerning a sports bicycle.

A comparison of flexible coupling models for updating in rotating machinery response

This paper analyzes the effects of the mathematical models of flexible couplings in rotating mechanical systems in terms of their vibrational behavior. The residual unbalance of the coupled shafts is considered to be the main source of vibration in the rotating system. The moments and the frequencies of the forces, which result from these effects, are close to the natural frequencies of the mechanical system. Since the coupling is considered to be a flexible component in the power transmission system, it introduces a certain amount of mass, damping and stiffness to the system, influencing its natural frequencies. The present work shows the modeling of a mechanical rotor-bearing-coupling system, through the finite element method, used in this case to analyze the transverse vibrations of the system. Different modeling techniques were taken into account for this purpose. Such models are recommended for flexible couplings to analyze their influence on the natural frequencies of the system and on the unbalance response of the system. Afterwards, a model updating was carried out to fit the coupling stiffness and damping coefficients, using the minimum quadratic technique. Some sensitivity of the proposed models was observed in relation to the coupling parameters.

Development of hybrid algorithm based on simulated annealing and genetic algorithm to reliability redundancy optimization

Purpose – The purpose of this paper is to present an application of the simulated annealing algorithm to the redundant system reliability optimization. Its main aim is to analyze and compare this optimization method performance with those of similar application.Design/methodology/approach – The methods that were used to compare results are the genetic algorithm, the Lagrange Multipliers, and the evolution strategy. A hybrid algorithm composed by simulated annealing and genetic algorithm was developed in order to achieve the general applicability of the methods. The hybrid algorithm also tries to exploit the positive aspects of each method.Findings – The results presented by the simulated annealing and the hybrid algorithm are significant, and validate the methods as a robust tool for parameter optimization in mechanical projects development.Originality/value – The main objective is to propose a method for redundancy optimization in mechanical systems, which are not as large as electric and electronic syst...

Reliability as an added‐value factor in an automotive clutch system

In the present competitive scenario, companies face the challenge of developing new products in a short time period, with superior technology in relation to prior developments and reduced costs to guarantee the survival of their business. Success is directly coupled with client requirements where quality and reliability should be the highest feasible, whereas deadlines and price have to be the lowest possible. This paper discusses tools and methods applied to planning and assurance of quality, which have to be taken into account at the product conception project, which concerns the phase in which quality, reliability and the final price of a product are technically defined. A methodology is presented for this purpose, and it can be extended to any product or system with few adaptations concerning quality, reliability and cost models. The product selected for the case-study analysis in this work is an automotive clutch. The methodology proposed for the analysis is a combination of the KANO method, target cost and value analysis with respect to the assessment of client requirement compliance levels and the determination of the choice of functions—whose relative costs are above relative needs, therefore offering optimization or elimination potential. Thus, the reliability concepts of statistical distributions and fault tree analysis are employed to locate critical components and quantify design temporary performance. To provide life tests results to the highest failure risk in the system, the planning and deployment of accelerated tests are carried out. The final goal of this paper is the reliability assessment based on critical levels for the analysis of components to be improved or optimized and, mainly, to create a methodology for the development of optimized products. Copyright

Analysis of a complete model of rotating machinery excited by magnetic actuator system

Rotating machines have a wide range of application involving shafts rotating at high speeds that must have high confidence levels of operation. Therefore, the dynamic behavior analysis of such rotating systems is required to establish operational patterns of the equipment, providing the basis for controller development in order to reduce vibrations or even to control oil instabilities in lubricated bearings. A classical technique applied in parameter identification of machines and structures is the modal analysis, which consists of applying a perturbation force into the system and then to measure its response. However, there are mainly two problems in modal analysis concerning the excitation of rotating systems. First, there are limitations to the excitation of systems with rotating shafts when using impact hammers or shakers, due to friction, undesired tangential forces, and noise that can be introduced in the system response. The second problem relies in the difficulty of exciting backward whirl modes, an inherent characteristic from these systems. Therefore, the study of a non-contact technique of external excitation, also capable of exciting backward whirl modes, becomes of high interest. In this sense, this article deals with the study and modeling of a magnetic actuator, used as an external excitation source for a rotating machine, mainly in backward whirl mode. Special attention is given to the actuator model and its interaction with the rotor system. Differently from previous works with similar proposal, which uses current and air gap measurements, here the external excitation force control is based on the magnetic field directly measured by hall sensor positioned in the pole center of the magnetic actuator core. The magnetic actuator design was completely developed for this purpose, opening different paths to experimental application of this device, for example, fault detection analysis based on directional modes. It is also presented a comparison between the numerical simulations and practical tests obtained from a rotor test rig and an experimental evidence of the backward whirl was accomplished based on the numerical simulation results.

On the Instability Threshold of Journal Bearing Supported Rotors

Journal bearing supported rotors present two kinds of self-excited vibrations: oil-whirl and oil-whip. The first one is commonly masked by the rotor unbalance, hence being rarely associated with instability problems. Oil-whip is a severe vibration which occurs when the oil-whirl frequency coincides with the first flexural natural frequency of the shaft. In many cases, oil-whip is the only fluid-induced instability considered during the design stage; however, experimental evidences have shown that the instability threshold may occur much sooner, demanding a better comprehension of the instability mechanism. In this context, numerical simulations were made in order to improve the identification of the instability threshold for two test rig configurations: one on which the instability occurs on the oil-whip frequency, and another which became unstable before this threshold. Therefore, the main contribution of this paper is to present an investigation of two different thresholds of fluid-induced instabilities and their detectability on design stage simulations based on rotordynamic analysis using linear speed dependent coefficients for the bearings.

EHD Modeling of Angular Contact Ball Element Bearings

The objective of this work is the study of the dynamic of angular contact ball element bearings considering the elastohydrodynamic lubrication. A computational model was built to foresee the dynamic behavior influence on the lubrication condition of those components. The model of EHD lubrication is taken into account in the bearing dynamic model, to obtain coefficients of stiffness, damping and subsequent characterization of the bearing, for different loading condition. The dynamic model has five degrees of freedom. The model considers, in its development, centripetal force and gyroscopic effects, and static equilibrium analysis are accomplished to find the force distribution in each sphere. With the force distribution, the dimensionless Moes parameters of lubrication and load are calculated, as well as the contact elliptic ratio, which are used in the EHD model. Therefore, it is possible to calculate the contact pressure, film thickness, as well as the contact force parameters and corresponding stiffness and damping coefficients.

Convergence on unbalance identification process based on genetic algorithm applied to rotating machinery

This work focusses on the application of genetic algorithm to fault detection in rotating systems and an uncertainty analyses were applied to mass unbalance identification. A finite element model is used to represent the system. The journal bearing stiffness and damping coefficients have already been identified by a model updating process, and they have been included in the model of the system. In order to identify the unknown fault parameters, a genetic algorithm search process is applied. The convergence of the process was investigated with regard to the influence of the main genetic algorithm parameters, taking into account the mean and standard deviation related to the objective function convergence in several cases.