Reliable model of mechanic behavior of lifting wire ropes

Wire ropes are used for different applications in many industrial domains, for instance, lifting system. Depending on the conditions of use, wire ropes are being degraded with direct consequences are significant changes of geometric and mechanical characteristics of its components. This results in a reduction in the resistance capacity of the wire rope with time, which could bring failure. Our work consists of studying the impact of the breaking of the wires which constitute the wire ropes on its duration, and develop models to determine the reliability of wire ropes to plan preventive maintenance actions and to change them in the appropriate time. We are equally proposing to develop a model which permits providing the resistance capacity of a wire rope in multiple levels of damage of its components and an analytical model of the relation of the reliability- damaging to illustrate the fatigue of the wires ropes’ lifting phenomenon . The approach adopted is a multi-scale approach with a total decoupling between the scale of the wire and the wire rope

Parametric Approaches for Spare Parts Demand

Forecasting of the spare parts needs is an important operational question. The problem in the needs forecast is that the demand is intermittent. In stock management, there are several forecasting tools based on demand history such as: linear regression, basic and modified Croston methods, simple and weighted moving average, exponential smoothing, and finally the bootstrap method. In this paper, we will treat the last method through three sections: literature review, procedure of the method and finally an application of the method which will be compared to simple exponential smoothing and hybrid method

Multipass Turning Operation Process Optimization Using Hybrid Genetic Simulated Annealing Algorithm

For years, there has been increasing attention placed on the metal removal processes such as turning and milling operations; researchers from different areas focused on cutting conditions optimization. Cutting conditions optimization is a crucial step in Computer Aided Process Planning (CAPP); it aims to select optimal cutting parameters (such as cutting speed, feed rate, depth of cut, and number of passes) since these parameters affect production cost as well as production deadline. This paper deals with multipass turning operation optimization using a proposed Hybrid Genetic Simulated Annealing Algorithm (HSAGA). The SA-based local search is properly embedded into a GA search mechanism in order to move the GA away from being closed within local optima. The unit production cost is considered in this work as objective function to minimize under different practical and operational constraints. Taguchi method is then used to calibrate the parameters of proposed optimization approach. Finally, different results obtained by various optimization algorithms are compared to the obtained solution and the proposed hybrid evolutionary technique optimization has proved its effectiveness over other algorithms

A novel approach for integrating the optimization of the lifetime and cost of manufacturing of a new product during the design phase

Maximum lifetime and minimum manufacturing cost for new products are the primary goals of companies for competitiveness. These two objectives are contradictory and the geometric dimensions of the products directly control them. In addition, the earlier design errors of new products are predicted, the easier and more inexpensive their rectification becomes. To achieve these objectives, we propose in this article a novel model that makes it possible to solve the problem of optimizing the lifespan and the manufacturing cost of new products during the phase of their design. The prediction of the life of the products is carried out by an energy damage method implemented on the finite element (FE) calculation by using the ABAQUS software. The manufacturing cost prediction is carried out by applying the ABC cost estimation analytical method. In addition, the optimization problem is solved by the method of genetic algorithms. The proposed model can be successfully applied for the optimization of new mechanical products made by subtractive manufacturing. The products that mostly benefits from this model are those used in machines and in the automotive or aeronautic fields. The proposed approach can be directly used by the designer for an optimal preliminary design of new products whose manufacture is done by the same company or subcontracted entirely or partially by other companies

Contribution Overview to the Evaluation and Development of Spare Parts Management Models: Meta-Heuristic and Probabilistic Methods

The presence of the spare parts stock is a necessity to ensure the continuity of services. The supply of spare parts is a special case of the global supply chain. The main objective of our research is to propose a global spare parts management approach which allows decision makers to determine the essential points in stock management. Thus, it is important for the stock manager to evaluate the system considered from time to time based on performance indicators. Some of these indicators are presented in the form of a dashboard. The presentation of this chapter chronologically traces the progress of our research work. In the first part, we present the work related to the forecast of spare parts needs through parametric and statistical methods as well as a Bayesian modelling of demand forecasting. To measure the appreciation of the supply of spare parts inventory, the second part focuses on work related to the evaluation of the performance of the spare parts system. Thus, we concretize the link between the management of spare parts and maintenance in the third part, more precisely, in the performance evaluation of the joint -management of spare parts and maintenance, in order to visualize the influence of parameters on the system. In the last section of this chapter, we will present the metaheuristic methods and their use in the management of spare parts and maintenance and make an analysis on work done in the literature

Performance Indicators for Spare Parts and Maintenance Management: An Analytical Study

A properly implemented maintenance management system has an impact at different levels. Maintenance is defined as the set of actions to maintain a property in a specified state. The unavailability of the spare parts required, to carry out the maintenance intervention, causes an extension of the inactivity time of the installation. On the contrary, an excessive stock of spare parts confines enormous capital and entails an enormous cost of ownership. According to the literature already made, we have directed in our work to propose a model of joint management of maintenance and spare parts based on stochastic-deterministic batch Petri networks. We studied this model by simulation using a graphical interface dedicated to the graphical tool used. So, we present, in this paper, the analytical study of the model by defining the performance indicators and viewing the influence of system parameters on these indicators. The main stages of the analytical study are developing the μ-marking graph, the associated Markov process which gives the associated transition matrix, and the definition of performance indicators using the probability distribution of the states. We deal with an application of the analytical evaluation of the proposed model. We end this article with an analysis and synthesis

The performance evaluation of the spare parts management: case study

The supply chain of spare parts is the intersection between the supply chain, the after-sales and the maintenance services. Some authors have tried to define improvement paths in terms of models to satisfy the performance criteria. In addition, other authors are directed towards the integration of risk management in the demand forecasting and the stock management (performance evaluation) through probabilistic models. Among these models, the probabilistic graphical models are the most used, for example, Bayesian networks and petri nets. Performance evaluation is done through performance indicators. To measure the appreciation of the supply of the spare parts stock, this paper focuses on the performance evaluation of the system by petri nets. This evaluation will be done through an analytical study. The purpose of this study is to evaluate and analyze the performance of the system by proposed indicators. First, we present a literature review on Petri nets which is the essential tool in our modeling. Secondly, we present in the third section the analytical study of the model based on bath deterministic and stochastic petri networks. Finally, we present an analysis of the proposed model compared to the existing ones