Arman Sajedinejad; Meysam Lotfi
Abstract
In this paper, a non-periodic preventive maintenance scheduling optimization model for multi-component systems is provided based on the maximum availability of system components. In addition to providing the required level of system reliability and satisfy other system constraints (maintenance activities ...
Read More
In this paper, a non-periodic preventive maintenance scheduling optimization model for multi-component systems is provided based on the maximum availability of system components. In addition to providing the required level of system reliability and satisfy other system constraints (maintenance activities and available resources), total costs (direct and indirect) associated with minimal maintenance and, if necessary, one of the maintenance activities include in inspected and serviced simple, preventive repair and preventive replacement for each component, is proposed. Each of these activities uses various sources and regarding the position of the repairing component, effects differently on the reliability of the system. The costs considered include in direct costs (simple service, repair and replacement) as well as indirect costs (out of order and random failures). Since the proposed model has a complex structure, in order to solve the problem, the Genetic Algorithm (G.A) has been used and the results is presented. In the end, performance and use of this model, for a 10-part series - parallel is presented in the form of a case study.
Mojgan Khorasani; Abolfazl Kazemi
Abstract
This paper investigates a supplier evaluation and selection model which considers features of leagile supply chain and allocates orders to the selected suppliers. In the proposed model, potential suppliers are evaluated by applying a multi-objective model with respect to the key features of leagile supply ...
Read More
This paper investigates a supplier evaluation and selection model which considers features of leagile supply chain and allocates orders to the selected suppliers. In the proposed model, potential suppliers are evaluated by applying a multi-objective model with respect to the key features of leagile supply chain, including the ability to respond to demands, reducing delay time and costs (which are the winning factors for being the winner of market in this supply chain), as well as considering the capacities and limitations of organizations and suppliers. The proposed model allows buyer to select several suppliers. In addition, the model is multi-products and multi-periods. Due to long time and inefficiency of exact methods for large-sized problems, in addition to Lingo software, Genetic Algorithm is used to achieve the optimum solution
Hadi Hematiyan; Meysam Sarreshtehdar; Hassan Hadipour
Volume 9, Issue 23 , December 2011, , Pages 163-186
Abstract
The present study aims at optimizing the vehicle brake drum assembling process. Considering the crucial role of the Axle unit, especially its vehicle brake drum which is related to the safety of the passengers, the study of the producing and assembling processes and conducting the quality control experiments ...
Read More
The present study aims at optimizing the vehicle brake drum assembling process. Considering the crucial role of the Axle unit, especially its vehicle brake drum which is related to the safety of the passengers, the study of the producing and assembling processes and conducting the quality control experiments during these stages is of great importance. With regard to the great significance of three main factors, namely, seal-oil spindle diameter, seal-oil internal diameter, and nut lock torque as independent variables, the present research attempts to optimize the rotatory torque of the automobile brake drum getting help from the discussions in the RSM and the unsteady of the automobile brake drum getting help from fuzzy regression using least absolute deviation estimators. Finally optimal solution perused by nonlinear programming model and Genetic Algorithm using one of multi-objective existing methods (LP-metric). Comparing the two optimization methods is shown that the GA technique has better performance rather than nonlinear programming model.