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The objective of the article is to present the linking of simulation and planning software. The paper begins with a review of recent literature as well as description of the problem under investigation. Following from practical requirements, five decision-making rules were implemented to the production process. In the final part, the overall results to ensure time and economic efficiency of the production process are presented. The obtained results show that the best option is to apply the rule during which the first part to be machined is the one that first enters the production process to ensure minimum production time, maximum machine load and limit machine costs. By application of this rule, the total production time accounts for 524 seconds at the total cost of 7914.60 €. The overall benefits of the research are being described in details in the final part of the article. [ABSTRACT FROM AUTHOR]

The article discusses the problem of total waste separation in the frame of a computer simulation design of these systems. The aim of the article is to employ computer simulation, modelling and logistics for the needs of total separation of waste and its recycling into the form of raw materials and re-usable resources in practice. The results of the computer simulation show that by using total separation and waste recycling in the specifically analysed region, it is possible to produce approximately 7700 tons of recycled paper, 2400 tons of multilevel packages, 8000 tons of glass, 3000 tons of old textiles, 3500 tons of iron, approximately 1500 tons of non-ferrous metals, approximately 2700 tons of wooden pallets, approximately 1200 tons of rubber granulate, to process approximately 800 tons of dangerous waste, 2400 tons of electro waste, 2100 tons of gravel, 840 tons of sand and to liquidate approximately 3200 tons of non-recyclable waste during the whole year. [ABSTRACT FROM AUTHOR]

At present, AGV systems are an important part of numerous companies and their internal logistics systems. They are used to efficiently secure different types of transport processes in order to minimize operating costs. However, their reliable operation requires adequate setting and maintenance. Computer simulation is probably the most suitable option from a wide range of engineering methods with which to meet these requirements. This paper describes the development of a simulation model in the Tecnomatix Plant Simulation program to identify critical points of failure within a specific delivery process on the basis of a Milk Run system. Based on the results obtained, an appropriate solution was determined with which to make the whole process function more efficiently and reliably. [ABSTRACT FROM AUTHOR]

This paper attempts to overcome the defects of bottleneck recognition and scheduling optimization in open production line. For this purpose, the author analysed the impact mechanism of external disturbances and system configuration changes on the production line, and put forward a multibottleneck identification model for production line through computer simulation. Then, the proposed model was applied to optimize the scheduling of open production line. Specifically, the bottlenecks of production line were identified based on hierarchical clustering and multi-attribute decision-making, aiming to overcome the small candidate set and low accuracy of traditional bottleneck identification algorithms. The measured results show that the proposed algorithm has clear primary and secondary logics; the number of main bottleneck clusters decreased with the increase in the order; the number of machines in the main bottleneck cluster changed nonlinearly. The traditional genetic algorithm (GA) was improved in three aspects: the local optimum trap was avoided by enhancing population diversity; the iteration speed was accelerated with the introduction of adaptive crossover operator and genetic operator; without sacrificing the computing speed, the convergence quality was guaranteed through the addition of multivariate competition algorithm. The research findings provide new insights into the efficient operation of production line. [ABSTRACT FROM AUTHOR]

Simulations are widely used in manufacturing system design, production planning and decision making. The aim of this paper is to present the possibility of using Monte Carlo simulations in the production plan optimizing and in the project risk management. Optimization is accomplished through two different approaches which principles and results are mutually compared. According to the first approach, production optimization is performed via a deterministic model using the Generalized Reduced Gradient algorithm. The second approach is based on the stochastic model. The optimized production plan is submitted to risk analysis. Two approaches are demonstrated in order to reduce the rate of risk. The first way is modifying the production plan to increase the forecast reliability; the second approach is limiting the uncertainty of key variables. The detailed methodology enables implementing presented approaches in solving various optimization tasks. [ABSTRACT FROM AUTHOR]

Currently, robotic manufacturing cells entail complex decisions concerning sequencing issues due to uncertainty which arises in different parameters such as time to failure, time to repair and cycle times that can be effectively supported by computer simulation models. The paper is focused on part sequencing of a two-machine robotic cell in a flow shop which produces different parts. The process is supported by a single gripper robot to load/unload products and also in displacement within the system. This study considers machine failures and repair such that S2 cycle time and total production cost should be minimized. In this study, simulation facilitated input part sequence and also data envelopment analysis method is applied to trace the optimum sequence for satisfying the objective functions. Results through some numerical examples showed some simulation advantages specially to model many uncertainties and what if analysis. [ABSTRACT FROM AUTHOR]