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![Figure 1: Modules of Tecnomatix considering the utilization [8].](profile/Peter-Malega/publication/321717261/figure/fig1/AS:570173631496192@1512951395337/Modules-of-Tecnomatix-considering-the-utilization-8_Q320.jpg)
![Figure 2: Examples of Plant Simulation exploitation [10].](profile/Peter-Malega/publication/321717261/figure/fig2/AS:570173633826816@1512951395419/Examples-of-Plant-Simulation-exploitation-10_Q320.jpg)
The aim of this article is to create a simulation model of specific production system in Plant Simulation environment. The main production program that we monitor in this article is focused on the production of tapered roller bearings. Types of produced products are wide; therefore we focus attention on a material flow of one particular dimensional...
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... we have chosen for the simulation process are tapered roller bearings. Fig. 4 shows the tapered roller bearing with its main parts. The components, from which they consist, are: inner ring, rolling element (in this case cones), outer ring (in the case of tapered roller bearings it is separable), ball cage (the purpose is to avoid contact/friction of individual cones with another ...
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... The basic element is the ability to innovate education, research, experimentation, development and information and thus apply new knowledge in society. Countries that have used these activities to strengthen innovation often show outstanding results [19,20,21]. ...
This paper deals with the design of an automatic robotic assembly station with the aim of creating a new and more efficient working environment in the production process on the assembly line and thus contributing to meeting customer requirements. The paper presents theoretical knowledge on innovations and on the innovation process. The introduction of an automated workplace will lead to a higher production line than it follows from evaluation of data collected over time. The result of the work is a proposal to create a new and more efficient work environment.
... García-Montalvo et al. evaluated two different scenarios of the sand recovery in a pilot plant using the Plant Simulation software [28]. Malega et al. improved the production efficiency of a tapered roller bearing using the Plant Simulation [29]. Fedorko et al. identified critical points of failure within a specific delivery process for a Milk Run system with the help of Plant Simulation [30]. ...
... One of such tools, the FlexSim package [1][2][3], was recently applied in various branches of industry. These include simulating the process of mass customization of products [4], performance improvement of airport security control system [5,6], fully-automatic sorting system design [7], dynamic redesign of the production system [8], lot sizing optimization [9], order batching algorithm for pick-and-pass system [10], production logistics optimization [11], production of tapered roller bearings [12], supply chain management [13][14][15], mixed line production in automotive sector [16] or implementation of lean manufacturing system in printing facility [17]. ...
A model of the transport system in a copper ore mine was prepared using FlexSim software and the simulations were performed for five days. Empirical parameters were applied to each item of the transport system in order for the ore transport times to correspond to the actual conditions. Both the class- and the loading point-specific haul truck courses were based on the five-day schedule. Mean inter-arrival times were modelled for haul trucks according to empirical histograms. The ore portions were discretized and their masses were based on haul truck load capacities. The simulations were performed for twelve variants covering the unavailability of different ore sources. The recorded statistics include ore provenience, lithology, Cu content and tag survival rate for RFID-tagged ore variants. The model represents the new way of solving the problem of ore mixing in a conveyor belt-based transport system. Adoption of the proposed scheme, will allow the enrichment plant managers to adjust the milling and crushing parameters to the lithology of the ore before it will leave the mine. The model allows to pinpoint the areas in the mine that produce certain demanded lithological factions and helps the managers to choose the most desirable pattern of the mining schedule and forecast the economical outcome.
... geostatistical). Problems with quality assessment occur when mined ore is blended, e.g. after the whole mined deposit height is blasted, or when ore is transported, e.g. on a belt conveyor with many feeding points and in transfer stations [4,5]. The identification of a transported run-of-mine ore is a compulsory condition to implement the Quality Assurance -Quality Control (QA/AC) procedures, necessary to maintain the required quality of products as well as to reconcile the mining production in mining fields. ...
Modelling the flow of a non-homogeneous ore is an important element needed to identify ore parameters for the purpose of ore processing control. The simulation model of the underground ore haulage system with the implemented function of estimating ore qualitative and quantitative parameters was built in the dedicated FlexSim simulation environment to address this issue. The transported ore is averaged in transfer and retention points, for instance in ore bunkers. This fact renders the modelling of ore flow inside the bunker a necessary part of the simulation. The movement of the granulated material, restricted by the geometry of the floor and walls, is modelled using Discrete Elements Method (DEM) with regard to the technological cycles of bunker filling and emptying. An experimental task was conducted on the site to identify the transport time of RFID tags that flowed together with the portions of ore they annotated. Empirical model of the transport system in the KGHM Lubin mine was parameterized with mean retention times obtained in DEM simulations in order to be compared with the RFID-tag experiment. The as-parameterized FlexSim simulation for one-chute bunker discharge variant yields tag transport times comparable with the experimental data. The results proved the reliable description of the ore transport time in the FlexSim model.
... Ю. Гусев, Ю. С. Скрипченко, Ю. М. Школьникова купность подсистем, деятельность которых направлена на достижение общей цели [1]. В работах современных ученых неоднократно исследовалось применение имитационного моделирования для исследования производственных систем [2,3,4]. Также проводились исследования наиболее перспективных программных средств имитационного моделирования производственных систем [5,6]. ...
Разработка имитационной модели представляет собой трудоемкий процесс, который характеризуется множеством взаимосвязанных этапов. В зависимости от корректности принятия решения на каждом этапе зависит результат моделирования в целом. Важным этапом разработки является определение структуры объектов в имитационной модели. В настоящее время в работах ученых слабо отражено состояние данного вопроса. В представленной работе авторами предложена иерархическая структура организации объектов имитационной модели при моделировании больших производственных систем
An optimization of the production process is defined as the search for solutions with improved production efficiency. Process optimization should be one of the main components of a business strategy that not only delivers benefits to customers but also helps increase the performance of production processes and benefits the entire business. The traditional approaches to job shop scheduling are based on the exact mathematically formalized model. If the number of model parameters is high and the environment is rather uncertain, the practical applications are quite restricted. That is why the theory proposes an approach based on a large-scale computer simulation. The main goal of this paper is to show that in a concrete company case, the simulation-based approach provides increased productivity. The presented study proposes the practical application of the Tecnomatix software used in the research to optimize the production system. The partial aims of the paper are as follows: (1) to create a simulation model of the production system with the help of the Plant Simulation module, (2) to model the current state of matters in the company, and (3) to propose a solution to the problem. Ultimately, we show that the simulation approach to the production line control provides rather effective solutions when compared to the intuitive one based on trial-and-error experience. The improvement includes a significant (1) shortening of the production cycle and (2) increase in productivity.
In this work, a case study of the footwear manufacturing industry is approached. In particular, the case of a leather footwear SME in Argentina is analyzed. The study focuses on the variability of performance that involves working with natural raw materials and its consequent impact on production capacity. For this, the production process was modeled respecting all sources of uncertainty of the problem. Discrete event simulations were performed to analyze the system, and the bottleneck was detected. When analyzing the potential alternatives to overcome the capacity limitation, it was decided to enlarge the workforce. The results of the proposed solution showed that incorporating a worker increased productivity more than proportionally to the direct increase in labor.
