Knowledge Acquisition Using Computer Simulation of a Manufacturing System for Preventive Maintenance

Author(s):  
Sławomir Kłos
2011 ◽  
pp. 574-595
Author(s):  
Donguk Cheong ◽  
Bokyeong Kim

A computer simulation for improving teaching is expected to remove the potential negative effects on real students while creating an environment that combines academic theories in an abstracted world of the classroom. simClass II is a teaching simulation which was designed to allow pre-service and in-service teachers to develop and exercise their motivational skills as they work within a Web-based, simulated classroom environment. This chapter aims to provide background knowledge and the basic logic for developing a simulation to help teachers enhance their skills in motivating students, with simClass II serving as a concrete example. In addition, three phases—knowledge acquisition, exercise, and debriefing— are proposed for cyclical practice of these skills.


Proceedings ◽  
2019 ◽  
Vol 16 (1) ◽  
pp. 29
Author(s):  
Katarzyna Gładyszewska-Fiedoruk ◽  
Vasyl Zhelykh ◽  
Andrii Pushchinskyi

The quality of internal air is one of the factors that affect the pace and quality of knowledge acquisition. Therefore, it is important that the classrooms have high air quality. Using computer simulation, the effect of various building ventilation variants on air quality in classrooms was analyzed. As an indicator of air quality, the concentration of carbon dioxide in school halls was assumed.


Author(s):  
Donguk Cheong ◽  
Bokyeong Kim

A computer simulation for improving teaching is expected to remove the potential negative effects on real students while creating an environment that combines academic theories in an abstracted world of the classroom. simClass II is a teaching simulation which was designed to allow pre-service and in-service teachers to develop and exercise their motivational skills as they work within a Web-based, simulated classroom environment. This chapter aims to provide background knowledge and the basic logic for developing a simulation to help teachers enhance their skills in motivating students, with simClass II serving as a concrete example. In addition, three phases—knowledge acquisition, exercise, and debriefing— are proposed for cyclical practice of these skills.


2020 ◽  
Vol 28 (1) ◽  
pp. 72-84 ◽  
Author(s):  
Sofiene Dellagi ◽  
Wajdi Trabelsi ◽  
Zied Hajej ◽  
Nidhal Rezg

This study develops an analytical model in order to determine an optimal integrated maintenance plan and spare parts management. We consider a manufacturing system, producing only one type of product, over a finite planning horizon H equal to the sum of all production periods and the production quantity of each period is known. This system is subject to a continuously increasing degradation rate. That is why a preventive maintenance strategy is adopted in order to face the increasing failure rate. We noted that contrarily to the majority of studies in literature, we take into account the impact of the production rate variation on the manufacturing system degradation and consequently on the adopted optimal maintenance strategy. In addition, the real need of spare parts relative to the scheduled maintenance actions is taken into account. In fact, the purpose of our study consists at determining the optimal preventive maintenance frequency and the optimal quantity of spare parts to order by minimizing a total cost, including maintenance and spare parts management. Numerical examples are presented along with a sensitivity study in order to prove the use of the developed model for deriving the optimal integrated strategy for any instance of the problem.


2013 ◽  
Vol 845 ◽  
pp. 770-774 ◽  
Author(s):  
Seyed Mojib Zahraee ◽  
Milad Hatami ◽  
J.M. Rohani ◽  
H. Mihanzadeh ◽  
Mohammadreza Haghighi

In the manufacturing industry, managers and engineers are seeking to find methods in order to eliminate the common problems in manufacturing systems such as bottlenecks and waiting times. This is because that all of these kinds of problems impose extra cost to the companies. In addition, manufacturing companies are striving to sustain their competitiveness by improving productivity, efficiency and quality of manufacturing industry for instance high throughput and high resource utilization. The paper concentrates on the application of computer simulation to analysis manufacturing system in order to improve the productivity. Therefore, this study introduces a color manufacturing line as a case study and the basic application of arena 13.9 software. The goal of this paper is to improve the productivity and efficiency of the production line by using computer simulation. To achieve this goal, first the basic model of the current situation of production line was simulated. Second, three different alternatives were simulated and modified to find the best scenario based on the maximum productivity and minimum total cost.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jamileh Hayati ◽  
Sohrab Abdollahzadeh

The main purpose of this study is to present a new hybrid approach to select the appropriate maintenance policy (NET) of machines utilizing analytic network process (ANP), computer simulation, and the concept of virtual cellular manufacturing system (VCMS). Since conventional methods select only one NET policy for all machines or production lines, the performance of machines that do not conform to the selected policy is reduced. In the proposed method, the information of the functional parameters of the machines is extracted by means of computer simulation and there is no need for expert opinion. Next, the appropriate net policy for each machine is selected using the ANP method. To reduce the diversity and complexity of NET applications, machines are grouped using the concept of virtual cellular manufacturing system based on the similarity of NET policies. A NET program is prepared for each group of machines. The proposed approach is used in a production unit with three widely used NET policies, and its efficiency was proved by comparing the results with conventional methods.


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