301 Flexibility Evaluation Method of Production Systems corresponding to Quantitative fluctuation

2010 ◽  
Vol 2010 (0) ◽  
pp. 37-38
Author(s):  
Shigeru HARASHIMA ◽  
Katsuhisa OHNO
2012 ◽  
Vol 524-527 ◽  
pp. 426-430
Author(s):  
Gang Xu ◽  
Yang Ding ◽  
Tian Jun Zhang

Coal mine safety assessment is an important ways for identification and elimination of danger in coal mine production systems. This paper introduce D-S evidence theory in evaluation of coal mine safety to solve the uncertainty problem of randomicity and faintness in evaluation of coal mine safety. The evaluation model of coal mine safety is set up based on evidence theory and the detailed arithmetic of evidence theory is brought forward, and according to some decision making rule the Chaohua Coal Mine has been evaluated. The results show that the model can solve the problem of uncertainty preferable and evaluation results with more accuracy and reliability.


Author(s):  
Yang Li ◽  
Qing Chang ◽  
Michael P. Brundage ◽  
Guoxian Xiao ◽  
Stephan Biller

Standalone throughput (SAT) of a single station is one of the most widely used performance indexes in industry due to its clear definition, ease of evaluation and the ability to provide a guidance for continuous improvement in production systems. A complex multistage manufacturing system is typically segmented into several subsystems for efficient local management. It is important to evaluate performance of each subsystem to improve overall system productivity. However, the definition of standalone throughput of a production subsystem is not as clear as for a single station in current literatures or in practice, not to say an effective evaluation method. This paper deals with the standalone throughput of a serial production line segment. The definition and implication of standalone throughput of a line segment is discussed. A data driven method is developed based on online production data and is proved analytically under a practical assumption. In addition, the method is verified through simulation case studies to be an accurate and fast estimation of the standalone throughput of a production line segment.


BioResources ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. 6752-6765
Author(s):  
Roman Bambura ◽  
Erika Sujová ◽  
Helena Čierna

Computer simulation methods are currently used to simulate production processes and optimize production systems. Computer simulation is one of the most effective tools for implementation of Industry 4.0 principles in industrial practice. This research focused on the optimization of production processes in furniture production using simulation, which is an innovative method of production optimization for furniture manufacturers. The aim of this research was to improve the production system of Slovak furniture manufacturing enterprise by creating a discrete event simulation model of production based on the analysis of its current state. Improvement indicators are specific parameters of the production system, which primarily include material flow, productivity, and workload utilization. First, with the use of Tecnomatix Plant Simulation software and the collected real production data, the original production system processes were simulated and analyzed. Second, the incorporation of more powerful devices was proposed to improve the production line. Third, the proposed improvements were simulated and analyzed. The result of this research was a statistical comparison of the parameters of the current production line and the proposed production improvements.


Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 641
Author(s):  
Ana Cornelia Gavriluţă ◽  
Eduard Laurenţiu Niţu ◽  
Constantin Alin Gavriluţă

Lean Manufacturing includes an ensemble of methods to analyze and continuously improve the functioning of manufacturing systems. The research presented in the literature highlights the fact that these methods are, on their own, in a process of continuous improvement as tools, being used in different ways, for different production systems. The paper presents an algorithm that facilitates the choice of the performance evaluation method, and the choice of the method of improvement that needs to be implemented for an efficient analysis and for a continuous increase of the manufacturing system performance. In addition to these, for the JobObservation and 5S methods, chartflows are proposed and specific tools are developed (questionnaires, forms etc.) that are meant to facilitate the implementation and to focus (guide) the user in the direction of improvement for the analyzed process. The algorithm, techniques, and tools developed in this research were used in a case study that took place in a production system “plastic injection”. Thus, a series of important improvements were made in the functioning of the production system, consisting of the reduction of production area, decrease of cycle time, decrease of the number of operators, stabilization, standardization, and securing of the work processes. All this has led to the improvement of several key performance indicators (KPIs) of the production system. The analysis of the investment in the reorganization of the production system in relation to the obtained gains shows a payback of approximately 1 month, proving the efficiency of use in such a form of the Lean Manufacturing methods.


Author(s):  
О.Е. Семенкина ◽  
И.С. Рыжиков ◽  
Л.В. Липинский ◽  
Е.А. Попов

Предложен метод моделирования для разработки систем поддержки принятия решений (СППР) в оперативном планировании производства. Обладая гибкостью в описании технологических процессов и простотой в масштабировании модели производственных систем, метод обеспечивает детальное планирование, включая сменно-суточные задания. Апробирован в СППР аффинажного производства. The paper proposes a method for production systems modeling for development of decision support systems (DSS) in operational planning. It allows to create a detailed plan, including shift-daily tasks, while having flexibility in describing technological processes and simplicity in scaling the model. The developed method was used to create a DSS for refining production.


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