Simulation modelling and analysis of a production line (original) (raw)
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Capacity improvement of an unreliable production line—an analytical approach
Computers & Operations Research, 2006
This paper addresses the problem of capacity estimation and improvement of a multi-stage, multi-product production line where workstations are subject to random failure and repair. The production line can process a variety of products in a batch production environment. Products are processed according to a predefined sequence. A linear programming model is used and modified by taking into account the random behaviour of unreliable stations. Station's downtime is modelled as a fictive product added to the production sequence at appropriate positions. A general procedure for the insertion of fictive products is presented. The procedure considers the states up and down that a station may experience while processing the product mix. It consists of two main steps. Firstly, enumerate the station's states and insert fictive products where appropriate. Secondly, find the best buffer size that minimizes the cycle time. The proposed approach considers more parameters than the Markovian models and the approximation methods where multi-product production lines longer than 2-station 1-buffer can be studied. Numerical examples are presented to show all the steps involved to compute the expected cycle time. Buffer contribution to minimize the cycle time of the production line is also addressed. Simulation is used to validate the results obtained.
A Simulation Based Approach to Calculate Total Availability of a Complicated Production Line
2009
Calculating total availability time in a complicated production line by mathematical methods is a problem. In contrast to a simple production line where each station breakdown results in stop in production line, in complicated lines, breakdown effect of a station depends on other stations availability, intermediated buffer capacity and so on. In this paper, after expressing the importance of this problem, a simulation based solution is proposed. A simulation model of subject production line is developed and got run twice, the first run considers real availability pattern of production line and the second run supposes all stations are available. The ratio of outputs of these two runs shows the availability percentage of subject production line.
Application of Discrete Event Simulation for Production Line Performance Evaluation
Simulation, in particular discrete event simulation, has still not gain industries wide acceptance as decision support tool for performance evaluation. This study intends to provide the example of the application of discrete event simulation in evaluating performance of a production line. The data was collected from an electronic manufacturing company's production line and the simulation model is built using ProModel simulation software. After validating the model and running the simulation, the result is obtained. The finding shows that the workers in the production line is underutilized and the bottleneck is detected at the inspection machine which has cause a higher manufacturing lead time. We suggest that these problems can be overcome by merging several tasks together to reduce the number of workers and increasing the capacity of the inspection machine. This study shows an another example of the benefits of simulation knowledge to manufacturing organization and its application in industry should be encouraged.
2016 Winter Simulation Conference (WSC), 2016
The paper demonstrates the use of a Discrete Event Simulation tool to reduce the negative impact of machine failures on the performance of a filling line. The buffer allocation problem has received a lot of attention, but still there are examples of unreliable production systems for which a buffer can be allocated in order to increase their productivity. The subject of the study is a filling and packaging production line which consisted of seven machines connected by conveyors. Machine failures are registered by maintenance Data Acquisition system. Those data are used to derive statistical distributions for Time To Repair and Time Between Failures. The model is built using FlexSim simulation software and different allocation scenarios are considered. Introduction of buffers results in an increase in mean line throughput by 15%. The initial results indicate that the proposed approach may lead to the reduction of negative effects of machine failures.
Utilizing simulation to evaluate production line performance under varying demand conditions
International Journal of Industrial Engineering Computations, 2012
Determining how a new production cell will function is problematic and can lead to disastrous results if done incorrectly. Discrete-event simulation can provide information on how a line will function before, during, and after the line is in operation. A simulation model can also provide a visual animation of the line to see how product will flow through the line. This paper discusses the development and analysis of a simulation model of a new manufacturing line. The manufacturing cell is a new motor assembly cell. An analysis of the capability of the line for varying demand levels was conducted for the two main motor types produced on the line. An ARENA ® simulation model was developed, verified, and validated to determine the daily production and potential problem areas for the various demand levels. The results show that at all but one demand level, the line is capable of producing to within one unit of customer demand if the required number of workers is present. At the highest demand level, the simulation results suggest that the line is not capable of meeting demand. Additional analysis indicates that multiple workstations could prove problematic with minor fluctuations in demand. Problematic workstations were identified for each assembly area and for the line as a whole.
Simulation Modeling of Automatic Production Lines with Intermediate Buffers
International Journal of Scientific and Engineering Research
A production line is an important class of manufacturing system when large quantities of identical or similar products are to be produced. The performance of a production line is highly influenced by machine failures. When a machine fails, it is then be unavailable during a certain amount of time required to repair it. Analysis of production lines divides into three types: analytical, approximation and simulation models. The analytical and approximation models have assumptions which make these models unrealistic such as reliable workstations, certain processing distribution, the first workstation cannot be starved and the last workstation cannot be blocked. The main problems in production lines treatment are the calculation of throughput and average levels of buffers because of the great size of state space. An analytical model is reviewed to clarify the limitations to use such treatment in real production lines. Simulation modeling of production lines is considered very important f...
Discrete Event Simulation Modeling To Improve Productivity On An Automotive Production Line
Computers and Industrial Engineering 42, 2012
Discrete event simulation modelling is a useful tool in helping decision makers in making operative, tactical and strategic decisions. The quick evaluation of possible scenarios in order to identify potential areas of improvement in a system is a prerequisite in a globally competitive manufacturing environment. In instances were simulation technology is not used the critical evaluation of complex production lines becomes a time-consuming and tedious exercise. The work presented in this case study is the development of a simulation model of a complex manufacturing automotive production line. "SIMUL8" was the discrete event simulation modelling software used in the case study presented. Systematic analysis was conducted on the simulation model in order to identify areas of inefficiency related to labour utilization and production capacity. From the analysis it was established that improvements could be made to labour utilization through a redistribution of work content as well as production capacity through the elimination of work stoppages and delays.
European Journal of Operational …, 2009
This paper compares two strategies for operating a production system composed of two machines working in parallel and a downstream inventory supplying an assembly line. The two machines, which are prone to random failures, undergo preventive and corrective maintenance operations. These operations with a random duration make the machines unavailable. Moreover, during regular subcontracting operations, one of these machines becomes unavailable to supply the downstream inventory. In the first strategy it is assumed that the periodicity of preventive maintenance operations and the production rate of each machine are independent. The second strategy suggests an interaction between the periods of unavailability and the production rates of the two machines in order to minimize production losses during these periods. A simulation model for each strategy is developed so as to be able to compare them and to simultaneously determine the timing of preventive maintenance on each machine considering the total average cost per time unit as the performance criterion. The second strategy is then considered, and a multi-criteria analysis is adopted to reach the best cost-availability compromise.
Simulation of The Production Line Repair Time Via Dynamic Systems
The major aims of this study are to analyze and study the optimal repair time of the production line of a manufacturing company. The relationship between timing failure, downtime, repair time, machine performance, sales and profit status of a dynamic system is also analyzed. It utilizes simulations (“Vensim Software”) and dynamic systems in a vegetable oil manufacturing firm in Iran. At first, the cause and effect diagrams of the model are shown via “Delphi techniques”, and then the statistical distribution of different factors affecting various parts of the model is determined by the “Arena Software”. Consequently the effect of different parts of the model on other parts is analyzed via the dynamic system. Then, by obtaining financial data relating to a digital generator, the cost- benefit of the model is determined from profit status views. The results of this study exhibit that the designated simulation model is potent and was able to indentify 5 factors influencing the repair time. The power disconnection (C.V=1.48), is indeed the most negative factor affecting the system. In addition, the profitability of the model can be enhanced 8.66% by investing in a digital generator.
MEASURING BOTTLENECK TIMES IN PRODUCTION LINES WITH DISCRETE EVENT SYSTEMS FORMALISMS
2000
This paper presents a theoretic approach to measurement of the bottleneck times in production lines. The mathematical formalism utilized is characteristic for Discrete Event Systems approaches, and is about the Markov chains. Using this approach, we introduce definitions of bottlenecks, and we discuss their implications for production automation and preventative maintenance. The bottleneck of a production line is a machine that impedes the system performance in the strongest manner. The size of the buffer between the two machines is assumed to be finite. The approach is based on the sensitivity of the system production rate to machine reliability parameters.