Case Study on Simulation Analysis of a Multiple Product Manufacturing System

2010 ◽  
Vol 43 (17) ◽  
pp. 172-177
Author(s):  
Juraj Švančara ◽  
Zdenka Králová
Keyword(s):  
Manufacturing System ◽  
Simulation Analysis ◽  
Product Manufacturing ◽  
Multiple Product

scholarly journals Joint Optimization Approach of Maintenance and Production Planning for a Multiple-Product Manufacturing System

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Lahcen Mifdal ◽  
Zied Hajej ◽  
Sofiene Dellagi
Keyword(s):  
Production Planning ◽  
Manufacturing System ◽  
Analytical Models ◽  
Maintenance Cost ◽  
Optimization Approach ◽  
Production Plan ◽  
Total Production ◽  
Maintenance Strategy ◽  
Product Manufacturing ◽  
Multiple Product

This paper deals with the problem of maintenance and production planning for randomly failing multiple-product manufacturing system. The latter consists of one machine which produces several types of products in order to satisfy random demands corresponding to every type of product. At any given time, the machine can only produce one type of product and then switches to another one. The purpose of this study is to establish sequentially an economical production plan and an optimal maintenance strategy, taking into account the influence of the production rate on the system’s degradation. Analytical models are developed in order to find the production plan and the preventive maintenance strategy which minimizes sequentially the total production/inventory cost and then the total maintenance cost. Finally, a numerical example is presented to illustrate the usefulness of the proposed approach.

Stochastic Flow Model-Based Representation of System-Level Manufacturing Quality

2007 ◽  
Author(s):  
Guillaume Graton ◽  
Martin Guay ◽  
Patrick Egbunonu ◽  
Jorge Arinez
Keyword(s):  
Supervisory Control ◽  
Manufacturing System ◽  
Flow Model ◽  
System Level ◽  
Stochastic Flow ◽  
Flow Modeling ◽  
Parameter Fitting ◽  
Product Manufacturing ◽  
Multiple Product ◽  
Adaptive Approaches

This paper describes the application of the stochastic-flow-modeling (SFM) approach to represent the quality behavior of a manufacturing system. The paper extends the basic one-product type SFM to that of a multiple-product manufacturing system. This quality SFM-based model has aggregation by machine, product, and operational shift. The paper also describes potential supervisory control architectures that could be used in conjunction with this quality-based SFM. The distribution parameter fitting is handled with static and adaptive approaches and a comparison between these two approaches is given. Finally, results are presented for different system examples that show the accuracy of the SFM modeling approach.

scholarly journals Utilizing an Adaptive Grey Model for Short-Term Time Series Forecasting: A Case Study of Wafer-Level Packaging

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Che-Jung Chang ◽  
Der-Chiang Li ◽  
Wen-Li Dai ◽  
Chien-Chih Chen
Keyword(s):  
Semiconductor Manufacturing ◽  
Manufacturing System ◽  
Grey System Theory ◽  
Grey Model ◽  
Grey System ◽  
Wafer Level ◽  
Short Term ◽  
Packaging Process ◽  
Wafer Level Packaging

The wafer-level packaging process is an important technology used in semiconductor manufacturing, and how to effectively control this manufacturing system is thus an important issue for packaging firms. One way to aid in this process is to use a forecasting tool. However, the number of observations collected in the early stages of this process is usually too few to use with traditional forecasting techniques, and thus inaccurate results are obtained. One potential solution to this problem is the use of grey system theory, with its feature of small dataset modeling. This study thus uses the AGM(1,1) grey model to solve the problem of forecasting in the pilot run stage of the packaging process. The experimental results show that the grey approach is an appropriate and effective forecasting tool for use with small datasets and that it can be applied to improve the wafer-level packaging process.

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