Integration of Seasonal Autoregressive Integrated Moving Average and Bayesian Methods to Predict Production Throughput Under Random Variables

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Integration of Seasonal Autoregressive Integrated Moving Average and Bayesian Methods to Predict Production Throughput Under Random Variables

Analysing and modelling efforts on production throughput are getting more complex due to random variables in today’s dynamic production systems. The objective of this study is to take multiple random variables of production into account when aiming for production throughput with higher accuracy of...

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Bibliographic Details
Main Author:	Amir, Azizi
Format:	Article
Language:	English
Published:	Faculty Mechanical Engineering, UMP 2014
Subjects:	TS Manufactures
Online Access:	http://umpir.ump.edu.my/id/eprint/8238/ http://umpir.ump.edu.my/id/eprint/8238/1/Integration_of_Seasonal_Autoregressive_Integrated_Moving_Average_and_Bayesian_Methods_to_Predict_Production_Throughput_Under_Random_Variables.pdf

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