An Integrated Approach Based on SARIMA and Bayesian to Estimate Production Throughput under Five Random Variables
Analyzing and modeling efforts on production throughput are getting more complex due to random variables in todays dynamic production systems. The production line faces the changes in setup time, machinery break down, lead time of manufacturing, demand, and scraps. Bayesian approach is applied to ta...
Main Author: | Azizi, Amir |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/6050/ http://umpir.ump.edu.my/id/eprint/6050/1/fkp-2013-Amir-Integrated_Approach_BasedMUCET.pdf |
Similar Items
-
Integration of Seasonal Autoregressive Integrated Moving Average and Bayesian Methods to Predict Production Throughput Under Random Variables
by: Amir, Azizi
Published: (2014) -
Different Approaches to Overcome Uncertainties of Production Systems
by: Azizi, Amir, et al.
Published: (2014) -
Throughput enhancement of car exhaust fabrication line by applying MOST
by: Hanash, Ebrahim, et al.
Published: (2017) -
An Integrated Approach For Fatigue Life Estimation Based On Continuum Mechanics Theory And Genetic Algorithm
by: M., Kamal, et al.
Published: (2015) -
Jointness in Bayesian Variable Selection with Applications to Growth Regression
by: Ley, Eduardo, et al.
Published: (2012)