Determining optimal process mean for small and medium juice processing industries using markovian model

The determination of process mean is important in industries especially for items that governed by laws and regulations on net content labelling. Thus, the economic selection of optimum process mean is critically significant since it will directly affect the quality characteristic of item. By assumi...

Full description

Saved in:
Bibliographic Details
Main Author: Razali, Hazlina
Format: Thesis
Language:English
English
Published: 2014
Subjects:
Online Access:http://eprints.utem.edu.my/id/eprint/16866/1/Determining%20Optimal%20Process%20Mean%20For%20Small%20And%20Medium%20Juice%20Processing%20Industries%20Using%20Markovian%20Model.pdf
http://eprints.utem.edu.my/id/eprint/16866/2/Determining%20optimal%20process%20mean%20for%20small%20and%20medium%20juice%20processing%20industries%20using%20markovian%20model.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-utem-ep.16866
record_format uketd_dc
spelling my-utem-ep.168662022-09-27T14:36:33Z Determining optimal process mean for small and medium juice processing industries using markovian model 2014 Razali, Hazlina T Technology (General) TP Chemical technology The determination of process mean is important in industries especially for items that governed by laws and regulations on net content labelling. Thus, the economic selection of optimum process mean is critically significant since it will directly affect the quality characteristic of item. By assuming the quality characteristic is normally distributed, an item that undergoes the juice filling in the container can be classified as accepted product, under-filled or over-filled by the system which is successfully transform to the finishing product. This research is focused on the setting of process mean in juice processing industries, especially before production starts as it is important in order to produce an item that fulfil within the specification limit with the aim of gaining the maximum profit. Moreover the determination of optimal mean value involves a complex decisions and small and medium enterprises (SME’s) constraint is especially in financial point of view. The Markovian model is chosen as it considers the long-term probabilities in dynamic system. In this research, the analysis of selecting the process mean of juice filling in the bottle in the SME production is presented. Three main objectives are stated, namely, to propose a Markovian model for mean value estimation as a main parameter estimation of expected profit estimation, to simplify the process of selecting optimal mean value estimation in Markovian model using quartile-based method and to evaluate the performance of Markovian model using iteration rate for estimation in juice processing industries. The process of juice filling from the raw materials until end products is developed based on the single-stage process. The Markovian model that considered the under-filled and over-filled products is proposed in the study. By varying the under-filled and over-filled cost, the analysis shows the significant results of Markovian model to determine process mean which maximizes the expected profit per item. The simplification method of targeting process mean by using quartile-based is also performed in order to reduce and minimize the searching iteration process of optimal mean. The variation of juice minimum volume in the bottle is set from 1% to 10% lower than upper limit value of each bottle that available in the market. The variation is needed in order to evaluate the trends of process mean determination. The main contribution of this research is the Markovian model that is used in juice processing industries, which refer to the accepted bottles, under-filled bottles and over-filled bottles. From the different state of finished product, the determination of optimal process mean is referred to the maximum profit gained. Besides, the simplification method of searching the optimal process mean has shown a significant outcomes which reduce and minimize the iteration process. By varying the lower limit of amount in the bottle, one can see the trends of optimal process mean and yet use the variation as a guide to set the process mean before start the juice filling process. 2014 Thesis http://eprints.utem.edu.my/id/eprint/16866/ http://eprints.utem.edu.my/id/eprint/16866/1/Determining%20Optimal%20Process%20Mean%20For%20Small%20And%20Medium%20Juice%20Processing%20Industries%20Using%20Markovian%20Model.pdf text en public http://eprints.utem.edu.my/id/eprint/16866/2/Determining%20optimal%20process%20mean%20for%20small%20and%20medium%20juice%20processing%20industries%20using%20markovian%20model.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=96164 mphil masters Universiti Teknikal Malaysia Melaka Faculty Of Information And Communication Technology Hasan Basari, Abd Samad
institution Universiti Teknikal Malaysia Melaka
collection UTeM Repository
language English
English
advisor Hasan Basari, Abd Samad
topic T Technology (General)
TP Chemical technology
spellingShingle T Technology (General)
TP Chemical technology
Razali, Hazlina
Determining optimal process mean for small and medium juice processing industries using markovian model
description The determination of process mean is important in industries especially for items that governed by laws and regulations on net content labelling. Thus, the economic selection of optimum process mean is critically significant since it will directly affect the quality characteristic of item. By assuming the quality characteristic is normally distributed, an item that undergoes the juice filling in the container can be classified as accepted product, under-filled or over-filled by the system which is successfully transform to the finishing product. This research is focused on the setting of process mean in juice processing industries, especially before production starts as it is important in order to produce an item that fulfil within the specification limit with the aim of gaining the maximum profit. Moreover the determination of optimal mean value involves a complex decisions and small and medium enterprises (SME’s) constraint is especially in financial point of view. The Markovian model is chosen as it considers the long-term probabilities in dynamic system. In this research, the analysis of selecting the process mean of juice filling in the bottle in the SME production is presented. Three main objectives are stated, namely, to propose a Markovian model for mean value estimation as a main parameter estimation of expected profit estimation, to simplify the process of selecting optimal mean value estimation in Markovian model using quartile-based method and to evaluate the performance of Markovian model using iteration rate for estimation in juice processing industries. The process of juice filling from the raw materials until end products is developed based on the single-stage process. The Markovian model that considered the under-filled and over-filled products is proposed in the study. By varying the under-filled and over-filled cost, the analysis shows the significant results of Markovian model to determine process mean which maximizes the expected profit per item. The simplification method of targeting process mean by using quartile-based is also performed in order to reduce and minimize the searching iteration process of optimal mean. The variation of juice minimum volume in the bottle is set from 1% to 10% lower than upper limit value of each bottle that available in the market. The variation is needed in order to evaluate the trends of process mean determination. The main contribution of this research is the Markovian model that is used in juice processing industries, which refer to the accepted bottles, under-filled bottles and over-filled bottles. From the different state of finished product, the determination of optimal process mean is referred to the maximum profit gained. Besides, the simplification method of searching the optimal process mean has shown a significant outcomes which reduce and minimize the iteration process. By varying the lower limit of amount in the bottle, one can see the trends of optimal process mean and yet use the variation as a guide to set the process mean before start the juice filling process.
format Thesis
qualification_name Master of Philosophy (M.Phil.)
qualification_level Master's degree
author Razali, Hazlina
author_facet Razali, Hazlina
author_sort Razali, Hazlina
title Determining optimal process mean for small and medium juice processing industries using markovian model
title_short Determining optimal process mean for small and medium juice processing industries using markovian model
title_full Determining optimal process mean for small and medium juice processing industries using markovian model
title_fullStr Determining optimal process mean for small and medium juice processing industries using markovian model
title_full_unstemmed Determining optimal process mean for small and medium juice processing industries using markovian model
title_sort determining optimal process mean for small and medium juice processing industries using markovian model
granting_institution Universiti Teknikal Malaysia Melaka
granting_department Faculty Of Information And Communication Technology
publishDate 2014
url http://eprints.utem.edu.my/id/eprint/16866/1/Determining%20Optimal%20Process%20Mean%20For%20Small%20And%20Medium%20Juice%20Processing%20Industries%20Using%20Markovian%20Model.pdf
http://eprints.utem.edu.my/id/eprint/16866/2/Determining%20optimal%20process%20mean%20for%20small%20and%20medium%20juice%20processing%20industries%20using%20markovian%20model.pdf
_version_ 1747833903863824384