Order Pattern Prediction Using Artificial Intelligence In An Inventory System Design

Achieving smmooth production is one of the major concern by the manufacturing industry. In order to have smooth production, waste must be avoided. Furthermore, the cost of investment in production can be high with contribution of Wasted activities especially high inventory management cost. Economic...

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Main Author:	Mohd Arshad, Nor Amirah
Format:	Thesis
Language:	English English
Published:	2016
Subjects:	T Technology (General) TS Manufactures
Online Access:	http://eprints.utem.edu.my/id/eprint/20764/1/Order%20Pattern%20Prediction%20Using%20Artificial%20Intelligence%20In%20An%20Inventory%20System%20Design%20-%20Nor%20Amirah%20Mohd%20Arshad%20-%2024%20Pages.pdf http://eprints.utem.edu.my/id/eprint/20764/2/Order%20Pattern%20Prediction%20Using%20Artificial%20Intelligence%20In%20An%20Inventory%20System%20Design%20-%20Nor%20Amirah%20Mohd%20Arshad.pdf
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id	my-utem-ep.20764
record_format	uketd_dc
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
topic	T Technology (General) TS Manufactures
spellingShingle	T Technology (General) TS Manufactures Mohd Arshad, Nor Amirah Order Pattern Prediction Using Artificial Intelligence In An Inventory System Design
description	Achieving smmooth production is one of the major concern by the manufacturing industry. In order to have smooth production, waste must be avoided. Furthermore, the cost of investment in production can be high with contribution of Wasted activities especially high inventory management cost. Economic Order Quantity (EOQ) has been applied in inventory management in order to determine economic lot size. However, EOQ has limitation due to uncertain situation. Thus, the aim of this study to reduce cost investment in inventory. This study has three objectives, (1) to investigate ordering pattern ordering pattern which is affected the inventory, (2) to propose order pattern in inventory using ANFIS and (3) to evaluate proposed order pattern with cost investment. The study was conducted based on case study at the furniture company. The historical data of demand and supply was provided for 52 weeks. Firstly, the inventory level was investigated with the historical data based on stochastic EOQ model. From the investigation, shortage occurred because order does not make for a long time. Hence, the total cost of inventory was high. Then, investigated order pattern using Fuzzy Inference System and shortage still occurred. Thus, manual prediction order pattern was developed which to ensure the inventory just below reorder point. This purposed to ensure that every week order was took placed and shortage was avoided. Adaptive Neuro Fuzzy Inference System was used in order to find the parameters in forecasting the order quantity. The result showed that the proposed order pattern can avoid shortage and every week the inventory is below reorder point. Every week order is take place. Also, the total cost is reduced since no shortage occurs.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Mohd Arshad, Nor Amirah
author_facet	Mohd Arshad, Nor Amirah
author_sort	Mohd Arshad, Nor Amirah
title	Order Pattern Prediction Using Artificial Intelligence In An Inventory System Design
title_short	Order Pattern Prediction Using Artificial Intelligence In An Inventory System Design
title_full	Order Pattern Prediction Using Artificial Intelligence In An Inventory System Design
title_fullStr	Order Pattern Prediction Using Artificial Intelligence In An Inventory System Design
title_full_unstemmed	Order Pattern Prediction Using Artificial Intelligence In An Inventory System Design
title_sort	order pattern prediction using artificial intelligence in an inventory system design
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Manufacturing Engineering
publishDate	2016
url	http://eprints.utem.edu.my/id/eprint/20764/1/Order%20Pattern%20Prediction%20Using%20Artificial%20Intelligence%20In%20An%20Inventory%20System%20Design%20-%20Nor%20Amirah%20Mohd%20Arshad%20-%2024%20Pages.pdf http://eprints.utem.edu.my/id/eprint/20764/2/Order%20Pattern%20Prediction%20Using%20Artificial%20Intelligence%20In%20An%20Inventory%20System%20Design%20-%20Nor%20Amirah%20Mohd%20Arshad.pdf
_version_	1747834001780899840
spelling	my-utem-ep.207642021-10-08T16:51:27Z Order Pattern Prediction Using Artificial Intelligence In An Inventory System Design 2016 Mohd Arshad, Nor Amirah T Technology (General) TS Manufactures Achieving smmooth production is one of the major concern by the manufacturing industry. In order to have smooth production, waste must be avoided. Furthermore, the cost of investment in production can be high with contribution of Wasted activities especially high inventory management cost. Economic Order Quantity (EOQ) has been applied in inventory management in order to determine economic lot size. However, EOQ has limitation due to uncertain situation. Thus, the aim of this study to reduce cost investment in inventory. This study has three objectives, (1) to investigate ordering pattern ordering pattern which is affected the inventory, (2) to propose order pattern in inventory using ANFIS and (3) to evaluate proposed order pattern with cost investment. The study was conducted based on case study at the furniture company. The historical data of demand and supply was provided for 52 weeks. Firstly, the inventory level was investigated with the historical data based on stochastic EOQ model. From the investigation, shortage occurred because order does not make for a long time. Hence, the total cost of inventory was high. Then, investigated order pattern using Fuzzy Inference System and shortage still occurred. Thus, manual prediction order pattern was developed which to ensure the inventory just below reorder point. This purposed to ensure that every week order was took placed and shortage was avoided. Adaptive Neuro Fuzzy Inference System was used in order to find the parameters in forecasting the order quantity. The result showed that the proposed order pattern can avoid shortage and every week the inventory is below reorder point. Every week order is take place. Also, the total cost is reduced since no shortage occurs. 2016 Thesis http://eprints.utem.edu.my/id/eprint/20764/ http://eprints.utem.edu.my/id/eprint/20764/1/Order%20Pattern%20Prediction%20Using%20Artificial%20Intelligence%20In%20An%20Inventory%20System%20Design%20-%20Nor%20Amirah%20Mohd%20Arshad%20-%2024%20Pages.pdf text en public http://eprints.utem.edu.my/id/eprint/20764/2/Order%20Pattern%20Prediction%20Using%20Artificial%20Intelligence%20In%20An%20Inventory%20System%20Design%20-%20Nor%20Amirah%20Mohd%20Arshad.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=104944 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Manufacturing Engineering 1. Aengchuan, P., and Phruksaphanrat, B., 2013. Inventory System Design by Fuzzy Logic Control: A Case Study. Advanced Materials Research, 811, pp. 619–624. 2. Aengchuan, P., and Phruksaphanrat, B., 2015. 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Order Pattern Prediction Using Artificial Intelligence In An Inventory System Design

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