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Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS)

ISSN:2141-7016

Article Title: Optimization of Effective Inventory Control and Management in Manufacturing Industries: Case Study of Flour Mills Company Calabar, Nigeria
by Stephen. A. Takim

Abstract:
For various manufacturing industries in Nigeria, inventory remains the prevalent asset on the balance sheet at any given time; therefore, there is the need for it to be properly managed. The researcher identifies some of the challenges hindering effective inventory management and control using Flour Mills Company as a case study. Although, effectiveness was seen in this research as the ability to achieve stated inventory levels, judge in terms of financial measures like inventory turnover. And for any company to claim to be effective, it inventory management decisions made by management must be ascertained and certified. The key source of information gathering which the research employed was the used of primary data through a well structured questionnaires and personal interviews. The data so obtain was analyse through qualitative technique, using descriptive statistics method by quantifying the level of frequency and determining the percentages of respondents and weighted mean scores. This method was considered more appropriate and convenient by the author because it helps to establish the objectives of the research. The results has help to proffer solution to the problem of lead time of delivery or delay in supply of goods or material, the interruption in production and stock out of goods or materials during production and problem of when to order and how much to order as it affects manufacturing industries in Nigeria. Conclusions were drawn and recommendations was made for the best practices that will ensure effective inventory control of stock and customers satisfaction and retention in both public and private industries in Nigeria.
Keywords: effective, optimization, inventory, manufacturing, flour mills
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ISSN: 2141-7016

Editor in Chief.

Prof. Gui Yun Tian
Professor of Sensor Technologies
School of Electrical, Electronic and Computer Engineering
University of Newcastle
United Kingdom

 

 

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