UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Volume 9 Issue 4
April-2022
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2204691


Registration ID:
400631

Page Number

g634-g639

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Title

Production Planning and Scheduling - A Data Mining Approach

Abstract

According to experience, raw material management is a major operational difficulty in the business. The importance of raw materials to the efficient operation of a manufacturing organization cannot be emphasized; the right quality and quantity are critical. Planning and production include determining the level of activity, turn-over, and final profit in a corporation, as well as minimum and maximum stock levels. Raw material management in a manufacturing organization requires specific care and scrutiny in order to achieve uninterrupted production cycles and better operational performance. Maintaining an acceptable stock level can also enhance the amount of available operating capital that can be put to better use. Material management is defined as the coordination of efforts (planning, managing, organizing, and directing) aimed at achieving efficiency in a manufacturing organization's procurement, transportation, stocking, and utilization of inputs. The effectiveness and efficiency of material management have a direct impact on the organization's overall success. This study provides a literature review on data mining definitions as well as a categorization of existing techniques to using data mining to manage production complexity in order to assist manufacturing organizations in implementing data mining.

Key Words

Data Mining, Hierarchical Clustering Algorithm and Association Rule

Cite This Article

"Production Planning and Scheduling - A Data Mining Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 4, page no.g634-g639, April-2022, Available :http://www.jetir.org/papers/JETIR2204691.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Production Planning and Scheduling - A Data Mining Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 4, page no. ppg634-g639, April-2022, Available at : http://www.jetir.org/papers/JETIR2204691.pdf

Publication Details

Published Paper ID: JETIR2204691
Registration ID: 400631
Published In: Volume 9 | Issue 4 | Year April-2022
DOI (Digital Object Identifier):
Page No: g634-g639
Country: Kolhapur, Maharashtra, India .
Area: Science & Technology
ISSN Number: 2349-5162
Publisher: IJ Publication


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