UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 8 Issue 5
April-2021
eISSN: 2349-5162

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

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Published Paper ID:
JETIRER06008


Registration ID:
308625

Page Number

32-35

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Title

A STUDY ON MANPOWER REQUIRMENTS IN PRODUCTION USING PREDECTIVE ANALYSIS

Abstract

The Supply chain management is the management of the flow of goods and services and includes all processes that transform raw materials into final products. Predictive analytics is that the use of knowledge, statistical algorithms and machine learning techniques to spot the likelihood of future outcomes supported historical data. The main objective of this paper is man power planning which involves reviewing current manpower resources, forecasting future requirements and availability, and taking steps to ensure that the supply of people and skills meets demand.

Key Words

Predictive analysis, Linear regression.

Cite This Article

" A STUDY ON MANPOWER REQUIRMENTS IN PRODUCTION USING PREDECTIVE ANALYSIS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.32-35, April-2021, Available :http://www.jetir.org/papers/JETIRER06008.pdf

ISSN


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

" A STUDY ON MANPOWER REQUIRMENTS IN PRODUCTION USING PREDECTIVE ANALYSIS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. pp32-35, April-2021, Available at : http://www.jetir.org/papers/JETIRER06008.pdf

Publication Details

Published Paper ID: JETIRER06008
Registration ID: 308625
Published In: Volume 8 | Issue 5 | Year April-2021
DOI (Digital Object Identifier):
Page No: 32-35
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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