Data analysis and machine learning-based modeling for real-time production
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2023.14.2.22Keywords:
Machine Learning, Data Analysis, Manufacturing Industry, Real-time data modeling.Dimensions Badge
Issue
Section
License
Copyright (c) 2023 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This article primarily focuses on data analysis and real time data modelling using linear regression and decision tree algorithm that might make revolutionary prediction on production data. Factual time data points include temperature, load, warning, on all the presented axis are the dependent parameters which be contingent on the changes in the autonomous paraments like load. Monitoring and innovative prediction is very much needed in industry as there are recurrent load changes that would create an data drift and in term of maintenance that could impact the production side as need of continues monitoring and control machine learning based approaches would work better on these real time production datasets.Abstract
How to Cite
Downloads
Similar Articles
- Naresh Vyas, Bhagirath Choudhary, Manu Purohit, Community Analysis of Plant Parasitic Nematodes in and Around Bilara, Rajasthan , The Scientific Temper: Vol. 13 No. 01 (2022): The Scientific Temper
- G. Hemamalini, V. Maniraj, Enhanced otpmization based support vector machine classification approach for the detection of knee arthritis , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Hariini Chandramohan, Sethu Gunasekaran, Comparative analysis on the photocatalytic activity of titania and silica nanoparticles using dye discoloration and contact angle test , The Scientific Temper: Vol. 16 No. 01 (2025): The Scientific Temper
- Maria D. Roopa, Nimitha John, Bayesian Optimization Phase I Design of Experiment Models , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Pooja Soni, Vikramaditya Dave, Sujit Kumar, Hemani Paliwal, A comparative study of AI-driven techno-economic analysis for grid-tied solar PV-fuel cell hybrid power systems , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- A. Rukmani, C. Jayanthi, Fuzzy optimization trust aware clustering approach for the detection of malicious node in the wireless sensor networks , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- U. Johns Praveena, J. Merline Vinotha, The multi-objective solid transshipment problem with preservation technology under fuzzy environment , The Scientific Temper: Vol. 16 No. 01 (2025): The Scientific Temper
- Harsha, Alwin S. Kumar, Srihari Jwalapuram, Sravan Kumar, Marketing strategies in the pharmaceutical industry , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Shivali Kundan, Neha Verma, Zahid Nabi, Dinesh Kumar, Satellite radiance assimilation using the 3D-var technique for the heavy rainfall over the Indian region , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper
- Himadri Nalinkumar Raval, Effective strategies in English language teaching: Enhancing writing proficiency among learners , The Scientific Temper: Vol. 16 No. 03 (2025): The Scientific Temper
<< < 34 35 36 37 38 39 40 41 42 43 > >>
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- S. C. Prabha, P. Sivaraaj, S. Kantha Lakshmi, Data analysis and machine learning-based modeling for real-time production , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper

