Evidence map›Paper›PMID 37258533›Full record

ArticleScientific reports2023

Adaptive elevator kinematics optimization based dual response algorithm for determining proper levels in plaster milling process parameters.

Pongchanun Luangpaiboon, Sirirat Juttijudata

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Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Pongchanun LuangpaiboonThammasat University Research Unit in Industrial Statistics and Operational Research, Faculty of Engineering, Thammasat School of Engineering, Thammasat University, Pathumthani, 12120, Thailand.ORCID http://orcid.org/0000-0002-4155-0688
Sirirat JuttijudataIndustrial and Production Management Research Unit, Faculty of Engineering at Sriracha, Kasetsart Univeristy Sriracha Campus, Chonburi, 20230, Thailand. sirirat@eng.src.ku.ac.th.ORCID http://orcid.org/0000-0001-8250-2298

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study proposes a novel hybrid approach, called Adaptive/Elevator Kinematics Optimization algorithm based on dual response algorithm (A/EKO-DRA), to enhance the robust parameters estimation and design of the plaster milling process. The A/EKO-DRA method reduces variability while maintaining the desired output target, thereby minimizing the impact of variance on the expected stucco combined water. The performance of the A/EKO-DRA is compared with conventional processes through numerical examples and simulations. The results show that the A/EKO-DRA method has the lowest mean absolute errors among other methods in terms of parameter estimation, and it achieves the response mean of 5.927 percent, which meets the target value of 5.9 percent for industrial enclosures, with much reduction in the response variance. Overall, the A/EKO-DRA method is a promising approach for optimizing the plaster milling process parameters.

Identifiers

PMID37258533
PMCPMC10232522

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.