Evidence map›Paper›PMID 39691792›Full record

ArticleMethodsX2024

A combined DEAV-BWM approach for effective evaluation and ranking of biomass materials in charcoal briquette production.

Narong Wichapa, Pariwat Nasawat, Nattapat Kanchanaruangrong, Atchara Choompol

Abstract read
In one paragraph

Article in MethodsX, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Narong WichapaDepartment of Industrial Engineering, Faculty of Engineering and Industrial Technology, Kalasin University, Kalasin 46000, Thailand.
Pariwat NasawatDepartment of Logistics and Process Engineering, Faculty of Industrial Technology, Rajabhat Rajanagarindra University, 24000, Thailand.
Nattapat KanchanaruangrongDepartment of Industrial Management Engineering, Faculty of Industrial Technology, Rajabhat Rajanagarindra University, 24000, Thailand.
Atchara ChoompolDepartment of Computer Engineering, Faculty of Engineering and Industrial Technology, Kalasin University, Kalasin 46000, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The utilization of agricultural waste for producing charcoal briquettes is gaining significant attention as a sustainable alternative energy source. Converting these residues into charcoal briquettes not only addresses energy shortages but also provides an efficient solution for managing agricultural waste, contributing to environmental sustainability. This study proposes a novel methodology integrating a Data Envelopment Analysis Variant (DEAV) with the Best-Worst Method (BWM) to assess and rank biomass materials for charcoal briquette production. The DEAV-BWM model enhances the evaluation process by considering multiple criteria simultaneously and incorporating both efficiency and consensus among different evaluation methods. The key highlights of the methodology are as follows:•A novel method, called the DEAV model, for evaluating efficiency scores has been established, incorporating both Data Envelopment Analysis (DEA) and Multi-Attribute Decision Making (MADM) concepts.•This paper introduces a novel hybrid method that combines the DEAV model with the BWM to evaluate and rank biomass materials for charcoal briquette production, enhancing the reliability and robustness of the decision-making process.•The proposed method can be adapted and applied to other areas of biomass utilization and beyond, providing a versatile tool for researchers and practitioners in the field of sustainable energy, engineering, and operations research.

Indexed as

Best-worst methodBiomassCharcoal briquetteData envelopment analysisData envelopment analysis variantMethod of integrating a novel Data Envelopment Analysis Variant (DEAV) model, and Best-Worst Method (BWM) for assessing the potential of biomass materials in charcoal briquette productionMulti-attribute decision making

Identifiers

PMID39691792
PMCPMC11650255

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LicenceCC BY
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Registered trials

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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.