Evidence map›Paper›PMID 40479467›Full record

ArticleInternational journal on interactive design and manufacturing2023

Optimal reliability allocation of heterogeneous components in pharmaceutical production plant.

Ibrahim Aqel, Mohamed Arezki Mellal

Abstract read
In one paragraph

Article in International journal on interactive design and manufacturing, 2023. 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
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 authors.

Ibrahim AqelLMSS, Faculty of Technology, M'Hamed Bougara University, Boumerdes, Algeria.
Mohamed Arezki MellalLMSS, Faculty of Technology, M'Hamed Bougara University, Boumerdes, Algeria.ORCID 0000-0003-0667-8851

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic and competitiveness pressure the pharmaceutical companies to acquire systems designed to be as reliable as possible. The present paper aims to optimize the design of a pharmaceutical plant through the reliability allocation of heterogeneous components under the design constraints. The problem is solved by resorting to three nature-inspired algorithms of artificial intelligence (AI): grey wolf optimizer (GWO), shuffled frog-leaping algorithm (SFLA), and adaptive particle swarm optimization (ADAP-PSO). A penalty function is implemented to handle the constraints and the results obtained are compared. Supplementary Information: The online version contains supplementary material available at 10.1007/s12008-023-01256-1.

Indexed as

COVID-19Grey wolf optimizer-shuffled frog-leaping algorithm-adaptive particle swarm optimizationHeterogeneous componentsPharmaceutical plantReliability allocation

Identifiers

PMID40479467
PMCPMC9975440

What OpenQuestion holds

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Registered trials

None linked

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.