Evidence map›Paper›PMID 38610535›Full record

ReviewSensors (Basel, Switzerland)2024

Cyber-Physical Systems for High-Performance Machining of Difficult to Cut Materials in I5.0 Era-A Review.

Hossein Gohari, Mahmoud Hassan, Bin Shi, Ahmad Sadek, Helmi Attia, Rachid M'Saoubi

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Hossein GohariDepartment of Mechanical Engineering, McGill University, Montreal, QC H3A 0G4, Canada.
Mahmoud HassanAerospace Manufacturing Technologies Center (AMTC), National Research Council Canada, Montreal, QC H3T 1J4, Canada.
Bin ShiAerospace Manufacturing Technologies Center (AMTC), National Research Council Canada, Montreal, QC H3T 1J4, Canada.
Ahmad SadekAerospace Manufacturing Technologies Center (AMTC), National Research Council Canada, Montreal, QC H3T 1J4, Canada.
Helmi AttiaDepartment of Mechanical Engineering, McGill University, Montreal, QC H3A 0G4, Canada.ORCID 0000-0002-4705-5311
Rachid M'SaoubiR&D Material and Technology Development, Seco Tools AB, SE-73782 Fagersta, Sweden.

Funding

Mitacs IT21722Natural Sciences and Engineering Research Council RGPIN-2020-06223
6 · The paper itself

Abstract

The fifth Industrial revolution (I5.0) prioritizes resilience and sustainability, integrating cognitive cyber-physical systems and advanced technologies to enhance machining processes. Numerous research studies have been conducted to optimize machining operations by identifying and reducing sources of uncertainty and estimating the optimal cutting parameters. Virtual modeling and Tool Condition Monitoring (TCM) methodologies have been developed to assess the cutting states during machining processes. With a precise estimation of cutting states, the safety margin necessary to deal with uncertainties can be reduced, resulting in improved process productivity. This paper reviews the recent advances in high-performance machining systems, with a focus on cyber-physical models developed for the cutting operation of difficult-to-cut materials using cemented carbide tools. An overview of the literature and background on the advances in offline and online process optimization approaches are presented. Process optimization objectives such as tool life utilization, dynamic stability, enhanced productivity, improved machined part quality, reduced energy consumption, and carbon emissions are independently investigated for these offline and online optimization methods. Addressing the critical objectives and constraints prevalent in industrial applications, this paper explores the challenges and opportunities inherent to developing a robust cyber-physical optimization system.

Indexed as

adaptive controlcyber–physical systemsfinite element analysisindustry 5.0process optimization

Identifiers

PMID38610535
PMCPMC11014020

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.