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Record W4225575528 · doi:10.31963/sinergi.v19i2.3387

Rancang Bangun Mesin Injeksi Plastik dengan Sistem Penekan Pneumatik

2021· article· en· W4225575528 on OpenAlexaff
Ahmad Zubair Sultan, Muh Arsyad Suyuti, Muh Devo Alfara, Muh. Asrul Adhani Yunus, Mujahid Ikhlasul Amal

Bibliographic record

VenueJurnal Teknik Mesin Sinergi · 2021
Typearticle
Languageen
FieldEngineering
TopicEngineering and Technology Innovations
Canadian institutionsHusky Injection Molding Systems (Canada)
Fundersnot available
KeywordsPressingPneumatic cylinderInjection molding machineWaste managementPlastic bagEnvironmental scienceMaterials scienceBar (unit)LeverProcess engineeringCylinderMechanical engineeringEngineeringComposite materialMoldGeology

Abstract

fetched live from OpenAlex

Trash is waste that is produced from a production process, both industrial and household in the form of solid or semi-solid in the form of organic or inorganic substances which are biodegradable or non-biodegradable which are deemed useless and disposed of into the environment. The disposal of waste, such as the increasing number of plastics, provides benefits for plastic recycling craftsmen so that a plastic smelter is needed to make various forms of molds (molds). Injection Molding is one of the techniques used in producing plastics and this process is among the most cost efficient to produce printed objects / products. But in general, most of these techniques still use a manual system, namely using a lever as a pressure in printing (vertical form). We tried to make a plastic injection machine with ashape horizontal and use a pneumatic cylinder as the actuator for pressing. Design of Plastic Injection Machines with a Pneumatic Pressing system with LDPE type plastic test materials, using 8 bar pressure and 690 watts ofband heater elements

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.184
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2021
Admission routes1
Has abstractyes

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