MétaCan
Menu
Back to cohort
Record W2141557867 · doi:10.5897/sre.9000445

Electrostatic discharge (ESD) improvement to reduce customer complaint

2010· article· en· W2141557867 on OpenAlexaboutno aff
Muhd Ambri Rahman, Faieza Abdul Aziz

Bibliographic record

VenueUniversiti Putra Malaysia Institutional Repository (Universiti Putra Malaysia) · 2010
Typearticle
Languageen
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsnot available
Fundersnot available
KeywordsComplaintElectrostatic dischargeAutomotive industryReputationCustomer satisfactionProduct (mathematics)Quarter (Canadian coin)Automotive engineeringEngineeringBusinessElectrical engineeringMarketingVoltage

Abstract

fetched live from OpenAlex

Electrostatic discharge (ESD) / electrical over stress (EOS) factors cannot be avoided when an organization running daily manufacturing activity. ESD problems are increasing in the electronics industry because of the trends toward higher speed and smaller device sizes which normally these devices are easy to be damaged by ESD. One of the manufacturing company in Malaysia which produces car radio is also facing the same problem. The failure trend related to ESD is become an alarming condition at 0 km (the product still at automotive customer assembly - 0 mileages which the vehicle is not yet sell to end user). In this study, the problem related to ESD and improvement to reduce the failure were conducted. These includes improvements in ESD protection and control which minimize yield losses and 0 km failures, and maintain the company reputation as a supplier of high-quality and reliable products. Findings from this study showed that virtually all materials, even conductors, can be triboelectrically charges. The level of charge is affected by material, speed of contact, separation and humidity. Electrostatic discharge can occur throughout the manufacturing test, handling and operational process. The improvement activity consist of two phases which is 3rd quarter 2009 (July – September) and 4th quarter 2009 (October – November). This followed by the continuous improvement activity take place on the 1st quarter 2010 (January – March). With this improvement, failure trend at customer related to ESD showed a reducing pattern.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.327
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.005
GPT teacher head0.194
Teacher spread0.189 · 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 teacher head, not a consensus.

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

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueUniversiti Putra Malaysia Institutional Repository (Universiti Putra Malaysia)Same topicElectrostatic Discharge in ElectronicsFrench-language works237,207