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Record W2749923249 · doi:10.5430/bmr.v6n3p1

Implementation of Transactional Planning Systems for the Plastics Industry

2017· article· en· W2749923249 on OpenAlexvenueno aff
Ana Eugenia Romo González, Angeles Villalobos-Alonzo

Bibliographic record

VenueBusiness and Management Research · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsnot available
Fundersnot available
KeywordsEnterprise resource planningProcess managementAgile software developmentPurchasingAutomationProduction planningTransactional analysisScheduleComputer scienceProcess (computing)Production (economics)Business processControl (management)Operations managementBusinessAutomotive industryManufacturing engineeringMarketingEngineeringWork in processSoftware engineeringEconomics

Abstract

fetched live from OpenAlex

Transactional systems are an alternative process improvement for any industrial sector; however, due to the rapid growth of the plastics industry worldwide, this industry requires the automation of production with agile systems. This document presents a procedure to implement transactional tools of the Master Production Schedule (MPS) and Materials Requirements Planning (MRP) for the automation and control of the operations area processes in an organization. These processes are part of Enterprise Resource Planning (ERP) tools that use connections to mobile devices and are often compatible with different customer support systems, allowing the integration of all business units to interact with the manufacturing control and purchasing. The method used in the research have a quantitative cut in which 15 companies were studied in the plastics sector in Mexico and was divided in three phases, these focused on the revision of the business processes and the analysis of the substantive processes of the organization that allowed the subsequent establishment of proposals for improvement. In the final proposal of implementation of the tool tansaccional included: the functional analysis of the systems, the planning and their evaluation.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.177
GPT teacher head0.414
Teacher spread0.237 · 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 designTheoretical or conceptual
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
Published2017
Admission routes1
Has abstractyes

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