Use of DMAIC to Elaborate a Proposal to Improve the Purchase Processes of the Material Department of the Federal University of Amazonas: A Study on Public Procurement Management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The public sector is a dynamic system composed of a web of tools and models for administrative and accounting management. In the midst of a tangle of processes, public procurement emerges as an important mechanism for the management, movement and application of financial resources destined to serve society. The purpose of this article is to present a proposal for a Manual of Procedures and Guidelines (MPG), aimed at promoting improvements to the public procurement process that is under the responsibility of the Material Department of the Federal University of Amazonas. The study methodology was developed from a bibliographic, documentary, and observational research, based on the application and analysis of the DMAIC tool. The study methodology was developed from a bibliographic, documentary, and observational research, based on the application and analysis of the DMAIC tool. The study presented as a result a viable proposal for improving procedures through the elaboration of a manual of rules and procedures for the optimization of public procurement management carried out by the materials department. The study presented as a result a viable proposal for improving procedures through the elaboration of a manual of rules and procedures for the optimization of public procurement management carried out by the materials department. It was concluded that greater efficiency in public procurement management is able to reduce expenses, allows the systematization of procedures and reduces the processing time of the purchase processes in their different phases until the purchase and availability of the purchased item to the requester.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it