MétaCan
Menu
← Back to cohort
Record W6990613882

DMS Fabshop Welding Streamlining

2021· report· en· W6990613882 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2021
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsWeldingScheduleRobot weldingPipingProcess (computing)WorkflowElectrogas weldingRetrofitting
DOInot available

Abstract

fetched live from OpenAlex

DMS Industrial Constructors is a fast-growing industrial contractor and one of the largest in Western Canada. DMS currently operates a fabshop for prefabrication of structural steel and piping components for its major projects. The current fabshop is reliant on solely manpower and utilizes underdeveloped welding equipment which results in slow manufacturing speed and welding inconsistencies. Aligned with DMS’s interest in continuous improvement, Team 10 has been tasked with improving the current welding process and streamlining the overall workflow by incorporating automated or semi-automated technology to a certain degree. The team is to focus on implementing design changes and analysis to improve the first stage welding aspect of DMS’s current workflow which involves circumference welding and welding of smaller pipe components. DMS has also outlined improving the current defect rate of 2%, and welding speeds of 20”- 25” and 40”- 60” per day for stainless steel and carbon steel pipes respectively. DMS has also specified that the recommended solution by the team should be capable of welding pipes ranging from 2” to 12” in diameter, Schedule 10 to Schedule 80 in thickness and up to 40ft in length. Also, the final design should comply with Canadian Standards Association (CSA) while staying within the $1,000,000 budget. The deliverables specified by DMS include a detailed cost summary, bill of materials, failure mode and effect analysis, supplier contact list, payback analysis, and construction drawings of the new system. To achieve a feasible solution, the welding process was broken down into 3 major systems based on functionality- Welding Robot, Turntable and Roller Stand. Various design concepts were researched, and a final concept that satisfies the needs and target requirement was selected. The selected welding system was the Spool Welding Robot (SWR) manufactured by Novarc Technologies which is adaptable to the existing turntables and has an interface to generate reports that keeps track of quality. The SWR also advertises a defect rate of less than 1% and a welding speed of 200”-350” and 569”– 998” per shift for carbon steel and stainless steel respectively. The current turntable is not efficient for pipes with diameters less than 4”. Therefore, the LJ welding 12P-900 portable turntable was selected to efficiently work with pipes with smaller diameters. Lastly, the HD2-300 roller stands also made by LJ welding was selected primarily because of its compatibility with the SWR and turntables. The final system will cost a sum of $607,184.00 which is within the $1,000,000 budget and will result in a 50% reduction in the current defect rate, more than 300% increase in the current welding speed for both stainless steel and carbon steel pipes. These improvements implies that the current workload can be completed in 76 days rather than 260 days for the existing system (240% improvement). A payback analysis on the system deduced that the payback period is 348 operational days with current workload.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.056
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0020.000
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0560.021

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 head0.051
GPT teacher head0.252
Teacher spread0.201 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueMspace (University of Manitoba)→French-language works237,207→