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Record W7054863979

Automated Pizza Pop Rack Mover

2020· report· en· W7054863979 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2020
Typereport
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsTrayRackAutomationLoaderProcess (computing)Work (physics)Head (geology)Table (database)Pneumatic cylinder
DOInot available

Abstract

fetched live from OpenAlex

The General Mills Pizza Pop facility located in Winnipeg, Manitoba, is the sole producer of Pizza Pops throughout all of Canada. With such high demand, it is critical to ensure all manufacturing processes are analyzed and optimized in search of improvement. However, when it comes to the manufacturing capabilities of manual labour, limitations such as strain injuries and harsh temperature arise. Therefore, to increase both human safety and manufacturing throughput, automation can be implemented. The scope of this design is contained from where the Pizza Pops begin getting placed on trays to where the Pizza Pops get taken to the packaging line. This process is very manual and requires the support of 5 operators. For one process, where an operator moves racks within a freezer, the work environment is challenging as the temperature is regulated at around -12° F. General Mills is looking to reduce these manual tasks through automation while only requiring 1 operator. This report performs a detailed analysis on implementing a fully automated system for tray loading, rack transportation, and Pizza Pop freezing. For the tray loading category, a dual head elevator is used to load two trays into a single rack at a time. The dual head was required to meet the current throughput of 17 trays per minute and can load up to 18.5 trays per minute. The racks are automatically indexed for the tray loader to keep supplying racks when they become full. For rack transportation, an AGV will driven under the racks, engage with a connection bar and then transport the rack to the desired location. An embedded magnetic strip path will be placed through out the area to provide a path for the AGV's to follow. It was found that a total of 3 AGV's continuously operating are needed to meet the required throughput time. However, more AGV's can be added in the future if an increase in throughput exceeds the capability of 3 AGV's. Lastly, upon further analysis of the freezer, it was determined that AGV's alone inside the freezer would be insufficient. Therefore, an indexing rail system was developed to operate inside the freezer, capable of moving racks quickly and efficiently. Racks are loaded into each rail via an AGV and engage with the rail latching mechanism. This latch is powered by an electric pulley system and is responsible for bringing the racks up to the front of the freezer. There are a total of 9 indexing lanes, each with an 8 rack capacity, allowing a max of 72 racks in the freezer. A cost breakdown has been provided to detail how much each individual system will cost, including operational and preventative maintenance costs. For the overall system to be installed, it is estimated to cost approximately $996,000 CAD. In summary, this automated system has been proven feasible within the General Mills facility. The design meets and exceeds throughput, reduces required employees from 5 to 1, and increases employee health and safety.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.887
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.025
GPT teacher head0.209
Teacher spread0.185 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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