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Record W3026419347

Design of a coin roll check weighing system

2012· article· en· W3026419347 on OpenAlexaboutno aff
Kevin Harder, Christopher Jack, Shadi Radwan, Gelleen Sicat

Bibliographic record

VenueMspace (University of Manitoba) · 2012
Typearticle
Languageen
FieldEngineering
TopicTransport Systems and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this report is to detail the design and analysis of a coin roll check weighing system for the Royal Canadian Mint. The intent of this system is to check the number of coins per wrapped roll, reject if needed, and output onto the tiling machine conveyor. This system is required due to newly contracted coin production that requires coin rolls to check weighed. For our design, we choose to solve this problem, using off-the-shelf components and prototyped models. To begin the check weighing system design, we recommended using the original attachments on the current four wrapping machines. After this attachment, our team prototyped a roll reorientation slide and buffer mechanism. The re-orientation slide rotates the rolls 90° and outputs them onto the buffer attachments. Once the roll is queued on the buffer attachment a buffer drop mechanism is used to output a single when signalled by a photoelectric sensor along the main conveyor. These sensors detect openings along the belt between the four wrappers for coin rolls to be dropped. We recommend using the E3H2 Miniature photoelectric sensors from Omron to complete this task. After the roll is dropped, it will begin moving towards the check weighing station. To complete this motion, two narrow flat belt conveyors from Mini Mover Conveyors were selected. These conveyors consist of a horizontal main conveyor under the buffer mechanism and an inclined conveyor to carry the roll up to the check weighing station. To ensure the rolls maintain the correct orientation during transport, adjustable side rail guides from Mini Mover Conveyors were selected. In order to optimize the use of the conveyors with different sized rolls, each conveyor section was fitted with a variable speed drive motor, also from Mini Mover Conveyors. In order check weigh each coin roll after wrapping, an Ishida DASC-G-S015-12-SS check weigher was selected. This check weigher is able to process up to 400 items per minute with accuracy of 0.1 grams. These specifications, along with others, are more than adequate for the Mint requirements. Not only does this system include check weighing but also user defined software and a rejection system. Since these components are all integrated into a single station, the check weighing machine is capable of recording weighing data and outputting in RS232 format. The rejection system is also capable of not only rejecting faulty rolls, but also alerting the operator and stopping the process after 10 consecutive rolls have been rejected. Following the check weighing the station, the coin rolls travel onto a final alignment conveyor, where similar used on the main and inclined conveyor, that re-aligns the coin rolls for the roll transfer attachment. This conveyor, guides, and motor were obtained from Mini Mover Conveyors as well. Finally, after the rolls have been re-aligned, they are dropped onto the tiling conveyor using a prototype roll transfer attachment. This attachment is designed to be adjusted for different roll diameters and lengths to ensure the correct roll orientation onto the tiling conveyor. Lastly, a cost analysis was performed for procuring the commercially available components and manufacturing the prototype components. The total cost of the system came out to be $62.441.86. It should be noted that this cost does not included prototype development and setup costs. This constraint, along with the floor space size, output height, and power methods were all met with our system. The total floor space size for our designed check weighing system was 5.46 feet long by 2.2 feet wide and the output height to the tiling conveyor is 34.75 inches from the roll transfer attachment.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0130.004

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 head0.013
GPT teacher head0.155
Teacher spread0.142 · 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 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
Published2012
Admission routes1
Has abstractyes

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