akitek - technical paper on foreign matter by paul lanthier

TECHNICAL PAPER

Detection of Foreign Matter in Beer Using an

Inline Foam Analysis System

Presented at the:

112th MBAA Convention September 12 – 14, 1999

Author : Paul Lanthier, P.Eng.Sales and Marketing ManagerAkitek Inc.2081 Grand Blvd.Oakville, Ontario, CANADAL6H 4X9

Tel : 905-338-9648FAX : 905-338-3522e-mail : [email protected]

Laboratory experiments were conducted at: Akitek Inc.1600 boul. Henri-Bourassa O.Montréal, Québec, CANADAH3M 3E2

The Prototype and Beta Units were installed at various Molson Canada locations.

mailto:[email protected]

TECHNICAL PAPERDetection of Foreign Matter in Beer Using an Inline Foam Analysis System

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TABLE OF CONTENTS

ABSTRACT.................................................................................................................................................... 3

KEY WORDS................................................................................................................................................. 3

INTRODUCTION ........................................................................................................................................... 4

MATERIALS AND METHODS....................................................................................................................... 4

REVIEW OF CURRENT PRACTICES................................................................................................................. 4POSSIBLE REJECT CAUSES .......................................................................................................................... 5AUDIT METHOD ............................................................................................................................................ 5MEASUREMENT MEDIUM............................................................................................................................... 6ADVANCED TECHNOLOGY TOOLS.................................................................................................................. 7LABORATORY EXPERIMENTATION.................................................................................................................. 7PROTOTYPE UNIT......................................................................................................................................... 8BETA UNITS ................................................................................................................................................. 9

RESULTS SUMMARY................................................................................................................................. 10

PROTOTYPE UNIT....................................................................................................................................... 10Setup.................................................................................................................................................... 10Results ................................................................................................................................................. 10Summary.............................................................................................................................................. 10

BETA UNITS ............................................................................................................................................... 11Setup.................................................................................................................................................... 11Results ................................................................................................................................................. 11Summary.............................................................................................................................................. 11

DISCUSSION............................................................................................................................................... 11

ACKNOWLEDGEMENT AND REFERENCES............................................................................................ 11


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ABSTRACT

In capped beer bottles, CO2 dissociation during pasteurization is increased with the presence of foreign

matter such as glass inclusion and visible organic material. During the past 30 odd years, Canadian

operating practices have called for 100% visual inspection of the bottled beer whereby Foampickers

observe foam collars for anomalies which would indicate the presence of foreign matter. This has been

regarded as a very successful, albeit expensive, quality control process.

To emulate this process Akitek had to determine the effectiveness of foampicking over a wide range of

beer and bottle types, define the methodology and develop an appropriate solution; at increasing

sophistication as the project evolved. A number of advanced software tools were employed to attain the

speed, accuracy and repeatability needed and to deal with the complex environment of process, product

and container variations and drifts.

The resulting solution is effective at detecting the presence of foreign matter.

KEY WORDSFoampicking

Foreign Matter

Foam

Glass

Inspection


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INTRODUCTION

Akitek’s mandate in developing a Foreign Matter Detection System was to replicate the human

Foampicker function (detecting and eliminating bottles containing foreign matter) in an automated system.

Its major objectives were to design a system which :

• Measures at an acceptable level of accuracy and consistency.

• Operates in a non contact fashion, on line, at production speeds.

• Adapts to product and process variations.

• Requires a minimum amount of modifications to existing bottling lines.

For the performance verification stage an audit method was chosen which is specifically geared to this

mandate. Though other benefits were or may have been observed, these were not quantified as they are

outside the scope of our mandate.

MATERIALS AND METHODS

REVIEW OF CURRENT PRACTICES

In breweries where Foampickers are used, inspection strategies have been put in place whereby the

Foampicker makes a pass/fail determination of presence of foreign matter in the capped bottle based

usually on 2 or 3 parameters. A compilation of these yielded a total of 11 parameters which are affected by

the presence of foreign matter. Further analysis of these effects helped determine the extent, repeatability

and interrelationship of the parametric variations.


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POSSIBLE REJECT CAUSES

The presence of glass inclusions and visible organic material can cause foam collar anomalies. Another

cause is improperly sealed containers, though this was not the subject of our project and requires further

study to ascertain accuracy and repeatability.

AUDIT METHOD

The foampicking inspection method has been in use for roughly 30 years and has proven to be effective.

It was therefore deemed appropriate to measure the system against seasoned Foampickers, matching the

system’s reject rate to that of the brewery. To this end Candling was viewed as a good audit tool as it

allowed for a large volume of bottles to be audited, from which statistical accuracy could be attained.

To candle a bottle one lifts it up to a light source and peers into the liquid, looking for visible foreign matter.

Baked on proteins, called by some beer skins, are discounted. When foreign matter is observed the bottle

is called a good reject and when the auditor does not observe foreign matter it is called a false reject.

The method cannot detect improperly sealed bottles or small particles and is a relative measurement tool

rather than an absolute one. Nonetheless it is important to emphasize that this is a good tool to compare

machine to man in light of the system’s mandate.

To determine the reliability of the system a Foampicker was positioned after both the system and the

human Foampicker on the good bottle conveyors.


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MEASUREMENT MEDIUM

Optical analysis, with a camera, coupled with image analysis algorithms was chosen as the measurement

medium:

• A camera has a number of advantages:

- It is a hazard free medium.

- It is easily adapted to various situations through a selection of lenses and filters.

- It can measure more than one parameter at a time, with a high level of accuracy.

• Machine Vision is a software tool which recognizes visual patterns, filtering out irrelevant datum. The

technology is noise insensitive, fast and adaptable to a wide range of conditions. Using Machine

Vision we were able to erase the bottle from the image and filter out surface distortions. The result is a

clean image of the foam collar from which the system can make precise measurements.

• There are nonetheless a few disadvantages to these tools:

- Cameras cannot measure through opaque or translucent mediums.

- Machine Vision requires computing capabilities and can be a limiter to simplified system designs.


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ADVANCED TECHNOLOGY TOOLS

We incorporated a number of advanced technology software tools in the final version. These are:

• Temporal Reasoning compares current conditions with past conditions.

• Heuristic Rule programming tends to simplify the application as it structures the software in human

terms helping make the application more specific, trouble free and adaptable to long term needs.

• A scalable and fault tolerant real time operating environment was chosen.

LABORATORY EXPERIMENTATION

We first reproduced the optical analysis in the laboratory with a camera and software tools.

As in the above sketch, a camera and light source were positioned facing each other with a beer bottle in

between. With this set up we were able to eliminate all but the foam collar from the resulting image.

Next, algorithms were developed to extract the desired parameters from the image. Repeated testing

demonstrated that precise measurements were achievable, on moving bottles, at speeds in excess of

1200 bottles per minute, with no perceived loss of accuracy.


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PROTOTYPE UNIT

The next phase was to develop a unit and test it on a production line. We incorporated advanced software

tools to help the system reason accurately. This was deemed important as we could not always be

assured of the availability of ideal data or consistent process and product conditions.

The following foam collar images demonstrate some of the types of foam collars the system was able to

adapt to and analyze. Each foam condition offers its unique analysis challenges.

Dense Foam Well Differentiated Foam Flat Collar


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BETA UNITS

The two Beta Units are in full time operation on a packaging line, without the presence of human

Foampickers. Key additions :

• Flexibility, robustness and stability.

• Adjustable Percent Reject Rate : This is used to adapt the system to the process and product

specifics.

• Auto Calibration : As beer collars may vary during a normal production cycle and between beer types,

the system calibrates itself for each new batch and constantly adjusts itself during normal operations.

• Multiple alarm levels and control strategies

• Remote access for rapid access to information and maintenance issues.

Bottles and Beers Tested to Date:

• Height: 7.8 to 11.65 inches (198 to 296 mm)

• Diameter : 2.44 to 3.74 inches (62 to 95 mm)

• Colour : Clear, green and amber bottles, light and dark beers.

Sketch of aBeta Unit


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RESULTS SUMMARY

PROTOTYPE UNIT

SETUP

• Percent reject rate was fixed at the normal reject rate for this plant.

• The sample sizes were chosen to give data with 95% certainty.

• The system was compared to a cross section of more than 10 inspectors.

RESULTS

• False Rejects: The machine was 1.85 times more likely to reject falsely than was the human. It was

decided that this was partly due to our selecting a higher % reject rate for the system than that

achieved by the human operators participating in the audit.

• Missed Rejects: The human was 4 times more likely to let suspect bottles pass.

SUMMARY

‘Human foampickers falsely reject somewhat fewer good bottles than does the machine, but the machine

is rather better than the foampickers in catching suspect bottles, thus providing better protection to the end

consumer.’ [Report from the University of Guelph].


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BETA UNITS

SETUP

For the two Beta Units the % Reject Rate was lowered, reflecting a more realistic reject rate, and

exhaustive audits were performed on a wide range of beers and conditions, always comparing them to

human Foampickers.

RESULTS

The units detected 2.8 times more bottles suspected of containing visible foreign matter than the human

Foampicker and rejected 23% less bottles. This last number is possibly related to a higher than normal

reject rate by the human Foampickers being audited.

SUMMARY

The two units have been on line since February, 1999 and are problem free. Molson is currently installing

four more units in their Montréal brewery.

DISCUSSION

Molson is very satisfied with the system's performance and is confident that with this technological

advancement it will be able to maintain and exceed its high level of consumer satisfaction.

The next step is to validate the system's accuracy with respect to its Percent Reject Rate selection and

determine if improperly sealed bottles can be accurately identified by observing foam collar anomalies.

ACKNOWLEDGEMENT AND REFERENCES

Report from the University of Guelph (1998)Dr. William Matthes-SearsDept. Mathematics & StatisticsGuelph, Ontario, CANADA

Denis Labelle / Christopher NunesMolson CanadaEtobicoke, Ontario, CANADA

akitek - technical paper on foreign matter by paul lanthier

Technology