Technology for Detecting the Orientation of Oil Seal

TechnologyIntroduction

Technology for Detecting the Orientation of Oil Seal
TURUMI Takuya

1Introduction

Recent production sites are required to automate theirinspection process due to higher product quality requirements and reduced work force. In KYB, the Production
Technology R&D Center and Production Engineering
Department are jointly promoting the development of inspection technologies to automate the inspection process.
Among those is the development of an automatic inspection technology to replace human inspectors allocated tothe manufacturing process of oil seals (hereinafter"seals") that are one of the components of shock absorbers (hereinafter "SA"). The technology has been introduced in mass production. This paper describes the overview.

2of human inspectors to prevent worsening of the cycle
time.
Table1

Target4

Evaluation error [%]Over-inspection [%]Inspection time [sec.]

0.000

Not more than 0.3

Not more than 2.1

Outline of Target Part

Photo 1 shows an enlarged view of the SA and seal assembly, the seal to be inspected, and the front and reverse
sides of the metal.

Purpose of Development

SAThe purpose of the technical development is to automate the inspection process for inspector labor saving. Atechnology for detecting the orientation of the insertmetal(hereinafter the "metal"), which is one of the seal components, has been developed.
Human inspectors are allocated to the process ofchecking finished seals. The inspection technology wehave developed is introduced into the process that may
be the source of reversed metals, not the process ofchecking finished seals, with the aim of reducing the loss
caused by non-conformities.

3

Target parameters of development

Enlarged view ofseal section

Target Parameters of Development

The target parameters for inspection capability andtime were set as shown in Table 1. Evaluation error
means recognizing a non-conforming item as a conforming one by mistake. In case of an evaluation error, nonconforming items will be released to the subsequent process, which may lead to claims in the market. Contrary toevaluation error, over-inspection refers to recognizing aconforming item as a non-conforming one. Over-inspection prevents work from being released to the subsequent
process, resulting in a halt in the production. This eventually leads to lower productivity. The target inspection
time was set based on the current visual inspection time

Seal

Identification
grooveFront side of metal
Reverse side of metal
Photo 1 SA, seal, and metal

The seal is a part for preventing oil leakage throughthe sliding part of the piston rod of SA. The metal, which
is one of the seal components, is molded integrally withrubber material to form the seal. The metal has front andreverse sides that can be differentiated from each other.
Molding the metal into the seal with its wrong side up
will result in a higher risk of oil leakage. To prevent this,the metal has an identification groove on one side. In this―8―

KAYABA TECHNICAL REVIEW No. 66 APR. 2023

document, the side of the metal with the identification
groove is called the front side.

5

 verview of Process with Inspection
OTechnology Introduced

set-up modes can be switched over with a push-buttonswitch.
This loop-running inspection is automatically started
when the operator's hand leaves the imaging area.

The inspection technology was introduced into theprocess in which human operators manually set metals
and rubber pieces on the jig Note 1) before molding. Photo
2 shows the work bench and jig in the target process. Thework bench had to be replaced by a device for automatedinspection.

Metal

Inspection PC

Equipment

Image processing andinspection software

Push-button switch

Communication
software

Interlocking

Digital I/O board

PLC

Fig. 1 Configuration of inspection system
RubberpiecesFig. 2 shows the flow chart of operation of the inspection software that was introduced in mass production:
Note 2) Acronym for Programmable Logic Controller.

Work benchStart

Jig

Capture camera
information

Photo 2 Work bench and jig

Inspection

The operator puts the jig on the work bench and sets
metals with the side with the identification groove facing
up in the circular pockets one by one. Then, the operator
places rubber pieces on each metal and sets the jig in themolding machine.

Wait signal
No signal

Note 1) The jig is used to set metals and rubber pieces in themolding machine.

6Imageprocessing

Start inspection
Wait trigger

Details of development

6. 1 Inspection Method
The inspection used an image processing system thatcan not only capture images from a position where thesystem cannot obstruct the operator but also examines all
metals on the jig at a time. It was decided to determine
whether the metals are front or reverse facing throughimage processing, superficially by detecting the presenceof the identification groove, which is the most distinctive
feature among the differences between the front and reverse sides.
6. 2 Inspection System
Fig. 1 shows an example of the configuration of the inspection system. Internally built communication software
was used to transmit signals from the image processing
and inspection software to the digital I/O board within
the inspection PC. The digital I/O board and PLC Note 2)
were interlocked so that metals could not be released tothe subsequent process unless they passed the inspection.
The image processing and inspection software has inspection, calibration, and set-up modes as described later.
The software was designed so that the calibration andSignal
received
Metal orientation
check
NG(Not OK)

Calibration
signal received

Calibration
operationStorecalibration data

Set-upSet-upoperation
Read machinemodel information

Send calibration

Send set-up

completed signal

completed signal

Judgement
OKStore data
Send OKsignalFig. 2 Flow chart of software operationIn mass production, the push-button switch can beused to switch the operation mode from inspection tocalibration or set-up. Inspection mode is run in loop anddoes not need to be started up with the switch. The system is configured to trigger the inspection when the operator's hand leaves the imaging area, and the molding machine has work in position. The image processing―9―Technology for Detecting the Orientation of Oil Seal

CameraCameraLighting

Lighting

Lighting

JigJig
Photo 3 Actual inspection machine

Fig. 3 General layout ofoptical system

Photo 4 shows images captured by the system on theactual inspection machine. Conditions for the inspection
were set under the constraint that the layout of the lighting and camera system was limited by the equipmentlayout of the production line.
The inspection machine is likely to be affected by disturbance light because the machine cannot be covered
with blackout curtain as this may lead to workability deterioration and the ingress of contaminants during molding. Then, an inspection algorithm has been developedthat is unlikely to be affected by these factors.

6. 4 Inspection Algorithm
6. 4. 1 Flow of Image Processing and Inspection
Fig. 4 shows the general flow of the processes fromimage capturing to inspection.

Judge
Inspection result
outputDetection

Pretreatment

Detect identification
grooveInspection image
cut-out

Inspection

Pretreatment

Detect metal OD
Inspection image
capturing

technology is used to locate the operator's hand and determine whether work is set in the machine or not.
This paper focuses on introducing the metal check(front/reverse side) in the flow chart.
6. 3 Optical Equipment
Photo 3 shows the actual inspection machine. Fig. 3shows the general layout of the optical system. This optical system consisted of a camera and two lighting units.
The camera was installed directly above the jig at aheight where the camera could not interfere with the operators. The resolution of the camera and its lens wereselected to enable the detection and imaging of the identification groove of the metals set in the jig. The lighting
units were located in such a manner that allowed irradiation of the whole area of the jig from the right and left
sides.

Fig. 4 General inspection flow

After an inspection image is captured, the outside diameter of the metals is detected to determine the positionand number of metals. Then, only the area around thecircular identification groove of each metal is cut out toallow detection of the groove. The number of grooves iscompared with the number of metals to make a judgement. When these numbers match, "OK" is displayed.
When they do not match, "NG" (Not OK) is displayed
along with the location of the NG metal(s). For NG, theoperator flips the reversed metal(s), automatically turning
NG into OK.
6. 4. 2 Pretreatment
In practice it is difficult to directly detect the identification groove on the captured image. So, the image must
be processed to highlight the features to be detected. In
this project, a band-pass filter was introduced. The bandpass filter passes frequencies within a certain range andis used to extract the outside diameter and identification
groove. As shown in Photo 4, the contour of the metalson the jig and their identification groove appears darker
than the surroundings. The contour (outside diameter)
and identification groove of metals can be extracted using the band-pass filter.
There is a difference in gray value Note 3) between thecontour of the metals on the jig and their identification
groove and the surroundings. This difference is considered unlikely to greatly diminish even if the metals areaffected by disturbance light. So, the use of the band-passfilter allows the detection of elements of the outside diameter and identification groove of metals without being
substantially affected by disturbance light.
The band-pass filter was applied with commands that
had been prepared in the image processing software.
Note 3) The level of brightness. The white-to-black level is given by a number between 0 and 255.

Entire image

Enlarged view of image

Photo 4 Images

Photo 5 shows an example of an image captured before treatment and another subjected to processing withthe filter and automatic binary processing that allocatesblack or white to individual pixels according to theirbrightness. In the image after treatment, the areas inwhite indicate the parts that were extracted by the pro-― 10 ―

KAYABA TECHNICAL REVIEW No. 66 APR. 2023

cessing. Hereinafter the band-pass filter processing andthe automatic binary processing are collectively called
the pretreatment.

Before treatment

After pretreatment

eter. From the image, a rectangular section is cut out indimensions larger than the diameter of the circular identification groove indicated in each drawing. Then, theimages shown in right of Photo 7 are obtained as many
as metals are captured in Photo 4. Each of the cut-out images is subjected to pretreatment and then the Houghtransform in terms of the diameter of the circular identification groove. This will detect the identification grooves.
Photo 8 shows an image after the pretreatment and another image after the Hough transform in which the center of the circle has been detected and dilated. The number of identification grooves can be determined bycounting these center points.

Photo 5 Images before and after image processing

6. 4. 3 Detection Method
Feature extraction from images subjected to pretreatment was done with the Hough transform technique. The
Hough transform is a feature extraction technique used inimage processing and can be used to detect lines and circles in the image. Circle detection finds any circles within the target image that match the diameter informationthat has been given in advance. If an applicable circle isfound, the coordinate of the center of the circle is detected. In this project, the outside diameter of the metal andthe diameter of the identification groove indicated in thedrawing are used as the diameter information to be given
to the system.
6. 4. 4 Detection of the Outside Diameter ofMetals
The outside diameter of the metals is detected in thecaptured images that have been subjected to pretreatment
and the Hough transform in terms of the outside diameter. Photo 6 shows an image after the band-pass filter
processing and another image after the Hough transformin terms of the outside diameter. The dots in red appearing in the image subjected to the Hough transform are thedilated center points of the metals. The automatic inspection system determines the number of metals by counting
the number of these red dots.

After pretreatment

Before cut-out

Photo 7 Cut-out inspection images

After pretreatment

6. 4. 5 Detection of Identification Grooves
Photo 7 shows inspection images of the identification
groove. This inspection uses the center of the circle detected by the Hough transform of the metal outside diam-

After Hough transform

Photo 8 Detected identification groove

6. 4. 6 Evaluation
After detection of the identification grooves has been
completed, the inspection results should be evaluated.
Evaluation criteria have been established so that the jig
passes the inspection (OK) when the number of metaloutside diameters detected matches the number of identification grooves while the jig fails the inspection (NG)when it does not. For mass production machines, the jig
is locked and cannot be taken out of the work bench as
long as the result is NG. The jig cannot be released fromthe work bench until the result is turned to be OK.

After Hough transform

Photo 6 Metal outside diameter detection processAfter cut-out

7

Results of Development

The results of the evaluation of the inspection capability are shown in Table 2. 62,000 parts currently in production were used in the evaluation of the inspection capability during the period between January 8 andFebruary 1, 2022.

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Technology for Detecting the Orientation of Oil Seal

the Hough transform.
 he inspection capability was proven for massT
production with an evaluation error rate of 0%
and an over-inspection rate of 0.005%.
(5) he inspection time was maximum 2.0 seconds,
which is equivalent to the visual inspection timefor human operators.
(6) The technology was introduced in mass production and inspector labor saving was achieved.

Table 2 Results of evaluation
Evaluation error [%]Over-inspection [%]Inspection time [sec.]

Target0.000

Not more than 0.3

Not more than 2.1

Result0.000

0.005

2.0

Evaluation○○○

The targets for all the items were achieved.
The automatic inspection system was introduced inApril 2022. Inspection labor saving, which was established as the purpose of this development project, wasachieved.

8In Closing

This project successfully developed technology for detecting the orientation of oil seal metals. The following
summarizes the project:(1) The inspection was made during the process forsetting metals in the jig.
(2) The presence/absence of the identification groove
was identified by image processing for inspection.
(3) The inspection algorithm included edge detection
with the band-pass filter and circle detection with

(4)

The inspection technology described in this paper canbe applied not only to the detection of the identification
groove of the metals but also to other inspection processes with circle detection such as for assembly error of circular parts.
Finally, I would like to take this opportunity to sincerely thank all those concerned who extended cooperation to this development project.

Author TURUMI Takuya
Joined the company in 2015.
R&D Sect. No.2, Production Technology R&D Center, Engineering
Div.
Took present post after working in
Production Engineering Sect., Steering Business Dept., Automotive
Components Operations, Gifu North
Plant.

Engaged in development of appearance inspection technology.

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