numerical investigation on the performance of suction head

28 ECTI TRANSACTIONS ON ELECTRICAL ENG., ELECTRONICS, AND COMMUNICATIONS VOL.18, NO.1 FEBRUARY 2020

Numerical Investigation on the Performanceof Suction Head in a Cleaning Process of

Hard Disk Drive Factory

Jirawat Khongsin∗ and Jatuporn Thongsri∗† , Non-members

ABSTRACT

The suction head is a component positioned at thevacuum cleaner’s tip and used to control airflow toeliminate small particles, thus preventing contamina-tion from occurring during the cleaning process ata hard disk drive (HDD) manufacturing factory. Atthe factory, 2 suction head types (bowl and straight)were used in the cleaning process. From an actualusage, the operators questioned the operating condi-tion’s performance and suitability. In order to seekan answer to the questions, the researchers used com-putational fluid dynamics (CFD) to simulate airflowand particle trace using the ANSYS Fluent software,the factory’s actual conditions, and a suction distanceranging between 2.5–15 mm. CFD simulation resultsshowed that the bowl type suction head performedbetter compared to the straight type in every suc-tion range under the exact same operating conditions.Both suction heads performed well at a 5 mm distancebetween the suction head and cleaning area. Suctionperformance decreased when the head was positionedcloser or farther than the mentioned distance. Apartfrom applying all results from this research to increasecleaning efficiency in the actual factory, the findingscould also be used as basic information for designingnew suction head models with higher efficiency thanthe original model.

Keywords: Airflow, ANSYS Fluent, ComputationalFluid Dynamics, Cleaning Process, Particle Contam-ination, Suction Head

1. INTRODUCTION

The Hard Disk Drive (HDD) is a device used tostore information in computers. Currently, the HDDindustry’s major manufacturing base is situated in

Manuscript received on September 28, 2019 ; revised on Oc-tober 29, 2019 ; accepted on November 8, 2019. This paperwas recommended by Associate Editor Chanon Warisarn.∗The authors are with the Computer Simulation in Engineer-

ing Research Group, College of Advanced Manufacturing Inno-vation, King Mongkut’s Institute of Technology Ladkrabang,Bangkok, 10520, Thailand.†Corresponding author. E-mail: [email protected]©2020 Author(s). This work is licensed under a Creative

Commons Attribution-NonCommercial-NoDerivs 4.0 License.To view a copy of this license visit: https://creativecommons.org/licenses/by-nc-nd/4.0/.

Digital Object Identifier 10.37936/ecti-eec.2020181.218580

Thailand. The HDDs are exported to countries overthe world, generating many billion-baht income forthe country. An HDD consists of over 2,000 tinypieces of electronic parts. During the manufacturingand assembling process, all parts must be assembledwithin a clean room with a cleanliness level betweenclass 100 and 1,000. Even a small amount of contam-ination onto an HDD part may negatively impact theHDD’s performance, making it a defect which cannotbe sold. Therefore, contamination in these processeswere a major problem in the factory that must beurgently resolved. The problem also challenged theresearchers as we had to develop new technology toovercome the obstacle and support the industry toproduce higher quality HDDs.

To solve the contamination problem in an HDDfactory’s cleaning process, the operators would regu-larly clean the production line using a vacuum cleanerwith a suction head installed at the tip to control air-flow to facilitate effective particle suction. This fac-tory used 2 suction head types: straight and bowltypes as in Figs. 1(a) and 1(b) accordingly. The bowltype’s angle and degree could be adjusted. Still, weonly considered the case which the head was posi-tioned vertically as shown in Fig. 1(b). Both suctionheads were used under the same operating conditions;therefore, raising questions among the operators ofboth types’ work efficiency and suitable operatingcondition, which eventually led to this research.

From our reviews of relevant research, we foundthat in the HDD manufacturing industry, Compu-tational Fluid Dynamics (CFD) was widely used todesign and develop devices and components to in-crease the efficiency of removing the small particlesin the cleaning process, such as Yimsiriwatana andJearsiripongkul [1] who used CFD to simulate airflowfrom a single probe vacuum. They discovered thatthe most suitable distance between the suction headand the designated cleaning area was 5 mm. Still,the single probe suction head in their research hada different design and operating condition from thesuction head of interest in this research. Jai-Ngamand Tangchaichit [2] used CFD to study airflow inHDDs to improve the Impinging Air Jet Particle De-tachment System used to efficiently clean head stackassemblies. Thongsri et al. [3–5] successfully usedCFD to simulate the airflow in automated machinesand in clean rooms to find the most suitable operat-

NUMERICAL INVESTIGATION ON THE PERFORMANCE OF SUCTION HEAD IN A CLEANING PROCESS 29

Fig.1: Suction heads for (a) straight type and (b)bowl type.

ing conditions, which were later implemented at theactual factory and effectively decreased particle con-tamination. Most mentioned research consistently in-dicated that nozzle heads or suction heads were thedevices that contributed to highly efficient vacuumingor spraying. Other examples of research which usedCFD to design nozzle heads were Kumar et al. [6]and Reza and Arora [7]’s study, which used CFD todesign and develop an aerospike nozzle head that wassuitable for attaching to new rockets that sent satel-lites into space. Hyder and Hayat [8] used CFD tooptimize a nozzle head with multiple air exit holes.Their research resulted in the creation of a nozzlehead that could spray air at a high speed and largequantity within a short period of time. For develop-ing air suction devices, Xi et al. [9] used CFD to checkthe particle suction performance of a reverse blowingpickup mouse. Their research led them to discoverthe design and operating conditions that were suit-able for cleaning road surfaces. All this literaturereview confirmed that CFD and suction head designwere major contributors to solutions for this problem.

In this article, we used the CFD to simulate air-flow and the particle trace which occurred after us-ing both straight and bowl suction head types underthe factory’s actual operating conditions. Simulationresults from both suction head types were then com-pared with actual measurement to verify the credibil-ity. Finally, the simulation results were analyzed toevaluate its performance and to find the most suitableoperating condition for each suction head type.

Fig.2: Solid models and dimensions of (a) straighttype and (b) bowl type.

2. METHODOLOGY

2.1 Fluid and mesh models

We simplified both suction head types in Fig. 1into a solid model as in Fig. 2 for both suction heads;(a) straight type, and (b) bowl type. To save com-putational time and the resources employed for cal-culation, we created a fluid model and mesh modelfor the air within the suction head and the air in thesurrounding area. Only a half model was created asin Fig. 3 for the straight suction head type, and Fig. 4for the bowl head type. The quantity of elements andnodes of the straight type were 0.59 million elementsand 0.61 million nodes. As for the bowl suction headtype, there were 0.40 million elements and 0.43 mil-lion nodes. All elements were the hexahedron type,created by the ICEM CFD software, with an averageskewness value of 0.075.

2.2 Boundary conditions

Air from outside would flow into the suction headwhenever the pressure in the pipe was lower than thepressure outside. After measuring the actual operat-ing conditions in the factory, we found that the airpressure outside the suction head was 101,375 Pa,while the pressure inside the pipe was 92,800 Pa.Therefore, the air pressure outside was set as the pres-sure inlet while air pressure inside the pipe was set asthe pressure outlet in the simulation. Fig. 5 shows theboundary conditions used in the bowl suction headtype. The same conditions were applied with thestraight suction head type, with only the design of thehead as the difference. The symmetry was the areawhere airflows were exactly the same. The symme-try enabled the software to calculate faster. The airdensity was 1.255 kg/m3. Convergent criterion wasset as 10–4. The turbulence model was shear stress


Fig.3: Fluid and mesh models of straight type.

Fig.4: Fluid and mesh models of bowl type.

transport (SST) k−ω. The reason of using SST k−ωwas because of its widespread popularity in research

Fig.5: Setting of boundary conditions.

relevant to industrial and medical applications [10–11]. This turbulence model combined the advantagesof both k − ω and k − ε turbulence models together,thus enabling us to simulate the fluid’s flow behaviorin the inner area of the boundary layer accurately,which is the k−ω’s uniqueness. Moreover, it can alsoswitch to correctly calculate the free shear flow, whichis another distinctive property of k − ε. All simula-tions were calculated in a steady-state condition usingthe ANSYS Fluent software. We separated the sim-ulation into 2 phases; phase 1 when the airflow wassimulated and air velocity was criterion, and phase 2when the particle trace was simulated, and numberof the suctioned particles was criterion. Results fromboth phases were then analyzed to investigate bothsuction head types’ performance. In phase 2, sincethe particles that must be eliminated are tiny in sizebut have greater density compared to the air, we usedthe Discrete Phase Model (DPM) with one-way simu-lation; we finished solving the flow before starting tosolve the DPM. This technique enabled us to accu-rately predict particle traces [3, 12, 13]. The particlesthat would be suctioned were skin particles that were0.5 micron in size, and 7,500 kg/m3 in density. Theseparticles were reported to be frequently found in fac-tories, caused by the operators’ activities [13–14].

2.3 Performance of suction head

As mentioned previously, we divided the criteriaused to evaluate the suction heads’ performance into2 phases: using the suspension velocity as the cri-terion and using the suctioned particle count as thecriterion. Details of using suspension velocity (vs) asthe criterion are as follows. When the vacuum cleaneris operating, the surrounding air is constantly suc-tioned into the device. Small particles are suctionedinwards when the velocity of the air where the par-ticles are floating in are equal to or higher than vs.If the particles that will be suctioned are sphericalin shape and have a Reynold number for floating be-tween 500–2×105, vs can be expressed by [9]


vs = 5.45

√dp(ρp − ρ)

ρ(1)

where dp stands for diameter of particle. ρp and ρstand for density of particle and air, respectively. Inthis research, the Reynolds number was in a range of5,000–10,000.

Therefore, for phase 1, we may consider the suctionhead’s performance (P1) from the suspension velocitywhich can be calculated from

P1 =

∣∣∣∣As

A0

∣∣∣∣× 100% (2)

where As is cleaning area that has air velocity higherthan vs. A0 is the circle area with radius 6 cm ex-pected to be cleaned, totalling 1.13 × 10−2 m2.

In phase 2, we calculated the suction head’s perfor-mance from the suctioned particles count (P2) usingequation;

P2 =

∣∣∣∣Ns

N0

∣∣∣∣× 100% (3)

where Ns is the number of suctioned particles fromthe simulation. N0 is all particles expected to besucked totalling 10,000 particles.

3. RESULTS AND DISCUSSION

3.1 Validation

To validate the used methodology and simulationresults, we measured the air velocity from both suc-tion heads at the distances of (h) 10, 15 and 20 mmin the vertical direction using hot-wire anemometerwith ±0.03 m/s of accuracy. Each h was then dividedhorizontally into 9 positions; at –10, –7.5, –5, –2.5, 0,2.5, 5, 7.5, and 10 mm. Negative positions meantpositions on the left side of the central line, whilepositive positions meant positions on the right sideof the central line. Number 0 meant the position atthe center, exactly at the middle of the suction head.Each position was measured 10 times. Measured re-sults were then compared with simulated results asin Figs. 6–7 for straight and bowl type suction heads,at distances of (a) h = 10 mm and (b) h = 20 mm.From Figs. 6 and 7, it is noticeable that the actualair velocity measurements were close to simulated re-sults. The highest maximum error value was 16.41%at h = 10 mm of straight type; however, the sim-ulated result was within the error bar. Therefore,the methodology used, and simulation results werecredible. The results compared at h = 15 mm alsogave consistent outcomes. However, due to the ar-ticle length limitations, we couldn’t include all thecontents.

Fig.6: Comparison between the simulated and mea-sured air velocities for straight type.

Fig.7: Comparison between the simulated and mea-sured air velocities for bowl type.

3.2 Performance comparison

To compare the performance of both suction headtypes using suspension velocity as the criterion forconsideration in phase 1, Fig. 8 represents the veloc-ity contour generated by the simulation of (a) straighttype and (b) bowl type suction heads. We also foundthat at the region near both suction heads, the veloc-ity of the suctioned air was higher than the velocityof the air further away. This finding was consistentto actual measurements in Section 3.1. The calcula-tion of vs using Eq. (1) resulted in vs = 0.092 m/swhich assumed that at an air velocity of 0.092 m/sor more, the air could lift these particles up, en-abling the head to suction the particles [9]. Ath = 5 mm, the air moved faster than 0.092 m/s thatgave As = 3.47 × 10−3 m2 for the straight suctionhead type, and As = 4.95 × 10−3 m2 for the bowlsuction head type. A0 = 1.13 × 10−2 m2 was the cir-cle area that we expected to clean. When the clean-ing area was used to calculate suction performanceusing Eq. (2), the straight type suction head’s perfor-mance was 30.69% while the bowl type suction head’sperformance was 43.83%. Fig. 9 shows velocity con-


Fig.8: Air velocity contour of suction heads ath = 5 mm for (a) straight type and (b) bowl type.

tour of cleaning areas resulted from Fig. 8. The bowltype gave the cleaning area a diameter of 79.41 mm,while the straight type gave a diameter of 77.38 mm.Fig. 10 shows velocity vectors of both suction headsat h = 5 mm. Air from the outside will be suctionedinto the suction head. The air volume with speedshigher than 0.092 m/s for the bowl type were higherthan the straight type. When considering Figs. 8–10along with Figs. 6–7, we analyzed that the most suit-able suction distance was h = 5 mm, because the airhad velocity higher than vs once compared to otherdistance ranges. Apart from at this distance, the suc-tioned air will not have a velocity high enough to pushthe articles upwards to enter the suction head.

In phase 2, to evaluate the performance by usingthe number of suctioned particles as the criterion, wesimulated the suction process using DPM in ANSYSFluent software with a one-way simulation technique.We pretended that there were N0 = 10,000 skin par-ticles intended to be suctioned, placed at h of 2.5,5, 7.5, 10 and 15 mm away from the suction head.The positions of particles were randomly distributedin a circle area with A0 = 1.13 × 10−2 m2, whichwas the same area mentioned in Eq. (2). The soft-ware would later count the quantity of particles thatwere successfully suctioned. Fig. 11 shows the ex-ample of particle traces of 500 particles. It was no-ticeable from Fig. 11 that the bowl type suctionedparticles better than the straight type because therewere more lines showing the particle traces. As forthe bowl type, particles were suctioned into the headin 2 routes. The straight type, on the other hand, hadonly one route. The number of remaining particles in

Fig.9: Air velocity contour on cleaning area of suc-tion heads for (a) straight type and (b) bowl type.

Fig.10: Air velocity vector of suction heads ath = 5 mm for (a) straight type and (b) bowl type.

Fig. 11(a) was greater than Fig. 11(b). Also, the ve-locities of the suctioned particles were faster. Afterthe DPM was completely run, the number of suc-tioned particles were recorded for both head types.Fig. 12 shows the number of suctioned particles sim-ulated by the software for varying h. The maximumnumber of suctioned particles was h = 5 mm with6,408 particles for the bowl type and 4,383 particles


Fig.11: Particle traces of suction heads at h = 5 mmfor (a) straight type and (b) bowl type.

Fig.12: Comparison of the number of suctioned par-ticles between the straight and bowl types.

for the straight type.

After the Fluent software recorded As and Ns, theperformances P1 and P2 can be calculated by usingEqs. (2) and (3) at h between 2.5–15 mm; calculationresults are presented in Table 1.

We found that the performance levels of bowl typewere higher than the straight type for every h. Theoptimal suction performance was at h = 5 mm, whichhad P1 = 43.83% and P2 = 64.08% for bowl type, andP1 = 30.69% and P2 = 32.82% for straight type atthe same h. When suctioned at h = 15 mm fromthe suction head, the performance level of both typesdecreased to P1 = 33.21% and P2 = 29.73% for thebowl type and P1 = 21.88% and P2 = 17.00% for thestraight type. Therefore, from the measured resultsand simulated results presented in Figs. 6–12 includ-ing Table 1, the researchers were confident that the

Table 1: Performance of suction heads.

Type h (mm) P1 (%) P2 (%)

Straight

2.5 29.72 29.33

5 30.69 32.82

7.5 29.65 28.21

10 27.95 25.30

15 21.88 17.00

Bowl

2.5 43.02 59.46

5 43.83 64.08

7.5 42.26 50.39

10 39.30 43.14

15 33.21 29.73

bowl type’s particle suction performance was higherthan the straight suction head. Both types had a suit-able particle suction distance at 5 mm. All findingsfrom this research were shared with the factory’s engi-neers for further cleaning process optimization. Still,the bowl type’s particle suction performance only hadmaximum particle suction performance of 64.08%, arate lower than the factory’s anticipation that theiroperating condition should exceed 80%. Designinga new suction head model with higher performanceis therefore a challenging and interesting task for re-searchers.

4. CONCLUSION

We used FLUENT software to investigate the par-ticle suction performance of both straight and bowltype suction heads which were used in the cleaningprocess of an HDD factory. We also studied to findthe optimal suction distance for operations. Inves-tigation on the performance were conducted using 2criteria: suspension velocity and the quantity of par-ticles for the suction distances ranging between 2.5–15 mm. When suspension velocity was used as the cri-terion, theoretically we found that the minimum airvelocity for suctioning particles was vs = 0.092 m/s.Using suspension velocity as criterion, simulation re-sults of the velocity contour showed that the bowltype suction head enabled the cleaning area to haveair velocities higher than vs more than the straighttype suction head at all suction ranges with a maxi-mum performance rate at 43.83%, while the straighttype suction head’s performance rate was only 30.69%at a suction distance of 5 mm. The results could beanalyzed to show that the performance of bowl typewas higher than the straight type. When the numberof particles for the suction distances was used as thecriterion, we simulated the particle trace using DPM.We found that the bowl type suction head could suckthe particles more than the straight type suction headat all suction ranges, with a maximum performance


rate at 64.08% at a suction distance of 5 mm, whilethe straight type suction head’s performance rate wasonly 32.82% at the same suction distance. Both crite-ria were credible and gave consistent results; the mostsuitable suction distance for both suction head typeswas 5 mm, since a distance closer or farther than thatwould not enable the device to suction the particlesand decreased the performance of suction.

ACKNOWLEDGEMENT

This research was supported by College of Ad-vanced Manufacturing Innovation, King Mongkut’sInstitute of Technology Ladkrabang, and SeagateTechnology (Thailand) Ltd. The fund was sponsoredby Research and Researchers for Industry (RRI),grant number MSD60I0126.

References

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[6] K. N. Kumar, et al. “Design and Optimization ofAerospike nozzle using CFD,” IOP Conf. Series:Mater. Sci, Eng., vol. 247, p. 012008, 2017.

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Jirawat Khongsin received his B.Sc.in Physics from Kasetsart University,Kamphaeng Saen Campus, Thailand,in 2017. He is currently studying forM.Eng. in Advance Manufacturing Sys-tem Engineering program at Collegeof Advanced Manufacturing Innovation,King Mongkut’s Institute of TechnologyLadkrabang, Thailand, since 2017. Hisresearch interest includes computationalfluid dynamics, particle contamination,

computer simulation, and cleaning process.

Jatuporn Thongsri received his B.Sc.in Physics from Khon Kaen University,Thailand, in 2002, and the M.Sc. degreeand the D.Sc. degree in Physics fromChulalongkorn University, Thailand, in2006 and 2011, respectively. He has ex-pertise in computer aided design (CAD),computational fluid dynamics (CFD), fi-nite element analysis (FEA), and com-puter simulation (CS). He is currently alecturer at College of Advanced Manu-

facturing Innovation, King Mongkut’s Institute of TechnologyLadkrabang, Thailand. Also, he is a researcher and a consul-tant of several factories, who has a lot of experience in applyingCAD, CFD, FEA and CS to solve various problems and im-prove the manufacturing processes.

numerical investigation on the performance of suction head

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