The complexities of cleanroom design and operation

BY DR TIM SANDLE | 26 March 2024

 

The design of a cleanroom is an essential part of the contamination control programme and there are many aspects that need to be considered. Simply focusing on one factor, like air change rates, is insufficient.

 

Central to design is understanding the ventilation pattern, which is concerned with the movement and distribution of the air within an enclosed space (the cleanroom). The air movement within an enclosed space can be very complex as it depends on many factors, including room geometry and the size and shape of equipment. Furthermore, the type and positioning of air inlets and outlets is important. 

Air change rates

 

In many textbooks, air change rates (the time taken for the air within the cleanroom to be replaced with fresh air, expressed as the number of times this happens per hour) is presented as one of the key contamination control measures, along with HEPA filtered air, good air mixing and the maintenance of a pressure differential to a lower classified area. Air changes are expressed as the relation between the air flow rate entering the enclosed space and its volume.

 

What impact does increasing air change rates have on contamination control? One study found that an increase of air changes from 15 h−1 to 20 h−1 did not significantly affect the particle removal efficiency in the occupied zone of a EU GMP Grade B equivalent cleanroom. 

However, it was found that increasing the air changes per hour from 20 h−1 to 25 h−1 decreased the time that a given concentration of particles remained in the cleanroom, causing room residence time to drop from 32% to 21% (1). This assumes that contamination is constant. A more nuanced consideration of air change rates sees contamination control as based on air change rate, particle emission rate and return airflow patterns. Even here, the presence of different ‘micro’ environments within the cleanroom are not accounted for.

 

There is a difference between the air change rate, which looks at the average (mean) time taken, and overall air change effectiveness within a cleanroom (2). Air-change effectiveness is defined as the ratio of the age-of-air for perfect mixing to the average age-of-air in a considered zone (3). It may be that different zones within the cleanroom have different levels of airflow effectiveness (based on some of the factors discussed below).

 

Hence, air change rates have an important role to play in reducing contamination from settling onto surfaces. However, it is not the only design factor that needs to be understood.

 

 

Other design factors

 

An analysis based exclusively on the air change efficiency has several limitations (4). There are many factors that contribute to cleanroom contamination control.

 

Different influencing factors include:

 

  • Whether there is continuous generation of particles
  • Types of particles, based on their mass, momentum and mean
    • Smaller particles (≤0.5 μm) follow the airflow pattern more strictly than larger particles (≥5.0 μm). Therefore, depending on the particles of concern, the room modelling may need to have a wider assessment
  • Whether the particles are microbial carrying
  • The rate of settling of particles on the surface of the equipment
  • The number of air inlets and extracts
  • The location of air inlets and extracts
    • Generally, downward flow (inlets mounted in the ceiling) is optimal, with extracts at a lower level on the wall (7)
  • How the configuration of the air diffusers and air exhaust impacts the transportation of contaminants
    • For example, swirl diffuser designs are more effective at creating a homogenous air distribution
  • The influence of internal structures (including the type and layout of equipment)
  • Room layout and dimensions
  • The cleanroom thermo-hygrometric parameters
  • The rate of air mixing within the room and its effect on particle concentration

 

 

Air patterns

 

The airflow pattern created by the ventilation system dictates the flow of particles within the space, especially in areas where two different cleanrooms or barrier devices meet. These can be accumulation locations. An understanding of airflow patterns is commonly achieved by airflow visualisation (using a ‘smoke’ generator with water or glycol sources) to study the way air behaves. The learnings from this can help with the positioning of environmental monitoring samples.

 

 

Stagnation

 

The closer air gets to an object, the slower it becomes and the presence of certain designs of equipment can slow down the airflow and create eddying. This can lead to air stagnation regions (microenvironments). Here, the mean age of air will be high in these areas and the ventilation will be poor. This means that the average air change rate is not the same for all parts of the cleanroom and there will be regions where older air persists for longer. 

 

 

Risk of excessive turbulence

 

There are circumstances when the air change rate is set too high. Not only is this wasteful in terms of energy efficiency, there is also an increased risk of turbulence and velocity fluctuations. Hence lower flow rates can sometimes reduce unwanted turbulence and result in the ventilation system becoming more efficient at removing contaminants. Finding this point is where the work is required, and empirical data needs to be collected. Techniques like computational fluid dynamics can prove very useful for predicting the movement of the air in ventilated spaces, but the ultimate test is an assessment of the operational state using airborne particle counters. 

 

 

Opening doors and temperature variances

 

When doors to a cleanroom are opened, pressure differentials provide some protection against contamination ingress (in the case of positive pressure) or contamination egress (in the case of negative pressure rooms). Risk factors include repeated door openings and the length of time that a door remains open, as well as movement through the door resulting in door operation sometimes eliminating and even reversing the pressurisation across the door. This is a type of uncontrolled infiltration of air. Studies have shown that longer door-opening duration and lower air change rate produce more risk, and this risk increases the faster personnel walk through the open doorway (8). As a counter, the higher the differential pressure, the faster the issue is addressed in terms of the positive pressure recovering (9). 

 

Another factor that can lead to an increased likelihood of contamination is a variation in temperature. Where a temperature gradient exists between the warm air (say, inside a room) and cooler air (such as within a corridor) this can create a ‘two-way buoyancy flow’, leading to the warmer air rising to seek a way out and the cooler area to flow at floor level in seeking a way in (10). 

 

 

Room temperature variances

 

Another influencing factor is affecting the ventilation airflow pattern is the presence of thermal sources and the variation in heat pattern from different items of equipment. In pharmaceuticals and healthcare, many types of equipment produce considerable amounts of heat and this can create contamination control concerns through secondary flows.

 

 

Room occupancy and personnel activities

 

Contamination sources like wall and ceiling shedding, floor dust and equipment operation, will introduce contamination - yet these sources will be fairly constant. The activities of personnel is something harder to predict.

 

People are a source of particulates (many microbial carrying) and an unpredictable variable (since behaviours cannot always be carefully controlled). Room design considerations must include an assessment of the number of personnel who will work within the room. Each additional person, no matter how effectively gowned, will contribute to an increase in the particulate concentration within the cleanroom (especially since particles generated by each operator migrate up the cleanroom garment to the head and drop to the legs during cleanroom movements) (11). In terms of the contribution, one extensive study found the equivalent value of the human particle emission rates is 50,000–180,000 particles/person/minute (12). This has been calculated in another study as creating a local concentration of particles of 1742 ± 481 particles m−3 per additional person (13). Here, the contamination source strength inside the cleanroom is linear with occupancy. It has also been noted that decay rates, based on 0.3-micron particles, decrease by up to 50% in the presence of occupants (14).

 

As well as room occupancy, the way personnel behave in the critical zone is also important. There are complex airflow distribution systems operating in each microenvironment. The air distribution may change significantly under various conditions involving the presence of different heat sources (through thermal plumes) and the movement of personnel (15). With behaviours specifically, human activity vigour influences total particle release in clean environments (especially with particles concentration ≥0.3 μm) (16).

 

 

Summary

 

The effective design of a cleanroom to control contamination is complex with many influencing variables. The effectiveness of contamination control must be verified. This can be approached theoretically through computational fluid dynamics or by running multiple practical simulations and collecting particle data. Both of these approaches are complicated, long and expensive, yet getting them right can help to reduce the likelihood of contamination . 

 

References

 

 

  1.    Zhao, F.-Y.; Cheng, J.; Liu, B. et al. Regional flow motion and heat energy balance analysis of a 10,000 class pharmaceutical cleanroom with secondary return air conditioning system. Int. J. Refrig. 2021, 129, 237–249
    2.    Whyte, W., Ward, S., Whyte, W. M. and Eaton, T. Decay of airborne contamination and ventilation effectiveness of cleanrooms, International Journal of Ventilation, 2014, 13 (3): 1-10
    3.    Rim, D., Novoselac, A. Ventilation effectiveness as an indicator of occupant exposure to particles from indoor sources, Building and Environment, 2010, 45 (5): 1214-1224,
    4.    Villafruela, J., Castro, F.,  San José, J., Saint-Martin, J. Comparison of air change efficiency, contaminant removal effectiveness and infection risk as IAQ indices in isolation rooms, Energy and Buildings, 2023; 57: 210-219
    5.    Brown, W.K.; Lynn, C.A. Fundamental clean room concepts. ASHRAE Trans. 1986, 92, 272–287
    6.    Whyte W, Hejab M, Whyte WM, et al. Experimental and CFD airflow studies of a cleanroom with special respect to air supply inlets. Int J Vent. 2010;9(3):197–209
    7.    Qian, H., Li, Y., Nielsen, P. V., & Hyldgaard, C. E. Dispersion of exhalation pollutants in a two-bed hospital ward with a downward ventilation system. Building and Environment, 2008; 43(3), 344–354.
    8.    Yang, Z., Hao, Y. Shi, W. et al Field test of pharmaceutical cleanroom cleanliness subject to multiple disturbance factors, Journal of Building Engineering, 2021; 42: https://doi.org/10.1016/j.jobe.2021.103083
    9.    Bhattacharya, A., Metcalf, A., Nafchi, A. & Mousavi, E. Particle dispersion in a cleanroom – effects of pressurization, door opening and traffic flow, Building Research & Information, 2021; 49:3: 294-307
    10.    Méndez, C.,  J.F. José, S., Villafruela, J.,  F. Castro, F. Optimization of a hospital room by means of CFD for more efficient ventilation, Energy and Buildings, 2008; 10 (5) : 849-854
    11.    Hu, S-C., Angus Shiue, A. Validation and application of the personnel factor for the garment used in cleanrooms, Building and Environment, 2016; 97: 88-95,
    12.    Zhang, F., Shiue, A., Fan, F. et al. Dynamic emission rates of human activity in biological cleanrooms, Building and Environment, 2022; 226: https://doi.org/10.1016/j.buildenv.2022.109777
    13.    Strauss, L., Larkin, J., Max Zhang, K. The use of occupancy as a surrogate for particle concentrations in recirculating, zoned cleanrooms, Energy and Buildings, 2011; 43 (11): 3258-3262
    14.    Saleh, M., Tak, N., Bhattacharya, A. Cleanroom air quality: combined effects of ventilation rate and filtration schemes in a laboratory cleanroom, Building Research & Information, 2023; 51:6: 717-729
    15.    Austin, P. Design and Operation of Clean Rooms, Detroit: Business News Publishing Company, 1970
    16.    Romano, F., Milani, S., Joppolo, C. Airborne particle and microbiological human emission rate investigation for cleanroom clothing combinations, Building and Environment, 2020; 180: https://doi.org/10.1016/j.buildenv.2020.106967

 

Contact us

Call us on either number below

Switchboard: +44 (0)118 918 4000

Customer Services: +44 (0)118 918 4076

We value your trust when sharing your personal data with us. We always treat your data in a fair and respectful manner limited to the purpose above mentioned. If you would like to know more about how we handle your data, please read our privacy notice.

;