Toplam Biyolojik Yük Sayısı için Kontrol Tablosu Yaklaşımını Kullanarak Belediye Dağıtım Hattının Mikrobiyolojik Stabilite Değerlendirmesi

Year 2023, , 363 - 383, 01.08.2023

Mostafa Eissa , Engy Rashed , Dalia Essam Eıssa

https://doi.org/10.25279/sak.1035879

Cited By: 1

Abstract

Arka plan: Belediye suyunun mikrobiyolojik kalitesi, insan faaliyetleri, tüketimi ve sonraki işlemler için güvenli kabul edilebilir suyun teslim edilmesini sağlamak için dikkatle izlenmesi ve kontrol edilmesi gereken önemli bir inceleme özelliğidir. Vaka sunumu: Mevcut vaka, farklı kullanım noktalarından bir sağlık tesisinde su dağıtımına ilişkin uzun vadeli veri eğilimlerinin incelenmesi ve analizi için özel bir tür nitelik kontrol çizelgesinin uygulanmasını göstermiştir. Tüm veri kümeleri, tek aralıklı yüksek değerleri gösteren, ancak herhangi bir gözlemlenebilir Spesifikasyon Dışı (OOS) olmaksızın sağa çarpık bir veri dağılım modeli gösterdi. Tüm satırlar, normalliği iyileştiren ve veri kümelerinden aykırı değerleri kaldıran dönüşüme ihtiyaç duymadan bilinen herhangi bir dağıtım modelini takip edemedi. Mikrobiyolojik sonuçların kaydını görselleştirmeye yönelik doğrudan yaklaşım, Laney öznitelik çizelgeleri kullanılarak gerçekleştirilmiştir. Tartışma: Her kullanım noktası, ortalamayı, düzeni, Üst Kontrol Limitini (UCL) ve alarm türlerini görselleştirerek kendine özgü veri eğilimine sahipti. Tesisteki su dağıtım sisteminin net kalitesi, ortalaması alınan ve tek bir süreç-davranış çizelgesinde bir araya getirilen genel okumalardan çıkarılabilir. Bu eğilim grafiğinin uygulanması, olası mevsimsellik belirtileriyle birlikte genlikte tutulma eğiliminde olan biyolojik yük sayımı için bir salınım modeli eğilimi gösterdi. Sonuç: Genel olarak, toplam biyolojik stabilite, Toplam Mikrobiyal Aerobik Sayım (TAMC) açısından zamanla iyileşir. Biyolojik yük seviyesi ve dalgalanmaların büyüklüğü en son izleme durumuna göre düşüyordu.

Keywords

Kutu grafiği, Laney-Nitelik Kontrol Tablosu, Belediye Suyu, Poisson Dağılımı, Olasılık Grafiği

Microbiological Stability Assessment of Municipal Distribution Line Using Control Chart Approach for Total Bioburden Count

Abstract

Background: The microbiological quality of municipal water is an important inspection characteristic that must be carefully monitored and controlled to ensure the delivery of acceptable water that is safe for human activities, consumption and further processing. Case presentation: The current case demonstrated the implementation of a special type of attribute control chart for the examination and analysis of long-term data trends of water distribution in a healthcare facility from different pints-of-use. All datasets showed a right-skewed dispersion pattern of data indicating solitary intermittent high values but without any observable Out-Of-Specification (OOS). All water lines failed to follow any known distribution pattern without the need for transformation which had improved the normality and removed the outliers from datasets. The direct approach for visualizing the record of microbiological results was accomplished using Laney-attribute charts. Discussion: Each use point had its unique trend of data by visualizing the mean, pattern, the Upper Control Limit (UCL) and the alarm types. The net quality of the water distribution system in the facility could be deduced from the overall readings that had been averaged and pooled in a single process-behavior chart. Implementation of this trending chart showed a tendency of oscillation pattern for bioburden count that tended to seize in amplitude with possible signs of seasonality. Conclusion: In general, the overall biological stability is improving with time in terms of the Total Microbial Aerobic Count (TAMC). The Bioburden level and the magnitude of fluctuations were decreasing according to the latest monitoring state.

Keywords

Box plot, Laney-Attribute Control Chart, Municipal Water, Poisson Distribution, Probability Plot

References

• Adams, B. M., Woodall, W. H., & Lowry, C. A. (1992). The use (and misuse) of false alarm probabilities in control chart design. In Frontiers in Statistical Quality Control 4 (pp. 155-168). Physica, Heidelberg.
• Adani, F., Lozzi, P., & Genevini, P. (2001). Determination of biological stability by oxygen uptake on municipal solid waste and derived products. Compost Science & Utilization, 9(2), 163-178.
• Allen, T. T. (2019). Software overview and methods review: Minitab. In Introduction to Engineering Statistics and Lean Six Sigma (pp. 575-600). Springer, London.
• Best, M. (2006). Walter A Shewhart, 1924, and the Hawthorne factory. Quality And Safety In Health Care, 15(2), 142-143. https://doi.org/10.1136/qshc.2006.018093
• Bordner, R., Winter, J. A., and Scarpino, P. (Eds.). (1978). Microbiological methods for monitoring the environment: water and wastes (Vol. 600). Environmental Protection Agency, Office of Research and Development, Environmental Monitoring and Support Laboratory. U.S. Government Printing Office.
• Chapman, D. V. (Ed.). (1996). Water quality assessments: a guide to the use of biota, sediments and water in environmental monitoring (2nd ed.). CRC Press.
• Eissa, M. E. A. Extended application of statistical process control-quantitative risk assessment techniques to monitor surgical site infection rates. International Medicine. 2019; 1 (4), 225-230.
• EİSSA, M., Rashed, E. and Eissa, D. (2021). Implementation of Modified Q-Control Chart in Monitoring of Inspection Characteristics with Finite Quantification Sensitivity Limits: A Case Study of Bioburden Enumeration in Capsule Shell. El-Cezeri, 8(3), 1093-1107.
• Essam Eissa, M. (2017a). Determination of the Microbiological Quality of Feed City Water to Pharmaceutical Facility: Distribution Study and Statistical Analysis. ATHENS JOURNAL OF SCIENCES, 4(2), 143-160. https://doi.org/10.30958/ajs.4-2-4
• Essam Eissa, M. (2017b). Monitoring of Cryptosporidium spp. Outbreaks Using Statistical Process Control Tools and Quantitative Risk Analysis Based on NORS Long-term Trending. Microbiology Journal, 9(1), 1-7. https://doi.org/10.3923/mj.2019.1.7
• Khan, R. M. (2013). Problem solving and data analysis using minitab: A clear and easy guide to six sigma methodology. John Wiley & Sons.
• Lieberman, G. J. (1965). Statistical process control and the impact of automatic process control. Technometrics, 7(3), 283-292.
• Mohammed, M. A., & Laney, D. (2006). Overdispersion in health care performance data: Laney’s approach. BMJ Quality & Safety, 15(5), 383-384.
• Moore, S. S., & Murphy, E. (2013). Process visualization in medical device manufacture: an adaptation of short run SPC techniques. Quality Engineering, 25(3), 247-265.
• Noskievičová, D. (2013). Complex control chart interpretation. International Journal of Engineering Business Management, 5(Godište 2013), 5-13.
• Prest, E., Hammes, F., van Loosdrecht, M., & Vrouwenvelder, J. (2016). Biological Stability of Drinking Water: Controlling Factors, Methods, and Challenges. Frontiers In Microbiology, 7. https://doi.org/10.3389/fmicb.2016.00045
• Ramirez, J. G. (2012). Control chart for complex systems with trended mean and non-constant variance (Doctoral dissertation).
• Sciortino, J. A., & Ravikumar, R. (2009). Water quality monitoring, standards and treatment. Bay of Bengal Programme, 1-18.
• Şengöz, N. (2018). Control Charts to Enhance Quality. Quality Management Systems - A Selective Presentation Of Case-Studies Showcasing Its Evolution, 153-194. https://doi.org/10.5772/intechopen.73237
• World Health Organization. (2011). Guidelines for drinking-water quality (3rd ed.). WHO chronicle, 38(4), 104-108.
• World Health Organization. (2012). Environmental Monitoring of Clean Rooms in Vaccine Manufacturing Facilities: Points to consider for manufacturers of human vaccines. Department World Health Organization (WHO), Geneva, Switzerland, 21-29.
• Wu, H., Zhou, Z., Zhang, Y., Chen, T., Wang, H., & Lu, W. (2012). Fluorescence-based rapid assessment of the biological stability of landfilled municipal solid waste. Bioresource Technology, 110, 174-183.