Sustainable design of the household water treatment systems using a novel integrated fuzzy QFD and LINMAP approach: a case study of Iran

Abstract

There is a high possibility that pursuit of water policies goals which could have impacts on water security. Decision makers are interested in developing the water management systems to establish sustainable demand for secured water. The aim of the paper is to analyze the sustainability indicators (SIs) related to designing of the household water treatment system (HWTS). Thirteen criteria like solid waste, liquid waste, air pollution, initial cost, operation and maintenance costs, transport cost, satisfaction, purchasing power, social acceptance, health, reliability, after sales service, and technological capacity in four categories including environmental, economic, social and technical aspects have been considered. These criteria affect HWTS. These criteria are evaluated by taking into account the customer requirements (CRs) and design requirements (DRs) of HWTS. The objective of this study is to design sustainable HWTSs. This is achieved by an analytical approach integrating quality function deployment (QFD) and a linear programming technique for multidimensional analysis of preference (LINMAP) under fuzzy environment for guiding HWTSs manufactures. Fuzzy QFD-LINMAP approach is used to investigate the roles of the study criteria and the interrelationships between them. The HWTSs development in the city of Behbahan, Iran, is considered. The findings indicate that operation and maintenance costs (with value of 0.0522) is the most important sustainability indicator in the CRs and the least important is technical capacity (with value of 0.1096). The most important sustainability indicator in DRs is purchasing power (with value of 0.0207), and the least important is liquid waste (with value of 0.1469). The results show that sustainability strategies are selected for water treatment systems constraints and the model provides compromise solutions to help decision makers evaluate suitable water policy mix.

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Abbreviations

HWTS:

Household water treatment system

V-AC:

Volt-alternative current

V-DC:

Volt-direct current

HOQ:

House of quality

LINMAP:

Linear programming technique for multidimensional analysis of preference

Sis:

Sustainability indicators

CRs:

Customer requirements

DRs:

Design requirements

MCDM:

Multi-criteria decision making

LEC:

Low energy consumption

LC:

Low cost

EA:

Easy access

VDS:

Variation in dimension and size

PQ:

Production quality

DR:

Depreciation reduction

PE:

Production efficiency

SW:

Solid waste

LW:

Liquid waste

AP:

Air pollution

IC:

Initial cost

OMC:

Operation and maintenance costs

TC:

Transport cost

S:

Satisfaction

PP:

Purchasing power

SA:

Social acceptance

H:

Health

R:

Reliability

ASS:

After sales service

TC:

Technological capacity

SPPM:

Strategic position of the product in the market

QI:

Quality improvement

EI:

Easy installation

CR:

Cost reduction

PWR:

Product waste recycle

OM:

Operation and maintenance

PECR:

Product energy consumption reduction

References

  1. Ahmed, F. E., Hashaikeh, R., & Hilal, N. (2019). Solar powered desalination—Technology, energy and future outlook. Desalination, 453, 54–76. https://doi.org/10.1016/j.desal.2018.12.002.

    CAS  Article  Google Scholar 

  2. Akao, Y., & Mazur, G. H. (2003). The leading edge in QFD: Past, present and future. International Journal of Quality and Reliability Management, 20, 20–35. https://doi.org/10.1108/02656710310453791.

    Article  Google Scholar 

  3. Altun, K., Zedtwitz, M. V., & Dereli, T. (2016). Multi-issue negotiation in quality function deployment: Modified Even-Swaps in new product development. Computers and Industrial Engineering, 92, 31–49. https://doi.org/10.1016/j.cie.2015.11.017.

    Article  Google Scholar 

  4. Asgharpour, M. J. (2011). Multiple Criteria Decision Making (9th ed.). Tehran: Tehran University Press. ((in Persian)).

    Google Scholar 

  5. Binks, A. N., Kenway, S. J., Lant, P. A., & Head, B. W. (2016). Understanding Australian household water-related energy use and identifying physical and human characteristics of major end uses. Journal of Cleaner Production, 135, 892–906. https://doi.org/10.1016/j.jclepro.2016.06.091.

    Article  Google Scholar 

  6. Bolar, A. A., Tesfamariam, S., & Sadiq, R. (2017). Framework for prioritizing infrastructure user expectations using Quality Function Deployment (QFD). International Journal of Sustainable Built Environment, 6, 16–29. https://doi.org/10.1016/j.ijsbe.2017.02.002.

    Article  Google Scholar 

  7. Bouchereau, V., & Rowlands, H. (2000). Methods and techniques to help quality function deployment (QFD). Benchmarking An International Journal, 7, 8–19. https://doi.org/10.1108/14635770010314891.

    Article  Google Scholar 

  8. Cardoso, J. F., Casarotto Filho, N., & Cauchick Miguel, P. A. (2015). Application of Quality Function Deployment for the development of an organic product. Food Quality and Preference, 40, 180–190. https://doi.org/10.1016/j.foodqual.2014.09.012.

    Article  Google Scholar 

  9. Chen, A., Dinar, M., Gruenewald, T., Wang, M., Rosca, J., & Kurfess, T. R. (2017). Manufacturing apps and the Dynamic House of Quality: Towards an industrial revolution. Manufacturing Letters, 13, 25–29. https://doi.org/10.1016/j.mfglet.2017.05.005.

    Article  Google Scholar 

  10. Chowdhary, P., & Bharagava, R. N. (2020). Green technologies and environmental sustainability. Environment, Development and Sustainability, 22, 2699–2701. https://doi.org/10.1007/s10668-018-00304-1.

    Article  Google Scholar 

  11. Chowdhury, M. M. H., & Quaddus, M. A. (2016). A multi-phased QFD based optimization approach to sustainable service design. International Journal of Production Economics, 171, 165–178. https://doi.org/10.1016/j.ijpe.2015.09.023.

    Article  Google Scholar 

  12. Daniel, D., Diener, A., Pande, S., Jansen, S., Marks, S., Meierhofer, R., et al. (2019). Understanding the effect of socio-economic characteristics and psychosocial factors on household water treatment practices in rural Nepal using Bayesian Belief Networks. International Journal of Hygiene and Environmental Health, 222, 847–855. https://doi.org/10.1016/j.ijheh.2019.04.005.

    CAS  Article  Google Scholar 

  13. Dikmen, I., Talat Birgonul, M., & Kiziltas, S. (2005). Strategic use of quality function deployment (QFD) in the construction industry. Building and Environment, 40, 245–255. https://doi.org/10.1016/j.buildenv.2004.07.001.

    Article  Google Scholar 

  14. Dinçer, H., Yüksel, S., & Martínez, L. (2019). Balance d scorecard-base d analysis about European energy investment policies : A hybrid hesitant fuzzy decision-making approach with Quality Function Deployment. Expert Systems With Applications, 115, 152–171. https://doi.org/10.1016/j.eswa.2018.07.072.

    Article  Google Scholar 

  15. Fargnoli, M., & Haber, N. (2019). A practical ANP-QFD methodology for dealing with requirements’ inner dependency in PSS development. Computers and Industrial Engineering, 127, 536–548. https://doi.org/10.1016/j.cie.2018.10.042.

    Article  Google Scholar 

  16. Fetanat, A. (2015). Location of solar power plant for sustainable development using a combined decision support system (Case Study: Iran, Behbahan City). In The first international conference on geographical sciences. https://www.civilica.com/Paper-GSCONFKH01-GSCONFKH01_379.

  17. Fetanat, A., & Khorasaninejad, E. (2015). A novel hybrid MCDM approach for offshore wind farm site selection: A case study of Iran. Ocean and Coastal Management, 109, 17–28. https://doi.org/10.1016/j.ocecoaman.2015.02.005.

    Article  Google Scholar 

  18. Fetanat, A., Mofid, H., Mehrannia, M., & Shafipour, G. (2019). Informing energy justice based decision-making framework for waste-to-energy technologies selection in sustainable waste management: A case of Iran. Journal of Cleaner Production, 228, 1377–1390. https://doi.org/10.1016/j.jclepro.2019.04.215.

    Article  Google Scholar 

  19. Getmiri, B. (2004). Regional physical spatial plans water uses and resources (First). Urban and architecture researches center of Iran (in Persian).

  20. Giret, A., Trentesaux, D., & Prabhu, V. (2015). Sustainability in manufacturing operations scheduling: A state of the art review. Journal of Manufacturing Systems, 37, 126–140. https://doi.org/10.1016/j.jmsy.2015.08.002.

    Article  Google Scholar 

  21. Gude, V. G. (2016). Desalination and sustainability—An appraisal and current perspective. Water Research, 89, 87–106. https://doi.org/10.1016/j.watres.2015.11.012.

    CAS  Article  Google Scholar 

  22. Arafat, H. A. (2017). Desalination Sustainability: A Technical, Socioeconomic, and Environmental Approach. Elsevier. https://doi.org/10.1016/B978-0-12-809791-5.00001-8.

    Article  Google Scholar 

  23. Heizer, J., Render, B., & Munson, C. (2016). Principles of operations management: sustainability and supply chain management (Tenth).

  24. Hendiani, S., Sharifi, E., Bagherpour, M., & Ghannadpour, S. F. (2019). A multi-criteria sustainability assessment approach for energy systems using sustainability triple bottom line attributes and linguistic preferences. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-019-00546-7.

    Article  Google Scholar 

  25. Kahraman, C., Ertay, T., & Büyüközkan, G. (2006). A fuzzy optimization model for QFD planning process using analytic network approach. European Journal of Operational Research, 171, 390–411. https://doi.org/10.1016/j.ejor.2004.09.016.

    Article  Google Scholar 

  26. Kasaei, A., Abedian, A., & Milani, A. S. (2014). An application of Quality Function Deployment method in engineering materials selection. Materials and Design, 55, 912–920. https://doi.org/10.1016/j.matdes.2013.10.061.

    Article  Google Scholar 

  27. Kutschenreiter-praszkiewicz, I. (2013). Application of neural network in QFD matrix. Journal of Intelligent Manufacturing, 24, 397–404. https://doi.org/10.1007/s10845-011-0604-7.

    Article  Google Scholar 

  28. Lam, J. S. L. (2015). Designing a sustainable maritime supply chain : A hybrid QFD—ANP approach. Transportation Research Part E, 78, 70–81. https://doi.org/10.1016/j.tre.2014.10.003.

    Article  Google Scholar 

  29. Lam, J. S. L., & Bai, X. (2016). A quality function deployment approach to improve maritime supply chain resilience. Transportation Research Part E, 92, 16–27. https://doi.org/10.1016/j.tre.2016.01.012.

    Article  Google Scholar 

  30. Liang, H., Ren, J., Gao, Z., Gao, S., & Luo, X. (2016). Identification of critical success factors for sustainable development of biofuel industry in China based on grey decision-making trial and evaluation laboratory (DEMATEL). Journal of Cleaner Production, 131, 500–508. https://doi.org/10.1016/j.jclepro.2016.04.151.

    Article  Google Scholar 

  31. Lin, C., & Wu, W. (2008). A causal analytical method for group decision-making under fuzzy environment. Expert Systems with Applications, 34, 205–213. https://doi.org/10.1016/j.eswa.2006.08.012.

    Article  Google Scholar 

  32. Linke, B. S., Corman, G. J., Dornfeld, D. A., & Tönissen, S. (2013). Sustainability indicators for discrete manufacturing processes applied to grinding technology. Journal of Manufacturing Systems, 32, 556–563. https://doi.org/10.1016/j.jmsy.2013.05.005.

    Article  Google Scholar 

  33. Mahmood, Q., Baig, S. A., Nawab, B., Shafqat, M. N., Pervez, A., & Zeb, B. S. (2011). Development of low cost household drinking water treatment system for the earthquake affected communities in Northern Pakistan. Desalination, 273(2–3), 316–320. https://doi.org/10.1016/j.desal.2011.01.052.

    CAS  Article  Google Scholar 

  34. Mehran, M., Mohammad, Z., Mojtaba, Y., & AbdulHussein, H. (2017). Determination of wheat water productivity in sprinkler and surface irrigation systems (Case Study in Behbahan). Journal of Physical Geography, 1–28 (in Persian).

  35. Memari, A., Dargi, A., Akbari Jokar, M. R., Ahmad, R., & Abdul Rahim, A. R. (2019). Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method. Journal of Manufacturing Systems, 50, 9–24. https://doi.org/10.1016/j.jmsy.2018.11.002.

    Article  Google Scholar 

  36. Mkwate, R. C., Chidya, R. C. G., & Wanda, E. M. M. (2017). Assessment of drinking water quality and rural household water treatment in Balaka District, Malawi. Physics and Chemistry of the Earth, 100, 353–362. https://doi.org/10.1016/j.pce.2016.10.006.

    Article  Google Scholar 

  37. Mohammadyari, F., Pourkhabaz, H., Tavakoli, M., & Aghdar, H. (2015). Mapping vegetation and monitoring its changes using remote sensing and GIS techniques (case study: Behbahan city). Scientific - Research Quarterly of Geographical Data (SEPEHR), 23–34 (in Persian).

  38. Montoya, J., Cartes, I., & Zumelzu, A. (2020). Indicators for evaluating sustainability in Bogota’s informal settlements: Definition and validation. Sustainable Cities and Society, 53, 110–896. https://doi.org/10.1016/j.scs.2019.101896.

    Article  Google Scholar 

  39. Muncan, J., Matovic, V., Nikolic, S., Askovic, J., & Tsenkova, R. (2020). Aquaphotomics approach for monitoring different steps of purification process in water treatment systems. Talanta, 206, 120–253. https://doi.org/10.1016/j.talanta.2019.120253.

    CAS  Article  Google Scholar 

  40. Mwabi, J. K., Adeyemo, F. E., Mahlangu, T. O., Mamba, B. B., Brouckaert, B. M., Swartz, C. D., et al. (2011). Household water treatment systems: A solution to the production of safe drinking water by the low-income communities of Southern Africa. Physics and Chemistry of the Earth, 36, 1120–1128. https://doi.org/10.1016/j.pce.2011.07.078.

    Article  Google Scholar 

  41. Na, L., Xiaofei, S., Yang, W., & Ming, Z. (2012). Decision making model based on QFD method for power utility service improvement. Systems Engineering Procedia, 4, 243–251. https://doi.org/10.1016/j.sepro.2011.11.072.

    Article  Google Scholar 

  42. Nazmi, I., Ab, K., Salleh, K., & Sahari, M. (2017). Design and development of platform deployment arm (PDA) for boiler header inspection at thermal power plant by using the house of quality ( HOQ ) approach. Procedia Computer Science, 105, 296–303. https://doi.org/10.1016/j.procs.2017.01.225.

    Article  Google Scholar 

  43. Ojomo, E., Elliott, M., Goodyear, L., Forson, M., & Bartram, J. (2015). Sustainability and scale-up of household water treatment and safe storage practices: Enablers and barriers to effective implementation. International Journal of Hygiene and Environmental Health, 218, 704–713. https://doi.org/10.1016/j.ijheh.2015.03.002.

    CAS  Article  Google Scholar 

  44. Osiro, L., Lima-junior, F. R., Cesar, L., & Carpinetti, R. (2018). A group decision model based on quality function deployment and hesitant fuzzy for selecting supply chain sustainability metrics. Journal of Cleaner Production, 183, 964–978. https://doi.org/10.1016/j.jclepro.2018.02.197.

    Article  Google Scholar 

  45. Park, S., Ham, S., & Lee, M. (2012). How to improve the promotion of Korean beef barbecue, bulgogi, for international customers. An application of quality function deployment q. Appetite, 59, 324–332. https://doi.org/10.1016/j.appet.2012.05.008.

    Article  Google Scholar 

  46. Rabia, F., Divyam, N., Alvaro, L.-P., Troy, H., Rabi, H. M., Bassel, D., Samia, M., & Martin, K. (2015). Renewable Energy in the Water, Energy & Food Nexus.

  47. Ramírez, Y., Cisternas, L. A., & Kraslawski, A. (2017). Application of House of Quality in assessment of seawater pretreatment technologies. Journal of Cleaner Production, 148, 223–232. https://doi.org/10.1016/j.jclepro.2017.01.163.

    CAS  Article  Google Scholar 

  48. Ren, J. (2018a). Life cycle aggregated sustainability index for the prioritization of industrial systems under data uncertainties. Computers and Chemical Engineering, 113, 253–263. https://doi.org/10.1016/j.compchemeng.2018.03.015.

    CAS  Article  Google Scholar 

  49. Ren, J. (2018b). Technology selection for ballast water treatment by multi- stakeholders : A multi-attribute decision analysis approach based on the combined weights and extension theory. Chemosphere, 191, 747–760. https://doi.org/10.1016/j.chemosphere.2017.10.053.

    CAS  Article  Google Scholar 

  50. Soni, A., Stagner, J. A., & Ting, D. S. K. (2017). Adaptable wind/solar powered hybrid system for household wastewater treatment. Sustainable Energy Technologies and Assessments, 24, 8–18. https://doi.org/10.1016/j.seta.2017.02.015.

    Article  Google Scholar 

  51. Prathna, T. C., Sharma, S. K., & Kennedy, M. (2018). Nanoparticles in household level water treatment: An overview. Separation and Purification Technology, 199, 260–270. https://doi.org/10.1016/j.seppur.2018.01.061.

    CAS  Article  Google Scholar 

  52. van Halem, D., van der Laan, H., Heijman, S. G. J., van Dijk, J. C., & Amy, G. L. (2009). Assessing the sustainability of the silver-impregnated ceramic pot filter for low-cost household drinking water treatment. Physics and Chemistry of the Earth, 34, 36–42. https://doi.org/10.1016/j.pce.2008.01.005.

    Article  Google Scholar 

  53. Xu, D., Lv, L., Ren, X., Ren, J., & Dong, L. (2018). Route selection for low-carbon ammonia production: A sustainability prioritization framework based-on the combined weights and projection ranking by similarity to referencing vector method. Journal of Cleaner Production, 193, 263–276. https://doi.org/10.1016/j.jclepro.2018.05.054.

    CAS  Article  Google Scholar 

  54. Yang, Q., Yang, S., Qian, Y., & Kraslawski, A. (2015). Application of House of Quality in evaluation of low rank coal pyrolysis polygeneration technologies. Energy Conversion and Management, 99, 231–241. https://doi.org/10.1016/j.enconman.2015.03.104.

    Article  Google Scholar 

  55. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353.

    Article  Google Scholar 

  56. Zaim, S., Sevkli, M., Camgöz-Akdaǧ, H., Demirel, O. F., Yesim Yayla, A., & Delen, D. (2014). Use of ANP weighted crisp and fuzzy QFD for product development. Expert Systems with Applications, 41, 4464–4474. https://doi.org/10.1016/j.eswa.2014.01.008.

    Article  Google Scholar 

  57. Zhang, L., Sovacool, B. K., Ren, J., & Ely, A. (2017). The Dragon awakens : Innovation, competition, and transition in the energy strategy of the People ’ s Republic of China, 1949–2017. Energy Policy, 108(June), 634–644. https://doi.org/10.1016/j.enpol.2017.06.027.

    Article  Google Scholar 

  58. Zheng, H. (2017). Solar Energy Desalination Technology (1st ed.). Amsterdam: Elsevier. https://doi.org/10.1016/B978-0-12-805411-6.00001-4.

    Google Scholar 

  59. Zhou, X., & Schoenung, J. M. (2007). An integrated impact assessment and weighting methodology: Evaluation of the environmental consequences of computer display technology substitution. Journal of Environmental Management, 83, 1–24. https://doi.org/10.1016/j.jenvman.2006.01.006.

    CAS  Article  Google Scholar 

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Acknowledgements

The authors would like to thank Behbahan Branch, Islamic Azad University, Behbahan, Iran, for providing research grant.

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Correspondence to Abdolvahhab Fetanat.

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Fetanat, A., Tayebi, M. Sustainable design of the household water treatment systems using a novel integrated fuzzy QFD and LINMAP approach: a case study of Iran. Environ Dev Sustain (2021). https://doi.org/10.1007/s10668-021-01284-5

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Keywords

  • Household water treatment system
  • House of quality (HOQ)
  • LINMAP
  • Quality function deployment (QFD)
  • Sustainability indicator