The Optimization of Photovoltaic Systems Design Using Mathematical Modeling and QFD-DSM Methods

Kashani, Marziyeh; Amindoust, Atefeh; Karbasian, Mahdi; Sheikh Aboumasoudi, Abbas

doi:10.30486/mjee.2022.696495

Document Type : Review Article

Authors

¹ Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran

² Department of Industrial Engineering, Maleke-Ashtar University of Technology, Isfahan, Iran

https://doi.org/10.30486/mjee.2022.696495

Abstract

In today's industrialized world, to survive in competitive markets, businesses are required to identify the expectations of their customers, whether explicitly or implicitly, and focus on these needs from the planning to the operational level. To produce customer-oriented products, it is important to extract design requirements that meet the identified needs. The purpose of the present study, which has been done on Photovoltaic systems (PV), is to develop a model for the selection of the optimal components required to design a new product. In this regard, Customer Needs (CNs) which have been extracted from the first stage of the systems engineering process have been interpreted to Functional Requirements (FRs) using the first matrix of QFD. They have examined and prioritized by use of Analytical Network Process (ANP). Then FRs have entered the second matrix of QFD and examined along with leveled components based on the alternatives available for each component. Also, the Design Structure Matrix (DSM) has been used to evaluate the effect of elements upon each other in each phase. Finally, the optimal components are selected by the presented multi-objective mathematical model. Accurate assessment of customer needs using a systems engineering framework in addition to extracting important functional requirements to meet the needs as well as selecting the optimal components for new product design, by integrating the three methods QFD, ANP and DSM, using multi-objective mathematical modeling has not been done by other researchers so far.

Keywords

References

[1].Lightsey, B., Systems engineering fundamentals. 2001, DEFENSE ACQUISITION UNIV FT BELVOIR VA.

[2].Chan, L.-K. and M.-L. Wu, Quality function deployment: A literature review. European journal of operational research, 2002. 143(3): p. 463-497.

[3].Roedler, G., et al., Systems engineering leading indicators guide. INCOSE Technical Product Number: INCOSE-TP-2005-001-03. Version, 2007. 2(1).

[4].Hsu, C.-H., A.-Y. Chang, and W. Luo, Identifying key performance factors for sustainability development of SMEs–integrating QFD and fuzzy MADM methods. Journal of Cleaner Production, 2017. 161: p. 629-645.

[5].Govers, C.P., What and how about quality function deployment (QFD). International journal of production economics, 1996. 46: p. 575-585.

[6].Liu, A., et al., Novel two-phase approach for process optimization of customer collaborative design based on fuzzy-QFD and DSM. IEEE Transactions on Engineering Management, 2017. 64(2): p. 193-207.

[7].Shvetsova, O.A., S.C. Park, and J.H. Lee, Application of Quality Function Deployment for Product Design Concept Selection. Applied Sciences, 2021. 11(6): p. 2681.

[8].Chen, B., J. Hu, and W. Chen, DRE-based semi-automation of the axiomatic design transformation: from the functional requirement to the design parameter. Journal of Engineering Design, 2019. 30(7): p. 255-287.

[9].Adams, K.M., Nonfunctional Requirements in Systems Analysis and Design. 2015, University of Maryland University College USA. : Springer International Publishing.

[10]. Saaty, T.L., and L.G. Vargas, Decision making with the analytic network process. Vol. 282. 2006: Springer.

[11]. Browning, T.R., Design structure matrix extensions and innovations: a survey and new opportunities. IEEE Transactions on Engineering Management, 2015. 63(1): p. 27-52.

[12]. Triantaphyllou, E., Multi-criteria decision-making methods, in Multi-criteria decision making methods: A comparative study. 2000, Springer. p. 5-21.

[13]. Jahn, J., Scalarization in multi-objective optimization, in Mathematics of Multi-Objective Optimization. 1985, Springer. p. 45-88.

[14]. Ocampo, L.A., et al., Integrated multiphase sustainable product design with a hybrid quality function deployment–multi-attribute decision-making (QFD-MADM) framework. Sustainable Production and Consumption, 2020. 24: p. 62-78.

[15]. Fargnoli, M. and N. Haber, A practical ANP-QFD methodology for dealing with requirements' inner dependency in PSS development. Comput. Ind. Eng., 2019. 127: p. 536-548.

[16]. Lam, J.S.L., and K.h. Lai, Developing environmental sustainability by ANP-QFD approach: the case of shipping operations. Journal of Cleaner Production, 2015. 105: p. 275-284.

[17]. Zaim, S., et al., Use of ANP weighted crisp and fuzzy QFD for product development. Expert systems with applications, 2014. 41(9): p. 4464-4474.

[18]. Prasad, K.D., K.V. Subbaiah, and K.N. Rao, Multi-objective optimization approach for cost management during product design at the conceptual phase. Journal of Industrial Engineering International, 2014. 10(1): p. 1-12.

[19]. Yang, Z. and Y. Chen, Fuzzy optimization modeling approach for QFD-based new product design. Journal of Industrial Engineering, 2014. 2014.

[20]. Prasad, K. and S. Chakraborty, A quality function deployment-based model for materials selection. Materials & Design, 2013. 49: p. 525-535.

[21]. Nahm, Y.-E., A novel approach to prioritize customer requirements in QFD based on customer satisfaction function for customer-oriented product design. Journal of Mechanical Science and Technology, 2013. 27(12): p. 3765-3777.

[22]. Cao, Y.L., et al. A Study on Economic Analysis of HOQ. in Applied Mechanics and Materials. 2012. Trans Tech Publ.

[23]. Zhang, Z. and Y. Wang. An improvement of service HOQ based on Economic perspective. in Proceedings of 2011.IEEE International Conference on Grey Systems and Intelligent Services. 2011. IEEE.

[24]. Mayyas, A., et al., Using quality function deployment and analytical hierarchy process for material selection of body-in-white. Materials & Design, 2011. 32(5): p. 2771-2782.

[25]. Malekly, H., S.M. Mousavi, and H. Hashemi, A fuzzy integrated methodology for evaluating conceptual bridge design. Expert Systems with Applications, 2010. 37(7): p. 4910-4920.

[26]. Liu, H.-T. and C.-H. Wang, An advanced quality function deployment model using fuzzy analytic network process. Applied Mathematical Modelling, 2010. 34(11): p. 3333-3351.

[27]. Lee, A.H., et al., An evaluation framework for product planning using FANP, QFD, and multi-choice goal programming. International journal of production research, 2010. 48(13): p. 3977-3997.

[28]. Lin, Y., et al., Using QFD and ANP to analyze the environmental production requirements in linguistic preferences. Expert Systems with Applications, 2010. 37(3): p. 2186-2196.

[29]. Hung, H.-F., H.-P. Kao, and Y.-S. Juang, An integrated information system for product design planning. Expert systems with applications, 2008. 35(1-2): p. 338-349.

[30]. Jariri, F. and S. Zegordi, Quality function deployment, value engineering and target costing, an integrated framework in design cost management: a mathematical programming approach. 2008.

[31]. Kaldate, A., et al., Engineering parameter selection for design optimization during preliminary design. Journal of Engineering Design, 2006. 17(4): p. 291-310.

[32]. Chen*, C.-H., L. Khoo, and L. Jiao, Information deduction approach through quality function deployment for the quantification of the dependency between design tasks. International Journal of Production Research, 2004. 42(21): p. 4623-4637.

[33]. Häberlin, H., Photovoltaics: system design and practice. 2012: John Wiley & Sons.

[34]. Khan, J. and M.H. Arsalan, Solar power technologies for sustainable electricity generation–A review. Renewable and Sustainable Energy Reviews, 2016. 55: p. 414-425.

[35]. Shubbak, M.H., Advances in solar photovoltaics: Technology review and patent trends. Renewable and Sustainable Energy Reviews, 2019. 115: p. 109383.

[36]. Raharjo, H., M. Xie, and A.C. Brombacher, A systematic methodology to deal with the dynamics of customer needs in Quality Function Deployment. Expert Systems with Applications, 2011. 38(4): p. 3653-3662.

[37]. Eppinger, S.D. and T.R. Browning, Design structure matrix methods and applications. 2012: MIT press.

[38]. Reich, Y. and A. Paz, Managing product quality, risk, and resources through resource quality function deployment. Journal of Engineering Design, 2008. 19(3): p. 249-267.

Majlesi Journal of Electrical Engineering

The Optimization of Photovoltaic Systems Design Using Mathematical Modeling and QFD-DSM Methods

References

References

Volume 16, Issue 2 - Serial Number 2
June 2022
Pages 55-72

The Optimization of Photovoltaic Systems Design Using Mathematical Modeling and QFD-DSM Methods

References

References

Volume 16, Issue 2 - Serial Number 2June 2022Pages 55-72

Volume 16, Issue 2 - Serial Number 2
June 2022
Pages 55-72