Skip to main content
Log in

Modeling and evaluation of product quality at conceptual design stage

  • Original Article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

Abstract

Quality of a product is a function of many variables. These have been identified, and modeled in terms of quality digraph. The nodes in the digraph represent the quality features and the edges represent the degree of influence among these. An equivalent matrix representation of the digraph is developed to define the product system quality function (PSQF). Quality index (QI) is defined as a ratio of the actual to the ideal values of PSQF. The designer may use this index to evaluate and compare alternative designs and choose the best among these from the perspective of quality. A high value of QI indicates that the product structure is closer to the ideal state. The presented model is illustrated with an example.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Ahmed H, Chateauneuf A (2014) Optimal number of tests to achieve and validate product reliability. Reliab Eng Syst Saf. doi:10.1016/jress.2014.04.014

    Google Scholar 

  • Akao Y (1990) Quality function deployment (QFD). Integrating customer requirements into product design, Cambridge

    Google Scholar 

  • Akao Y, Mazur GH (2003) The leading edge in QFD: past, present and future. Int J Qual Reliab Manag 20(1):20–35

    Article  Google Scholar 

  • Al- Hakim L, Kusiak A, Mathew J (2000) A graph-theoretic approach to conceptual design with functional perspectives. Comput Aided Des 32(14):867–875

    Article  Google Scholar 

  • Baldwin C, Clark K (1999) Design Rules. Harvard University Press, Boston

    Google Scholar 

  • Bouti A, Kadi DA (1994) A state-of-the-art review of FMEA/FMECA. Int J Reliab Qual Saf Eng 1(4):515–543

    Article  Google Scholar 

  • Brad S (2008) Vectors of innovation to support quality initiatives in the framework of ISO 9001: 2000. Int J Qual Reliab Manag 25(7):674–693

    Article  Google Scholar 

  • Cristiano JJ, Liker JK, White CC (2000) Customer-driven product development through quality function deployment in the U.S. and Japan. J Prod Innov Manag 17(4):286–308

    Article  Google Scholar 

  • Colledani M, Tolio T, Fischer A, Benoit Iung B, Lanza G, Schmitt R, Váncza J (2014) Design and management of manufacturing systems for production quality. CIRP Ann Manuf Technol 63(2):773–796

    Article  Google Scholar 

  • Collins JA, Hagan BT, Bratt HM (1976) The failure experience matrix: a useful design tool. ASME Trans J Eng Ind 98(3):1074–1079

    Article  Google Scholar 

  • Coulibaly A, Mutel B, Ait-Kadi D (2007) Product modeling framework for behavioral performance evaluation at design stage. Comput Ind 58(6):438–449

    Article  Google Scholar 

  • Coulibaly A, Houssin R, Mutel B (2008) Maintainability and safety indicators at design stage for mechanical products. Comput Ind 59(5):438–449

    Article  Google Scholar 

  • Darvish M, Yasaei M, Saeedi A (2009) Application of the graph theory and matrix methods to contractor ranking. Int J Proj Manag 27(6):610–619

    Article  Google Scholar 

  • De Toni A, Tonchia S (1998) Manufacturing flexibility: a literature review. Int J Prod Res 36(6):1587–1617

    Article  MATH  Google Scholar 

  • Dekkers R, Chang CM, Kreutzfeldt J (2013) The interface between “product design and engineering” and manufacturing: a review of the literature and empirical evidence. Int J Prod Econ 144(1):316–333

    Article  Google Scholar 

  • Deo N (1974) Graph theory. Prentice Hall, Englewood Cliffs

    MATH  Google Scholar 

  • Düpow H, Blount G (1997) A review of reliability prediction. Aircr Eng Aerosp Technol 69(4):356–362

    Article  Google Scholar 

  • Ebeling CE (2000) An introduction to reliability and maintainability engineering. Tata McGraw-Hill Education Private Limited, New Delhi

    Google Scholar 

  • Fulton Suri J, Marsh M (2000) Scenario building as an ergonomics method in consumer product design. Appl Ergon 31(2):151–157

    Article  Google Scholar 

  • Gagnon B, Leduc R, Savard L (2012) From conventional to a sustainable engineering design process: different shades of sustainability. J Eng Des 23(1):49–74

    Article  Google Scholar 

  • Gao X, Barabady J, Markeset T (2010) An approach for prediction of petroleum production facility performance considering arctic influence factors. Reliab Eng Syst Saf 95(8):837–846

    Article  Google Scholar 

  • Gupta P, Gandhi OP (2013) Ontological modeling of spatial shaft-position knowledge for steam turbine rotor. Int J Syst Assur Eng Manag 4(3):284–292

    Article  Google Scholar 

  • Gupta P, Gupta S, Gandhi OP (2013) Modeling and evaluation of MTTR at product design stage based on contextual criteria. J Eng Des 24(7):499–523

    Article  Google Scholar 

  • Harary F (1994) Graph theory, Addison–Wesley: reading. McGraw-Hill, Massachusetts

    Google Scholar 

  • Heidari F, Loucopoulos P (2013) Quality evaluation framework (QEF): modeling and evaluating quality of business process. Int J Account Inf Syst. doi:10.1016/j.accinf.2013.09.002

    Google Scholar 

  • Hempelmann F, Engelen A (2014) Integration of finance with marketing and R&D in new product development: the role of project stage. J Prod Innov Manag. doi:10.1111/jpim.12237

    Google Scholar 

  • Hsu Y-H, Fang W (2009) Intellectual capital and new product development performance: the mediating role of organizational learning capability. Technol Forecast Soc Chang 76(5):664–677

    Article  Google Scholar 

  • Hua Z, Yang J, Coulibaly S, Zhang B (2006) Integration TRIZ with problem-solving tools: a literature review from 1995 to 2006. Int J Bus Innov Res 1(1–2):111–128

    Article  Google Scholar 

  • Inman RR, Blumenfeld DE, Huang N, Li J (2003) Designing production systems for quality: research opportunities from an automotive industry perspective. Int J Prod Res 41(9):1953–1971

    Article  Google Scholar 

  • Jiang P, Guo B, Lim J-H, Zuo MJ (2010) Group judgement of relationship between product reliability and quality characteristics based on Bayesian theory and expert’s experience. Expert Syst Appl 37(10):6844–6849

    Article  Google Scholar 

  • Jin S, Zheng C, Yu K, Lai X (2010) Tolerance design optimization on cost-quality trade-off using shapely value method. J Manuf Syst 29(4):142–150

    Article  Google Scholar 

  • Bouza-Rodríguez JB, Alberto C-C, Agustín M-D (2014) A graphical method to assist quality decisions throughout the product development process. Qual Eng 26(4):467–478

    Article  Google Scholar 

  • Jurkat WB, Ryser HJ (1966) Matrix factorization of determinants and permanents. J Algebra 3(1):1–27

    Article  MathSciNet  MATH  Google Scholar 

  • Karunanithi N, Whitley D, Malaiya YK (1992) Using neural networks in reliability prediction. Softw IEEE 9(4):53–59

    Article  Google Scholar 

  • Kayrbekova D, Barbadi A, Markeset T (2011) Maintenance cost evaluation of a system to be used in Arctic conditions: a case study. J Qual Maint Eng 17(4):320–336

    Article  Google Scholar 

  • Kim S, Baek JW, Moon SK, Jeon SM (2015) A new approach for product design by integrating assembly and disassembly sequence structure planning. In: Proceedings of the 18th Asia pacific symposium on intelligent and evolutionary systems, proceedings in adaptation, learning and optimization, vol 1. Springer International Publishing, Switzerland, pp 247–257. doi:10.1007/978-3-319-13359-1_20

  • Kumar VNA, Gandhi OP (2011) Quantification of human error in maintenance using graph theory and matrix approach. Qual Reliab Eng Int 27:1145–1172

    Article  Google Scholar 

  • Lawson B, Krause D, Potter A (2014) Improving supplier new product development performance: the role of supplier development. J Prod Innov Manag. doi:10.1111/jpim.12231

    Google Scholar 

  • Lee J, Ni J, Djurdjanovic D, Qiu H, Liao H (2006) Intelligent prognostics tools and e-maintenance. Comput Ind 57(6):476–489

    Article  Google Scholar 

  • Lee WS, Grosh DL, Tillman FA, Lie CH (1985) Fault tree analysis, methods, and applications: a review. IEEE Trans Reliab 34(3):194–203

    Article  MATH  Google Scholar 

  • Yutong LI, Wang Y, Duffy AHB (2014) Computer-based creativity enhanced conceptual design model for non-routine design of mechanical systems. Chin J Mech Eng. doi:10.3901/CJME.2014.0620.117

    Google Scholar 

  • Liao H, Zhao W, Guo H (2006) Predicting remaining useful life of an individual unit using proportional hazards model and logistic regression model. In: IEEE Reliability and Maintainability Symposium, RAMS’06, pp 127–132

  • List D (2001) The consensus group technique in social research. Field Res 13(4):277–290

    Article  Google Scholar 

  • Morita M, Machuca Jose AD, Flynn EJ, Pérez de los Ríos JL (2014) Aligning product characteristics and the supply chain process: a normative perspective. Int J Prod Econ. doi:10.1016/j.ijpe.2014.09.024

    Google Scholar 

  • Nada OA, ElMaraghly HA, ElMaraghly WH (2006) Quality prediction in manufacturing system design. J Manuf Syst 25(3):153–171

    Article  Google Scholar 

  • Paramasivam V, Senthil V (2009) Analysis and evaluation of product design through design aspects using digraph and matrix approach. Int J Interact Des Manuf 3(1):13–23

    Article  Google Scholar 

  • Petersen KJ, Handfield RB, Ragatz GL (2005) Supplier integration into new product development: coordinating product, process and supply chain. J Oper Manag 22(3–4):371–388

    Article  Google Scholar 

  • Presig HA (2009) A graph-theory-based approach to the analysis of large-scale plants. Comput Chem Eng 33(3):598–604

    Article  Google Scholar 

  • Ribeiro JS, Gomes J, de O (2014) Extending producer responsibility: framework to incorporate life cycle assessment in aircraft preliminary design based on take-back policies. In: IEEE international conference on innovative design and manufacturing, Montreal, 13–15 August 2014

  • Ross PJ (1996) Taguchi techniques for quality engineering, 2nd edn. McGraw Hill, New York

    Google Scholar 

  • Saleh JH, Mark G, Jordan NC (2009) Flexibility: a multi-disciplinary literature review and research agenda for design flexible engineering systems. J Eng Des 20(3):307–323

    Article  Google Scholar 

  • Sanchez R, Mahoney JT (1996) Modularity, flexibility, and knowledge management in product and organization design. Strateg Manag J 17(S2):63–76

    Article  Google Scholar 

  • Sapuan SM, Mansor MR (2014) Concurrent engineering approach in the development of composite products: a review. Mater Des 58:161–167. doi:10.1016/j.matdes.2014.01.059

    Article  Google Scholar 

  • Schilling EG, Neubauer DV (2012) Acceptance sampling in quality control. CRC Press, New York

    MATH  Google Scholar 

  • Sehgal R, Gandhi OP, Angra S (2000) Fault location of tribo-mechanical systems: a graph theory and matrix approach. Reliab Eng Syst Saf 70(1):1–14

    Article  Google Scholar 

  • Sharma BC, Gandhi OP (2008) Digraph-based reliability assessment of tribo-pair. Ind Lubr Tribol 60(3):153–163

    Article  Google Scholar 

  • Sheng ILS, Kok-Soo T (2010) Eco-efficient product design using theory of inventive problem solving (TRIZ) principles. Am J Appl Sci 7(6):852–858

    Article  Google Scholar 

  • Simon AT, Di Serio LC, Pires SRI, Martins GS (2014) Evaluating supply chain management: a methodology based on a theoretical model. http://www.anpad.org.br/rac. Accessed 14 Oct 2014

  • Sousa GWL, Carpinetti LCR, Groesbeck RL, Aken EV (2005) Conceptual design of performance measurement and management systems using structured engineering approach. Int J Prod Perform Meas 54(5–6):385–399

    Article  Google Scholar 

  • Taguchi G (1986) Introduction to quality engineering. Asian Productivity Organisation, Tokyo

    Google Scholar 

  • Tan CL, Vonderembs MA (2006) Mediating effects of computer-aided design usage: from concurrent engineering to product development. J Oper Manag 24(5):494–510

    Article  Google Scholar 

  • Tiwari V, Jain PK, Tandon P (2014) Design decision automation support through knowledge template CAD model. Comput Aided Des Appl. doi:10.1080/16864360.2014.949580

    Google Scholar 

  • Tsai YT (2005) The preliminary investigation of system reliability and maintainability to develop availability sound designs. J Eng Des 16(5):459–471

    Article  Google Scholar 

  • Uddin A, Campean IF, Khan MK (2014) Complex product architecture analysis using an integrated approach. In: IOP conference series: material science and engineering, vol 65(1). IOP Publishing

  • Upton DM (1995) What really makes factories flexible? Harv Bus Rev 73(4):74–84

    Google Scholar 

  • Vasantha GVA, Roy R, Lelah A, Brissaud D (2012) A review of product-service systems design methodologies. J Eng Des 23(9):635–659

    Article  Google Scholar 

  • Veryzer RW (1993) Aesthetic response and the influence of design principles on product preferences. Adv Consum Res 20(1):224–228

    Google Scholar 

  • Wang HH, Yang QP (2014) Theoretical framework for innovation design with optimised customization. Appl Mech Mater 599–601:2206–2209

    Article  Google Scholar 

  • Whitney DE (2002) Physical limits to modularity. Working paper series, ESD-WP-2003-01.03, MIT, USA. http://www.aeroinside.com/incidents/type/b788/boeing-787-8-dreamliner. Accessed 11 March 2015

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shashank Gupta.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gupta, S., Kota, S. & Mishra, R.P. Modeling and evaluation of product quality at conceptual design stage. Int J Syst Assur Eng Manag 7 (Suppl 1), 163–177 (2016). https://doi.org/10.1007/s13198-015-0357-3

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-015-0357-3

Keywords

Navigation