Dynamic modeling for product family evolution combined with artificial neural network based forecasting model: A study of iPhone evolution

Sumana Biswas · Ismail Mohamed Ali · Ripon Kumar Chakrabortty · Hasan Hüseyin Turan · Sondoss Elsawah · Michael J. Ryan

22 citations0/0 files storedTechnological Forecasting and Social Change

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Product Development and Customization Technology Assessment and Management Innovation Diffusion and Forecasting

Abstract

Products continuously evolve over time. Realizing the pattern of product family evolution along with proper estimation of features for future products has been regarded as a critical issue for business success. Focusing on this issue, a dynamic model for product family evolution combined with forecasting is proposed in this research work. The proposed model considers the influence of market demand, customer needs and technological requirements that are time-dependent. The methodology is a four-phase model. For each phase, the effectiveness of the developed approach is demonstrated with numerical simulation results and validated with a case study of Apple's iPhone product family.

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References

2018PRODUCT DESIGN AND DEVELOPMENT 1982Control problems of grey systems 1998Forecasting with artificial neural networks:2016Sensitivity analysis of environmental models: A systematic review with practical workflow 2008The use of grey relational analysis in solving multiple attribute decision-making problems 1997The power of product platforms : building value and cost leadership 1992The product family and the dynamics of core capability 2002A Comparative Study of Using Grey Relational Analysis in Multiple Attribute Decision Making Problems

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