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

计算机科学 新产品开发 人工神经网络 产品设计 产品(数学) 可靠性(半导体) 模糊逻辑 过程(计算) 工业工程 需求预测 运筹学 数据挖掘
作者
Sumana Biswas,Ismail Ali,Ripon K. Chakrabortty,Hasan Hüseyin Turan,Sondoss Elsawah,Michael J. Ryan
出处
期刊:Technological Forecasting and Social Change [Elsevier BV]
卷期号:178: 121549-121549
标识
DOI:10.1016/j.techfore.2022.121549
摘要

• The proposed model combines the evolution model with the forecasting model. • It considers market demand, customer needs and technological requirements together. • The ANN model can forecast the specification of some features of future product. • The proposed model is applicable in the engineering design of product development. 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. In this model the evaluations of product family evolution are based on the Grey Relational Analysis and Fuzzy Analytical Hierarchy Process. Sensitivity is performed to investigate the reliability of the model. In addition, a data-driven neural network-based forecasting model is proposed that can forecast the specification of the most influential features of future product with a reasonable accuracy. This forecasting model utilizes the information of the previous generation’s product. 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. The case study shows that the approach is very effective to identify the most influential key design features and best performed products that will influence the evolution design of future product.
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