Online data-driven concurrent product-process-supply chain design in the early stage of new product development

Abstract

The ability to accelerate the discovery of product innovation ideas is critical for manufacturers with short life cycles, such as smartphones. Companies with short product lifespans require innovative strategies to improve their products based on customer needs. Three-dimensional concurrent engineering (3DCE) has the potential to speed up the process of developing new products. On the other side, the availability of online data, such as social media and intellectual property, has the potential to identify and prioritize product, technology, and supplier opportunities in a cost-effective, quick, and real-time manner. This study proposes an online data-driven concurrent product, process, and supply chain design (3DCE) for linking customer requirements to potential technology and supplier opportunities in early-stage new product development. Three case studies on the leading smartphone industry demonstrate the proposed method's feasibility and effectiveness. To identify customer requirements, opinions from social media data are collected. Product opportunities are developed using latent Dirichlet allocation to identify product topics and sentiment analysis to assess satisfaction levels. Then, a novel approach by association rule mining is developed to mine specific customer requirements for each promising topic. In the 3DCE approach, the potential technology and supplier opportunities are tailored to specific customer requirements based on intellectual property mining. Finally, this study discovers improvement ideas and potential alternative solutions for product development with an unsupervised approach. The proposed method has also been validated and aligns with successful innovation products by Apple, Samsung, and Huawei.