Product Development-Oriented Knowledge Service: Status Review, Framework, and Solutions

Abstract

The product development knowledge stored in manufacturing firms can be obtained and re-used to assist the development engineers in new product development and facilitate the use of knowledge resources, which in turn enhances the quality and reduces the time-cost of product innovation. This study presents a knowledge service integrated framework for product development, which is refined from the literature and supported by practice needs. The proposed integrated framework is supported by four pillars of work, namely, how to represent knowledge exactly, the model of knowledge integration, the method of knowledge recommendation, and the mechanism and performance evaluation of knowledge service. A demonstration of a gantry crane design is provided to show the effectiveness and benefit of the proposed integrated framework and technology solutions. Finally, we offer some pointers for future research.

Automatic knowledge graph creation from engineering standards using the example of formulas

“…Product development is subject to constant change due to increasing product complexity, additional requirements towards sustainability, and increasing individualisation of products (Dumitrescu et al, 2021;Isaksson and Eckert, 2020). For a company to improve quality, reliability and performance of its products while reducing development costs and time, the handling of knowledge is becoming increasingly important (Hicks et al, 2002;Zhenyong et al, 2020). Knowledge workers currently spend 16% of their time searching, understanding, and processing information from various sources, yet 44% of searches fail to find relevant information (Schubmehl and Vesset, 2014).…”

Representation and Application of Digital Standards Using Knowledge Graphs

“…Since product development is also characterized as knowledge-intensive activity, the integration of digital knowledge management is of particular interest. (Zhenyong et al, 2020) Standards are an essential source of knowledge and enable companies to, among others, meet regulatory requirements and decrease development costs (Ziegenfuss, 2020). Furthermore, they support the decision making process of many engineering activities along the product development process (Manoharan and Koehler, 2018).…”