Purpose

Smart manufacturing can lead to disruptive changes in production technologies and business models in the manufacturing industry. This paper aims to identify technological topics in smart manufacturing by using patent data, investigating technological trends and exploring potential opportunities.

Design/methodology/approach

The latent Dirichlet allocation (LDA) topic modeling technique was used to extract latent technological topics, and the generalized linear mixed model (GLMM) was used to analyze the relative emergence levels of the topics. Topic value and topic competitive analyses were developed to evaluate each topic's potential value and identify technological positions of competing firms, respectively.

Findings

A total of 14 topics were extracted from the collected patent data and several fast growth and high-value topics were identified, such as smart connection, cyber-physical systems (CPSs), manufacturing data analytics and powder bed fusion additive manufacturing. Several leading firms apply broad R&D emphasis across a variety of technological topics, while others focus on a few technological topics.

Practical implications

The developed methodology can help firms identify important technological topics in smart manufacturing for making their R&D investment decisions. Firms can select appropriate technology strategies depending on the topic's emergence position in the topic strategy matrix.

Originality/value

Previous research studies have not analyzed the maturity levels of technological topics. The topic-based patent analytics approach can complement previous studies. In addition, this study provides a multi-valuation framework for exploring technological opportunities, thus providing valuable information that supports a more robust understanding of the technology landscape of smart manufacturing.

中文翻译：

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基于主题的专利分析方法，用于探索智能制造中的技术趋势

目的

智能制造可能会导致制造业生产技术和商业模式的颠覆性变化。本文旨在通过使用专利数据，研究技术趋势并探索潜在机会来确定智能制造中的技术主题。

设计/方法/方法

潜在的狄利克雷分配（LDA）主题建模技术用于提取潜在的技术主题，而广义线性混合模型（GLMM）则用于分析主题的相对出现水平。进行了主题价值和主题竞争分析，以评估每个主题的潜在价值并分别确定竞争公司的技术地位。

发现

从收集的专利数据中总共提取了14个主题，并确定了几个快速增长和高价值的主题，例如智能连接，网络物理系统（CPS），制造数据分析和粉末床融合增材制造。几家领先的公司将研发重点放在各种技术主题上，而其他公司则专注于少数技术主题。

实际影响

先进的方法可以帮助企业确定智能制造中的重要技术主题，以制定研发投资决策。企业可以根据主题在主题策略矩阵中的出现位置来选择适当的技术策略。

创意/价值

以前的研究尚未分析技术主题的成熟度。基于主题的专利分析方法可以补充以前的研究。此外，本研究为探索技术机会提供了一个多价值框架，从而提供了有价值的信息，这些信息有助于对智能制造的技术格局有更深入的了解。