Identification of technology life cycles(TLC) provides a crucial basis for managing national policy, regional planning, and enterprise investment. Thus, it is a significant challenge to determine the stages of TLC. To this end, an entropy-based indicator is proposed, as well as a quantitative method based on the S-curve of entropy is established to identify the stages of TLC. Furthermore, the effectiveness of the method is verified by the analogy of three typical cases (thin-film-transistor liquid-crystal displays, cathode ray tubes, and nano-biosensors). It is clear that the entropy calculation produces a sum of overall distributions for patent applications against the researchers in the field to be studied, which can be used to find out the stage changes of TLC, while the other analysis considers trends of many patent active measures such as patent applications and citations collectively, to figure out the changes. Thus, the former constructs an index that has clear meanings and then uses its characterization to identify the changes logically, while the latter can only try to identify them empirically often with no trivial difficulties as these trends are often inconsistent. Finally, three-dimensional (3D) printing is investigated as an empirical case study, which reveals that 3D printing is still in its growth stage.

技术生命周期（TLC）的确定为管理国家政策，区域计划和企业投资提供了至关重要的基础。因此，确定TLC的阶段是一项重大挑战。为此，提出了一种基于熵的指标，并建立了基于熵S曲线的定量方法来识别TLC的阶段。此外，通过三种典型情况（薄膜晶体管液晶显示器，阴极射线管和纳米生物传感器）的类比，验证了该方法的有效性。显然，熵的计算得出了针对待研究领域的研究人员的专利申请的总体分布之和，可用于找出TLC的阶段变化，另一种分析则综合考虑了许多专利有效措施（例如专利申请和引用）的趋势，以找出变化。因此，前者构建具有明确含义的索引，然后使用其特征来从逻辑上识别变化，而后者只能尝试根据经验识别它们，而没有琐碎的困难，因为这些趋势通常不一致。最后，对三维（3D）打印进行了实证研究，表明3D打印仍处于发展阶段。而后者只能尝试凭经验来识别它们，而没有琐碎的困难，因为这些趋势通常是不一致的。最后，对三维（3D）打印进行了实证研究，表明3D打印仍处于发展阶段。而后者只能尝试凭经验来识别它们，而没有琐碎的困难，因为这些趋势通常是不一致的。最后，对三维（3D）打印进行了实证研究，表明3D打印仍处于发展阶段。