成熟度评估工具在创新过程中的应用:将系统的涌现属性转化为技术知识

Julio Cesar Lemos , Milton Freitas Chagas Junior
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引用次数: 11

摘要

本文旨在建立利用学习概念与技术准备水平(TRL)和系统准备水平(SRL)概念之间的理论建构。通过使用来学习的概念揭示了在复杂系统中发生的技术变化是由许多不同技术学科的小改进的总和集成在这个系统的特定配置中。这种学习源于科技知识的迭代组合,而科技知识是通过产品及其相关生产过程的广泛使用而产生的。在处理复杂系统的紧急特性时,可能需要这种组合知识的储备。复杂系统的演化模式涉及到技术和科学前沿的平衡以及客户期望的实现。每一项创新都涉及系统不确定性,这与引入复杂系统的变化幅度呈正相关。技术解决方案的成熟度水平允许组织实际地评估实施复杂系统创新的战略风险暴露。SRL的概念代表了一个揭示涌现属性的复杂工具,它既考虑了单个元素的TRL,也考虑了它们如何集成到一个复杂的系统中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of maturity assessment tools in the innovation process: converting system's emergent properties into technological knowledge

This paper aims at establishing a theoretical construction between the concept of learning-by-using and the concepts of Technological Readiness Level (TRL) and System Readiness Level (SRL). The concept of learning-by-using reveals that the technical change that takes place in complex systems is given by the sum of small improvements in many different technological disciplines integrated in a specific configuration of this system. This kind of learning results from the iterative combination of scientific and technological knowledge, which is generated by the extensive use of products and their associated production processes. A stock of this combined knowledge might be required to cope with emergent properties of complex systems. The pattern of complex systems evolution involves the balance of technological and scientific frontiers as well as the fulfillment of customer expectation. Every innovation involves systemic uncertainty, which is positively correlated to the magnitude of the change introduced into the complex system. Maturity level of technological solutions allows organizations to assess pragmatically strategic risk exposure of implementing complex system innovation. The concept of SRL represents a proficuous tool to unveil emergent properties, which consider both the TRL of individual elements and how they are integrated into a complex system.

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