Affiliation:
1. Molecular Electronics Research Institute; Moscow Institute of Physics and Technology
2. Molecular Electronics Research Institute
Abstract
Objectives. Over the past few decades, multiple knowledge management models have been developed by many research groups studying the innovation process in companies. However, these knowledge and information management models are rather general, and do not consider the dynamics and variability of technology development. This implies involving specific organizations in different types of knowledge generation activities. The paper aims to reveal the importance of a knowledge management system in micro- and nanoelectronics technologies as well as identify and systematize the sources of knowledge in the scientific and technical field.Methods. In this paper, the method for analyzing the relationship between key business indicators of the companies is applied. The results are then represented in a causal loop diagram. The stakeholder analysis method is also used here.Results. Three relevant trends in developing the knowledge management system for knowledge-intensive enterprises involved in micro- and nanoelectronics technologies are identified with respect to the social, commercial, and scientific and technical aspects in research organizations. The key sources of knowledge on micro- and nanoelectronics technologies include universities, institutions of the Russian Academy of Sciences, industry-specific institutions, customers, manufacturers, and consumers. Also, the authors consider digital twins to be a promising source of knowledge on micro- and nanoelectronics technologies.Conclusions. The analysis of the technology life cycle curve using the example of micro- and nanoelectronics allows correlating single stages of this life cycle with specific activities during which new knowledge is generated. These activities include fundamental and applied research, requirements management, implementation in manufacturing, and operation analysis. For microelectronics, they correspond to the areas of emergence, peak of inflated expectations, trough of disillusionment, slope of enlightenment, and plateau of productivity on the technology life cycle curve.