Abstract:

    In the digital economy, intelligent key technological innovation is an inevitable requirement for discrete manufacturing enterprises to transform to intelligence, and collaborative innovation is the main trend of intelligent manufacturing innovation. Discrete manufacturing is an assembly-type, order-oriented production method. And its production unit is scattered and independent, which makes the production "disorderly and inefficient". To meet the changing needs of customers and make up for the production disadvantages of traditional discrete manufacturing, discrete manufacturing enterprises need to change the decentralized, unit-level workshop distribution and the "design-manufacturing" integrated production methods. 

         Based on the characteristics of discrete manufacturing and the application of intelligent technology, this paper firstly proposes an intelligent development scheme of digital economy discrete manufacturing based on the application of intelligent technology. The scheme expounds the specific application of intelligent technology in discrete manufacturing from four aspects: demand design, production management, information management, and knowledge management, and clarifies the direction of discrete manufacturing to intelligent transformation. Then, this paper constructs an intelligent key technology collaborative innovation system of discrete manufacturing. The system aims at the intelligentization of discrete manufacturing and describes the collaborative innovation process with discrete manufacturing enterprises, governments, universities, and scientific research institutions as the main participants. We also analyse the connotation of collaborative innovation of intelligent key technologies from the perspective of the internal and external aspects of the enterprise, which provides a direction for the development of intelligent innovation of discrete manufacturing enterprises. At the same time, the system proposes that an intelligent knowledge innovation alliance should be formed around collaborative innovation subjects such as discrete manufacturing enterprises, governments, universities, and scientific research institutes, so as to transform technological innovation achievements into knowledge and form a virtuous innovation knowledge cycle. 

        Secondly, this paper takes 23 discrete intelligent manufacturing enterprises in China as the research object and constructs a system of influencing factors for collaborative innovation of intelligent key technologies. This paper uses the entropy weight method and Grey Relation Analysis method when studying the influencing factors: the entropy weight method determines objective weights according to the variability of indicators. This method can avoid subjectivity in weighting and increase the accuracy of research results; the Grey Relational Analysis method uses grey relational degrees to quantitatively describe the relative changes of various factors in the system, and then judge the main influencing factors of the system. We study the influence of these factors on collaborative innovation by analysing and comparing the grey relational degree of individuals, combinations and systems. 

       The results of the research show that: first, enterprise innovation capabilities, enterprise intelligence manufacturing potential, enterprise synergy power, regional innovation capabilities, and external environmental support can promote the collaborative innovation of intelligent key technologies; Second, enterprise synergy power is the factor that directly promotes enterprises to participate in collaborative innovation. Enterprise innovation capabilities, enterprise intelligence manufacturing potential, and regional innovation capabilities determine the ability of innovation participants to invest in innovation resources. The influence of external environmental support factors is relatively weak. Third, in the secondary indicators, the stock of enterprise knowledge and government subsidies are the main factors affecting the collaborative innovation of intelligent key technologies. 

        Finally, according to the empirical results, this paper puts forward targeted development suggestions: First, enterprises should build a database of intelligent manufacturing innovation knowledge to improve enterprise knowledge reserves and interaction capabilities; Second, the government should increase financial support and improve talent training and attraction policies; Third, enterprises should keep up with social trends, strengthen internal and external cooperation, and apply innovative achievements to practice.

Key words: discrete manufacturing, intelligent manufacturing, collaborative innovation of key technologies, influencing factor