Keqin Dou

As complex system engineering involving multiple stakeholders, multi-objective collaboration, and multi-spatiotemporal scales, the components, logical structure, and functional mechanisms of production equipment operation management and control (PEOMC) can be generalized through functional modelling to support dynamic analysis and intelligent decision-making of PEOMC in the industrial internet environment. To address the diversity of scenarios and objectives of PEOMC, a hierarchical construction method for the functional model of PEOMC based on IDEF0 is proposed. By analysing relevant international standards, such as ISO 55010, ISO/IEC 62264, and OSA-CBM, the generic functional modules for the first and second layers of the functional model are identified and defined. On the basis of semi-supervised machine learning, topic clustering is used to extract the components, functional mechanisms, and logical relationships of production equipment operation management and control from approximately 200 standard texts and to construct a reference resource pool for the third-layer functional module. On this basis, an interface matching and recursive traversal algorithm for functional modules is designed, and a composition and orchestration strategy of functional modules for specific scenarios is provided to support the flexible construction of diversified and personalized PEOMC scenarios. The proposed construction and application method was validated through an engineering case study in an aero-engine transmission unit manufacturing workshop: the average process capability index of the enterprise’s production equipment steadily increased from 1.28 to approximately 1.60, the mean time to repair (MTTR) of production equipment failures significantly decreased from 8 h to 3 h, and the average overall equipment effectiveness (OEE) increased from 56.43% to a stable 68.57%, demonstrating its effectiveness and practicality.

In the industrial internet environment, the operation and control of production equipment have become increasingly complex, and their performance directly affects the efficiency, benefits and sustainable development of manufacturing enterprises. From the three-dimensional perspective of “asset-application-maintenance”, this paper constructs a performance analysis framework for the operation and control of production equipment, systematically identifies the combination of core factors affecting performance, and fills the research gap in the current lack of empirical analysis from the configuration perspective in this field. On the basis of data from 82 manufacturing enterprises, the fsQCA method was used to identify three performance improvement paths: the high-load output mode, the lean management and control mode, and the low-failure operation mode. These paths clarify the equivalent approaches to achieve high performance in the operation and control of production equipment under the interaction of multiple factors. On this basis, the study demonstrates the operability and effectiveness of the proposed strategies in actual industrial scenarios through empirical verification in a manufacturing workshop of aero-engine transmission units. In contrast to existing studies, this study introduces the fsQCA method in the field of industrial equipment management and control for the first time to reveal the influencing paths; its originality and methodology have significant innovative significance. The research results provide new ideas and methodological guidance for enterprise managers to improve the performance of production equipment operations and controls in the industrial internet environment, which helps to enhance the sustainable development capability of manufacturing enterprises.

Presently, for the purpose of sustainable growth of the economy, it is a common choice to promote sectors’ digital transformation (DT). However, to credibly monitor the effect of DT on sectoral development, it is necessary to develop a systematic measure for the monitoring sector’s DT. This study provides a monitoring index system for sectors’ DT. First, an assessment framework for enterprises’ DT is introduced, which laid a foundation for the proposed monitoring index system for sectors’ DT. Secondly, a monitoring index system for sectors’ DT is established, which includes 13 monitoring indexes from four aspects, namely transformation stages, single-domain digitalization, integration and interconnection, and collaboration, interaction and mode innovation. A weighted method of interval hesitant fuzzy entropy is also given here. Finally, a panorama of sectors’ DT in China is derived by applying the proposed monitoring index system, and a prediction that the level of sectors’ DT in China will continue to grow in the next three years is made by gray predication.

With the continuous innovation of new-generation information technology and its accelerated integration with manufacturing industry, industrial internet platforms (IIPs) are rapidly emerging worldwide. IIP construction and promotion has become a new competition focus of global leading enterprises, and a new direction of industrial development in various countries. However, the development of IIP is still in exploration, and the industry still lacks unified understanding of the composition, functions and their interrelationships of IIP. As a result, the IIPs construction presents a disorderly development trend, and is faced with problems and challenges of unclearness of development path, indeterminacy of technical system, and unsoundness of business model. So, this paper firstly constructs a reference architecture of IIP to clarify its hierarchical framework and core functions, so as to provide a general reference model for the industry to understand and jointly promote IIP construction. Secondly, an evaluation system is proposed to guide the healthy development of IIP. The evaluation framework is composed from three dimensions namely the foundation guarantee, key capability, value and benefit, and the specific evaluation index system is also given. Finally, the application process and method of IIP evaluation are described with a practical case.