Predictive maintenance is one of the important technical means to guarantee and improve the normal industrial production. The existing bottlenecks for popularization and application are analyzed. In order to solve these problems, a cooperative awareness and interconnection framework across multiple organizations for total factors that affect prediction maintenance decision-making is discussed. Initially, the structure and operation mechanism of this framework are proposed. It is designed to support the sharing of data, knowledge and resources. As a key supporting technology, the digital twin is also integrated into it to improve the accuracy of fault diagnosis and prediction and support making a maintenance plan with higher accuracy and reliability. Then, under this framework, an integrated mathematical programming model is established with considering the parameter uncertainty and an NSGA-II hybrid algorithm is utilized to solve it. Moreover, an adjustment strategy for a maintenance plan is discussed in response to the dynamic characteristics of the actual maintenance environment. Finally, a case, prediction maintenance decision-making for bearings in grinding rolls of the large vertical mill, is studied. Analysis results verify the advantage of the integrated solving mechanism based on the proposed framework. The framework and integrated decision-making approach can guide the implementation of predictive maintenance with higher accuracy and reliability for industrial enterprises. 相似文献
Big data is one of the most important resources for the promotion of smart customisation. With access to data from multiple sources, manufacturers can provide on-demand and customised products. However, existing research of smart customisation has focused on data generated from the physical world, not virtual models. As physical data is constrained by what has already occurred, it is limited in the identification of new areas to improve customer satisfaction. A new technology called digital twin aims to achieve this integration of physical and virtual entities. Incorporation of digital twin into the paradigm of existing data-driven smart customisation will make the process more responsive, adaptable and predictive. This paper presents a new framework of data-driven smart customisation augmented by digital twin. The new framework aims to facilitate improved collaboration of all stakeholders in the customisation process. A case study of the elevator industry illustrates the efficacy of the proposed framework. 相似文献
The study aims at evaluation of the steady-state heat dissipation capability of a high-density through silicon via (TSV)-based three-dimensional (3D) IC packaging technology (briefly termed 3D TSV IC packaging) designed for CMOS image sensing under natural convection through finite element analysis (FEA) and thermal experiments. To enhance modeling and computational efficiency, an effective approach based on FEA incorporating a 3D unit-cell model is proposed for macroscopically and thermally simulating the heterogeneous TSV chips. The developed effective thermal conductivities are compared against those obtained from a rule-of-mixture technique. In addition, the proposed numerical models are validated by comparison with two experiments. Besides, the uncertainties in the input chip power from the specific power supply and in the measured chip junction temperature by the thermal test die are evaluated. Finally, a design guideline for improved thermal performance is provided through parametric thermal study. 相似文献
To investigate the degradation of the touchpad usability by surface wear, the touchpad with new, worn, plastics and paper surfaces are examined in terms of performance and frictional response. It is found that the friction coefficient of the surface affect the usability. It is concluded that the major factors controlling the friction was surface roughness. It is also found that friction coefficient is affected by the difficulty of the task. The reasons for this is the human tendency to be cautious, he/she try to reduce the load to be precise. Then the load dependence of friction coefficient results in high friction. The other reason is mental sweating, which will be increased when the task is difficult. 相似文献