On the basis of actual situations of Guangdong Province, using Factor Analysis Approach and Quantitative Analysis Method, we built index system by four factors, namely, extent of farmland connectivity, local financial...On the basis of actual situations of Guangdong Province, using Factor Analysis Approach and Quantitative Analysis Method, we built index system by four factors, namely, extent of farmland connectivity, local financial support, grain production capacity and farmland consolidation potential. Finally, we obtained that the areas with total scores of evaluation higher than 50 points are key construction areas of high-standard capital farmland in Guangdong Province. In total, there are 40 key construction areas, including 16 in plain areas of the Pearl River Delta, 9 in coastal regions of east of Guangdong, 10 in coastal regions of west of Guangdong, and 5 in northwest mountainous regions of Guangdong. Besides, we put forward construction direction of these 4 capital farmland areas.展开更多
Digital twins have emerged as a promising technology for maintenance applications,enabling organizations to simulate and monitor physical assets to improve their performance.In Operation and Maintenance(O&M),digit...Digital twins have emerged as a promising technology for maintenance applications,enabling organizations to simulate and monitor physical assets to improve their performance.In Operation and Maintenance(O&M),digital twin facilitates the diagnosis and prognosis of critical assets,forming the basis for smart maintenance planning and reducing downtime.However,there is a lack of standardized approaches for the qualifications of digital twins in maintenance,leading to low trustworthiness and limiting its application.This paper proposes a novel framework for the qualifications of digital twins in maintenance based on five pillars,namely fidelity,smartness,timeliness,integration,and standard compliance.We demonstrate the effectiveness of the framework through two case studies,showing how it can be implemented on digital twins for preventive maintenance and condition-based maintenance.Our proposed framework can help organizations across different industrial domains develop and implement digital twins in maintenance more effectively and efficiently,leading to significant benefits in terms of cost reduction,performance improvement,and sustainability.展开更多
基金Supported by the Project of Monitoring System for Farmland Quality Grade of Guangdong Province (2011B020313020)
文摘On the basis of actual situations of Guangdong Province, using Factor Analysis Approach and Quantitative Analysis Method, we built index system by four factors, namely, extent of farmland connectivity, local financial support, grain production capacity and farmland consolidation potential. Finally, we obtained that the areas with total scores of evaluation higher than 50 points are key construction areas of high-standard capital farmland in Guangdong Province. In total, there are 40 key construction areas, including 16 in plain areas of the Pearl River Delta, 9 in coastal regions of east of Guangdong, 10 in coastal regions of west of Guangdong, and 5 in northwest mountainous regions of Guangdong. Besides, we put forward construction direction of these 4 capital farmland areas.
文摘Digital twins have emerged as a promising technology for maintenance applications,enabling organizations to simulate and monitor physical assets to improve their performance.In Operation and Maintenance(O&M),digital twin facilitates the diagnosis and prognosis of critical assets,forming the basis for smart maintenance planning and reducing downtime.However,there is a lack of standardized approaches for the qualifications of digital twins in maintenance,leading to low trustworthiness and limiting its application.This paper proposes a novel framework for the qualifications of digital twins in maintenance based on five pillars,namely fidelity,smartness,timeliness,integration,and standard compliance.We demonstrate the effectiveness of the framework through two case studies,showing how it can be implemented on digital twins for preventive maintenance and condition-based maintenance.Our proposed framework can help organizations across different industrial domains develop and implement digital twins in maintenance more effectively and efficiently,leading to significant benefits in terms of cost reduction,performance improvement,and sustainability.
