Abstract: In the single-bucket–truck process system of open-pit coal mines, coordinated operations between trucks and electric shovels often experience phenomena such as "trucks waiting for shovels" or "shovels waiting for trucks", leading to decreased coordination efficiency of equipment at the working face. Current research on coordination evaluation mostly focuses on single time indicators (e.g., average waiting time) or qualitative descriptions, which struggle to comprehensively cover multidimensional demands such as cost loss, capacity utilization, operational steadiness, and supply–demand balance. Moreover, issues such as fuzzy indicator boundaries and insufficient data support make it difficult to provide precise quantitative foundations for scheduling optimization. To address the above problems, a comprehensive evaluation method for truck-shovel coordination efficiency in the single-bucket–truck process system at stripping faces was proposed. A comprehensive evaluation system comprising 16 core indicators was constructed from four main control factors: waiting cost, equipment utilization, system stability, and capacity matching degree. A structural equation model was defined to analyze the above four main controlling factors as global latent variables. The standardized paths of the evaluation system were established through model fitting, and reliability and validity analyses were further conducted to verify the practical effectiveness and reliability of the structural equation model. Using matter-element extension theory, the correlation degree calculation method for indicators was determined, deriving weight relationships between the evaluation problem and various primary and secondary controlling factors. Combined with the standardized paths from the structural equation model, the global comprehensive correlation degree of the entire evaluation system was calculated. Through case analysis, the coordination status and efficiency were quantitatively evaluated. Results showed that the comprehensive weights of the four primary controlling factors were 0.286, 0.258, 0.231, and 0.255, respectively, with capacity matching degree having the highest weight, indicating it as the key factor affecting truck-shovel coordination efficiency. By removing data items with excessively long waiting times from the dataset to construct a comparative experiment, the correlation degree indicators for system stability and waiting cost were significantly improved, changing from –0.088 66 and –0.056 83 to –0.006 34 and –0.077 48, respectively, and the evaluation grade increased from 1 to 3. The research results demonstrate that combining the structural equation model with matter-element extension theory can effectively address the multidimensional coupling and boundary fuzziness problems in coordination evaluation, providing reliable quantitative decision support for equipment capacity release and transportation scheduling optimization in open-pit coal mine stripping processes.