With the deep integration of intelligent manufacturing and digital transformation, manufacturing production is moving toward multi-variety, small-batch, and customized modes, increasing the proportion of indirect costs in total cost. Traditional cost accounting based on a single allocation standard can no longer meet refined cost-management requirements. To solve problems in Activity-Based Costing application, including difficult data collection, unclear activity-center division, low accounting efficiency, and weak real-time performance, this paper designs and implements an ABC intelligent accounting system for manufacturing enterprises. First, an overall system architecture is constructed based on manufacturing production characteristics and ABC accounting logic. Second, key modules including data collection, activity-center division, and cost allocation are designed, and artificial intelligence algorithms are introduced to optimize cost-driver identification and allocation efficiency. Finally, a large manufacturing enterprise is used for system testing. Results show that the system supports automated collection of multi-source cost data with collection delay below 5 minutes, reducing manual recording delay by 90%. Cost accounting time for a single production batch is reduced from 8 hours to 30 minutes, providing reliable support for refined manufacturing cost management.
Z. H. Cao (Thu,) studied this question.