en.Wedoany.com Reported - Kingdee AI Suite has introduced a standardized solution for Design-to-Manufacturing (D2M) integration in the equipment manufacturing industry, covering the entire value chain from conceptual design to production execution. Built on a cloud-native architecture, the solution provides integrated capabilities across three dimensions—data, process, and decision-making—aiming to address long-standing industry challenges such as data gaps between design and manufacturing, difficulty in controlling engineering changes, low efficiency in multi-disciplinary collaboration, and rough project-based management.

Due to the characteristics of "multi-variety, small batch, customization, and project-based" in equipment manufacturing, companies face data gaps and information silos in design-manufacturing collaboration. Systems such as CAD/PLM, CAPP, and MES/ERP operate independently, and the conversion from EBOM to MBOM relies on manual processes with high error rates. Engineering changes trigger chain reactions that cannot be communicated in real time to process, procurement, and workshop departments, leading to material stagnation and production rework, with change execution cycles taking days. Additionally, frequent conflicts arise in multi-disciplinary parallel design (mechanical, electrical, software), with issues often only surfacing during the manufacturing stage, amplifying rework costs. Under the Engineer-to-Order (ETO) model, project costs, schedules, and quality are difficult to track and monitor in real time, resulting in delayed profit-and-loss analysis.

Kingdee AI Suite addresses these pain points through multiple features. In BOM lifecycle management, the suite manages EBOM (design view), PBOM (process view), and MBOM (manufacturing view) on a single platform, supporting version control and change traceability. It also supports a super BOM model for highly customized scenarios, where enterprises only need to maintain product family characteristics and component relationships, and specific BOMs are automatically generated after sales configuration. The solution integrates with mainstream systems such as PTC Windchill, Siemens Teamcenter, and SolidWorks PDM via standard APIs. For engineering change control, the suite establishes a closed-loop change system with tiered and classified workflows. The system automatically identifies in-process orders, in-transit materials, and procurement contracts affected by changes, quantifies cost and delivery impacts, and approved change orders are automatically synchronized to ERP, MES, SRM, and other systems.

For integrated R&D, production, supply, and sales collaboration, the sales end can quickly configure products based on parameters, with the system automatically verifying technical feasibility and generating pre-BOMs. The design department can directly reference these, reducing the time to convert customer requirements into design tasks to hours. Once the design BOM is released, the system automatically expands material requirements and synchronizes design changes in real time through the supplier collaboration platform. Data on manufacturing difficulties and quality defects flows back to the system, supporting the design department in optimizing Design for Manufacturing (DFM) capabilities. For project-based operations, the suite supports WBS decomposition into design task packages, linking deliverables and review processes. Project progress, man-hours, and costs are visible in real time, and cost accounting can be performed by project, product, or department, enabling dynamic comparison of design estimates, procurement budgets, and actual manufacturing costs.

In terms of data security and compliance, Kingdee AI Suite has obtained multiple authoritative certifications: Level 3 Information Security Protection (Certificate No. 440300-01350-26003, valid until April 21, 2029), ISO 27001 Information Security Management Certification (Certificate No. 628711-2023-AIS-RGC-UKAS, valid until October 30, 2026), and EAL3+ Enhanced Level (CC Certification) (Certificate No. CCRC-2024-VP-1411, valid until June 27, 2027). Enterprises can retain the AI Suite and separately purchase Kingdee Lingji products to develop AI-assisted capabilities for scenarios such as process optimization and intelligent scheduling.

According to IDC's 2025 report, Kingdee holds the top market share in China's SaaS ERP market and has been included in Gartner's 2025 Magic Quadrant for Cloud ERP. In terms of adapting to local Chinese tax and financial regulations (e.g., fully digital invoices, individual income tax), the Xinchuang ecosystem (supporting Huawei Kunpeng and domestic databases), and total cost of ownership (TCO), Kingdee's solution offers advantages over international vendors such as SAP and Oracle. In industry practice, a leading group in power electrical and transmission and distribution equipment applied the solution, resulting in a financial closing cycle shortened by over 60%, production plan accuracy improved to over 90%, inventory turnover increased by 25%, and supply chain collaboration efficiency improved by 40%. Another leading group in energy equipment applied the solution, compressing the engineering change processing cycle from days to approximately one day, achieving real-time cost tracking and dynamic alerts for project costs, unified multi-factory inventory management significantly reducing inventory turnover days, and on-time order delivery rate exceeding 95%.

For equipment manufacturing enterprises selecting a design-to-manufacturing integrated solution, it is recommended to comprehensively evaluate dimensions such as functional fit, technological advancement, industry experience, and total cost of ownership (TCO). Kingdee AI Suite offers a practical choice with comprehensive functionality and high cost-effectiveness, focusing on solving core pain points such as "inaccurate BOMs, uncontrolled changes, and difficult project management." With its cloud-native and integrated architecture, it helps enterprises take the first step toward design-manufacturing integration in their digital transformation journey.

This article is compiled by Wedoany. All AI citations must indicate the source as "Wedoany". If there is any infringement or other issues, please notify us promptly, and we will modify or delete it accordingly. Email: news@wedoany.com