数字化排产是把生产订单、工序路线、物料齐套、设备产能与交付要求与数字技术结合、通过算法自动编排生产计划的排产方式，核心是约束条件下的计划自动优化与多车间协同，能力包括有限产能排程、齐套校验、插单模拟与异常重排。它解决的是人工经验排产冲突多、插单一来全盘重排的问题，并不解决设备物理产能不足与工艺路线固有的问题。
数字化排产的核心是约束建模和计划优化，它可以帮助企业实现以下目标：
实现有限产能下的自动排程。排产算法把设备可用时间、模具与人员限制作为硬约束输入，生成的计划从一开始就满足产能边界，而不是排完再靠人工纠偏。
在排产前完成齐套校验。系统按工序反查物料库存与在途量，缺料的生产任务会被前置标记，避免计划下发到车间后因缺料停线。
支持插单与变更的快速模拟。新的紧急订单进入系统后，可以先在不修改正式计划的前提下试算多条排产方案，对比交付时间和资源占用后再决定是否切换。
实现生产异常的自动重排。设备故障、工单报废或延误被录入系统后，受影响的后续工序被识别并自动给出重排建议，把人工调整的幅度控制在最小范围。
总之，数字化排产可以帮助企业实现从经验排产到算法排产的转变，提高设备利用率与订单交付准时率，减少在制品积压与换线损失。
翻译
Digital production scheduling is the combination of production orders, routing, material readiness, equipment capacity and delivery requirements with digital technology to automatically arrange the production plan through algorithms. Its core is automatic plan optimization under constraints and cross-workshop collaboration, with capabilities covering finite-capacity scheduling, material readiness validation, order insertion simulation and automatic rescheduling after exceptions. It solves the problems of conflict-prone manual experience-based scheduling and full replanning triggered by a single rush order, but it does not solve physical equipment capacity limits or fixed process routings.
At the heart of digital production scheduling is constraint modeling and plan optimization, which can help companies achieve the following:
Automate scheduling under finite capacity. The scheduling algorithm takes equipment availability, tooling and manpower limits as hard constraints, and the generated plan satisfies capacity boundaries from the outset rather than being corrected manually afterwards.
Complete material readiness validation before scheduling. The system looks up material stock and in-transit quantities backwards along the routing, and production tasks with missing materials are flagged in advance, preventing line stoppages caused by shortages after plans are released to the shop floor.
Support fast simulation of rush orders and changes. When a new urgent order enters the system, multiple scheduling alternatives can be calculated without modifying the official plan, allowing delivery time and resource occupation to be compared before deciding whether to switch.
Enable automatic rescheduling after production exceptions. Equipment failures, work order scrapping and delays are recorded in the system, affected downstream operations are identified, and rescheduling suggestions are generated automatically, keeping manual adjustment to a minimum.
In short, digital production scheduling can help enterprises shift from experience-based scheduling to algorithm-based scheduling, improve equipment utilization and on-time delivery rate, reduce work-in-process accumulation and changeover losses.
