Different demands from EV, consumer, and energy storage markets for lithium batteries, with rapid demand changes
Different focuses during peak and off-peak seasons - maximizing capacity utilization during peak seasons,提前planning storage in off-seasons to reduce peak pressure, or集中shutting down idle equipment
Diverse models with frequent switching causing losses, with爬坡after changeover potentially lasting a month
Critical materials fluctuate due to price and other reasons, shortages affect production. Need to consider single substitute materials, combined substitute materials, multi-supplier quotas, material requirements under ECN engineering changes, procurement plans, and kit analysis management. Information asymmetry between material plans and production plans leads to complex material management
Cells belong to MTS production mode, Packs belong to MTO production mode. Multiple departments including inventory, production, and transportation generate internal反复confirmations and inefficient communication. This leads to difficulty balancing inventory costs, production costs, and transportation costs
Based on data analysis and AI technologies, a production-sales-inventory联动execution system where when any one of the three changes, the other two make corresponding adjustments to adapt to the execution plan, effectively improving management efficiency
With a complete service system and role division,具备end-to-end solution delivery capability for industry customers, with 100% successful delivery cases guaranteed to date
Combining production costs, transportation costs, and inventory costs with production capacity supply-demand situations to jointly model, obtaining low-cost and high-benefit plans. Economic benefits and management benefits are实时visible
Key data such as demand delivery, material supply, inventory turnover, and production progress at a glance
Based on the powerful operations research engine of our self-developed Deloris algorithm platform, automatically generating: production plans, changeover plans, material requirements plans, transportation plans, inventory plans, and demand delivery plans. For example: automatically calculating when what production line produces what, when the production line进行changeover爬坡, how long the爬坡time is? This optimizes changeover爬坡time to achieve overall supply chain效益maximization
By building an intelligent planning system,实现master/daily plan overall optimization, further保障delivery,提升capacity utilization,减少inventory losses and降低other production costs.
Through overall optimization in multiple aspects including spare parts demand forecasting, spare parts inventory replenishment planning, and spare parts production coordination,打造an intelligent spare parts supply chain management system.
