Iron Casting Foundry

Process Synchronization through Optimal, Sequential Scheduling

An iron casting foundry faces many planning challenges, including the production of metal with different ratios of alloy material and different furnace settings and process flows. A schedule must be stringent, consider furnace availability, availability of sub-resources such as molds and ladles, as well as byproducts and lot sizes. Melting and holding processes consume large amounts of energy, and optimizing transfer times with precision is vital for a leaner, most cost-efficient plant. The prime objective is to have maximum output with the shortest possible lead time.

  • Fully comprehensive process synchronization
  • Minimized lead times and inventory stocks
  • Flawless delivery reliability
  • Reduced time and effort spent on planning

Challenges

Different configurations of the same material require different processes, for example hot and cold rolled steel. A foundry that has many different such end products must consider all the different combinations of processes. Asprova can dynamically generate the optimal schedule, knowing the constraints and production requirements of each resource and item.

When there is a looming deadline for many orders of vastly different products, it is necessary to find the optimal grouping of orders to minimize changeover times, while also still making sure that due dates are kept.

Transfer times and secondary processes are part of the planning challenge. Work-in-process material can have strict time constraints between processes. Conflicts between orders, especially at bottlenecks in the plant, need to be considered when scheduling.

With Asprova APS

  • Comprehensive process synchronization through optimal, sequential scheduling
  • Drastically shortened production lead times through bottleneck-oriented planning
  • Massive reduction in intermediate parts
  • Produce a more optimized schedule considering all restrictions
  • Shorter delivery time
  • Increased resource efficiency
  • Improved transparency in factory and order status
  • Greater flexibility in case of order changes, rush orders, machine downtime, etc.
  • Substantial reduction of planning efforts