Scheduling Plastic Injection Molding

Increased Resource Productivity

A plastic injection molding factory faces many challenges in scheduling. Even if the production process itself is straight-through, the many resources, including shared machines using different dies and molds, and other resources such as driers and grinders, each with their own constraints, makes scheduling a huge undertaking.

Orders need to be grouped because of lengthy changeover times. Lot sizes are in the thousands. An important factor is maintaining inventory stock while keeping waste to a minimum. The unavailability of one resource for a short time can delay the entire manufacturing process and increase costs.

Asprova plans all resources (injection molding machines, molds, machine operators, changeover teams) considering finite capacity. Also, orders can only be scheduled if all required resources are available.

  • Fully comprehensive process synchronization
  • Minimized lead times and inventory
  • Flawless delivery reliability

Challenges

In a plastic injection molding plant, sizing lots optimally is necessary to minimize time spent on setups, however manually setting each lot is a complicated task—too many small lots increases changeover time, while too large lots can buildup inventory and cause delays. Asprova considers all constraints, including changeover times and on-time delivery rates, to create the optimal schedule.

Limitations of workers and tool availability can make it hard to schedule "just-in-time." Sometimes when a process is started, it is wasteful or impossible to interrupt it because of changing priorities or sudden demand.

Keeping track of inventory levels and managing safety stock is also a challenge, when there is a large backlog, orders move in quickly, or you have a large product line to manage.

With Asprova APS

  • Shorter delivery times
  • Comprehensive process synchronization through optimal, sequential scheduling
  • Drastically shortened lead times through bottleneck-oriented planning
  • Massive reduction in intermediate parts
  • Increased resource efficiency
  • Improved transparency in factory and order status
  • Greater flexibility in case of order changes, rush orders, machine failure, etc.
  • Drastic reduction in planning efforts