Janne Juola, August 28, 2019
Typically, casting starts from the purest products and moves on toward progressively more alloyed products. The goal is to reduce non-productive clean-up or setup times and, therefore, increase productivity and yield.
In addition to grouping, an essential element in production order sequencing is choosing the correct batch size. What are the optimal sizes of the production batches; how many tons of one item are cast before starting to produce another item? By utilizing the lean philosophy, small quantities are produced in chronologic order to reduce the inventories. In contrast, to meet productivity targets, it is tempting to choose long production runs instead.
Both approaches have their challenges. Short production runs mean a lot of set-times and reduced productivity, whereas, long production runs cause long delivery lead times and excess capital tied to the inventory.
In practice, it’s best to establish business-driven rules for batch sizes and simulate and optimize this sequence by the changes in demand and supply. Procedures need to be well articulated to be sure they align with business targets. For example, business rules can be established and implemented for the solution by using the following guidelines:
The business environment is continually changing and with increasing frequency. Simulations and optimization can tell you how to react, or even better, allow you to be proactive concerning emerging changes. If business needs require, APS should be done several times per day; however, often, it is sufficient to revisit the APS only once a day.
Many companies still use frozen periods in their planning process because re-planning demands too much effort. This means that all the high-margin rush orders are automatically lost, even if the production itself had the generation capacity. This can be solved by expertise planning and by utilizing the correct APS. With optimal process synchronization and sequencing, as well as using APS, manufacturing lead time may be cut in half, and work-in-process inventory can be reduced to a minimum.