Understanding Planning Options in PP/DS

Essentially, PP/DS consists of two parts: PP and DS.

The PP (production planning) part deals primarily with products and the creation of orders.

The figure lists Production Planning features which include multilevel planning, usage of heuristic methods, lot quantity calculations, support of various manufacturing models, order pegging, and alert monitor integration. Production Planning is highlighted as the first step in a four step process, covering Detailed Scheduling, Manufacturing Execution, and Performance Monitoring as subsequent steps.

The DS part deals primarily with resources and the scheduling of orders.

The figure lists Detailed Scheduling features which include a scheduling optimizer, optimal sequencing, backlog resolution, what-if analysis, simulation, and alert monitoring. Detailed Scheduling is highlighted as the second step in a four step process, with Production Planning as a previous step, and Manufacturing Execution, and Performance Monitoring as subsequent steps.

The planning algorithms of PP/DS are applied to many industries.

The figure represents eight different industries with icons each: top row displays Consumer Products, Life Science, Chemicals, Mill; bottom row shows High Tech, Automotive, Machinery, A&D.

To understand the differences between the two core optimization engines available in PP/DS, it is very important to distinguish between bucket-oriented and time-continuous planning. These two approaches lead to a significant difference in what is used as an input to the optimization model and what to expect as an outcome.

A chart showing supply and forecast for Products A, B, and C over January, February, and March in the top section; dark blue represents supply; light blue represents forecast. The bottom section depicts resource views over the same months. In the bucket view, the supply orders are stacked (in each month/bucket), whereas in the time-continuous view they are sequenced after each other.

Bucket-oriented planning aggregates data based on buckets, for example days or weeks or even months. The planning is executed on that level of granularity and yields (production) quantities (per product and) per bucket as a result. This quantity per bucket must be translated to the order level. Depending on lot sizing rules, a bucket quantity may need to be split into several orders. From the resource perspective, the resource load is only known in aggregated form, since no finite scheduling has been done in bucket-oriented planning. In contrast, time-continuous planning works on order-level and includes finite scheduling on resources. In PP/DS, you can do both.