cprpd domains

LN never updates the involved plan or forecast, which means that you can only maintain it manually (in the Item Master Plan (cprmp2101m000) session).

Depending on the involved plan or forecast, this value means that:

• LN computes the production plan or purchase plan for this item when you run the Generate Master Planning (cprmp1202m000) session or the Generate Master Planning (Item) (cprmp1203m000) session.
• LN computes the inventory plan or demand forecast for this item when you run the Generate Demand and Inventory Plan (cpdsp1210m000) session.

(Aggregation and disaggregation is disabled for the plan or forecast involved.)

LN aggregates or disaggregates data from a lower or higher aggregation level to the plan or forecast of the current item when you run one of the following sessions:

• Aggregate Channel, Plans & Orders (cprmp2250m000)
• Disaggregate Channel, Plans & Orders (cprmp2260m000)
• Aggregate Channel to Item Master Plan (cpdsp5210m000)

Depending on the involved plan or forecast, this value means that:

• LN computes the production plan or purchase plan for this item when you run the Generate Master Planning (cprmp1202m000) session or the Generate Master Planning (Item) (cprmp1203m000) session.
• LN computes the inventory plan or demand forecast for this item when you run the Generate Demand and Inventory Plan (cpdsp1210m000) session.

Moreover, LN aggregates or disaggregates data from a lower or higher aggregation level to the plan or forecast of the current item when you run one of the following sessions:

• Aggregate Channel, Plans & Orders (cprmp2250m000)
• Disaggregate Channel, Plans & Orders (cprmp2260m000)
• Aggregate Channel to Item Master Plan (cpdsp5210m000)

The forecast demand is distributed across the number of days in the specified period according, to the daily availability in the calendar of the plan item's warehouse.

The forecast demand is planned on the last day of the period.

LN determines the average demand for a number of past periods. The periods that LN takes into account are the current period plus a definable number of previous periods. Each time that LN calculates the moving average, the most recent period is added, and the oldest period is dropped.

LN applies a weighted average for past demand figures. The heaviest weight is assigned to the most recent demand figures.

LN applies the polynomial regression analysis technique. In this technique, an n'th degree polynom is determined that matches the historical demand pattern. This method is suitable to forecast only a few periods into the future.

LN applies the linear regression analysis technique. In this technique, a first degree polynom is determined (unless the trend is progressive).

No demand forecast will be calculated for this plan item.

LN first uses the suppliers or supplying relationships with the highest priority. You can define the priority in the Item - Purchase Business Partner (tdipu0110m000) session and in the Supplying Relationships (cprpd7130m000) session.

LN first uses the suppliers or supplying relationships with the lowest cost. This cost includes material cost, production cost, and supply cost.

This option is only available if the supply type is Distribution.

LN first uses the suppliers with the shortest supply time. LN first uses the supplying relationships with the shortest supply lead time.

You can define the supply time in the Item - Purchase Business Partner (tdipu0110m000) session and you can define the supply lead time in the Supplying Relationships (cprpd7130m000) session.

LN first uses the suppliers with the lowest transportation WIP. The transportation WIP (work in process) is the supply time multiplied by the item cost.

This option is only available if the supply type is Distribution.

The phase numbers for order planning are recomputed. These phase numbers are based on:

• Bills of material (BOMs)
• Supplying relationships

The phase numbers for master planning are recomputed. These phase numbers are based on:

• Bills of critical materials (BCMs)
• Supplying relationships

The recomputation of phase numbers for master planning also takes plan units into account.

Chose to print Items - Planning (General) report.

Chose to print Items - Planning (Details) report.

Chose to print Items - Planning (Summary) report.

Chose to print Items - Planning (COLT) report.

The plan item is a product family. Goods-flow data for families is aggregated through the aggregation relationships.

Goods flow data of a plan item of plan item type Item is retrieved from the execution level.

( infinite planning)

( workload control)

The scenario can still be modified.

The scenario can no longer be modified.

A plan item is recomputed only if the phase number of the plan item's parent has changed since the last computation.

LN recomputes the phase numbers of all plan items in the selection range.

The number of days in a period (specify a number).

The number of weeks in a period (specify a number).

The number of months in a period (specify a number).

The number of years in a period (specify a number).

The whole effectivity period of this sourcing strategy.

The order interval of the plan item involved.

The plan item is supplied by means of production or purchase orders, unless a specific sourcing strategy is defined.

The plan item is supplied by means of distribution orders, unless a specific sourcing strategy is defined.

In the case of a constant seasonal influence, an absolute seasonal component recurs after every seasonal cycle.

Example

A product is very popular among consumers towards the end of the year. The seasonal pattern is defined by the following factors:

LN uses these factors as follows:

• If the average demand is 800, a demand of 1000 is forecast for December.
• If the average demand is 900, the forecast for December will be 1100.

In the case of a progressive seasonal influence, a relative seasonal component recurs after every seasonal cycle.

Example

A seasonal pattern is defined by the following factors:

LN uses these factors as follows:

• If the average demand is 800, a demand of 1000 is forecast for December.
• If the average demand is 900, the forecast for December will be 1125.

There is no seasonal influence.

The trend influence is linear. If the Forecast Method field is Exponential Smoothing, LN also uses the Additive term in the forecast calculation. The trend can be characterized by the following formula:

FD(t+1) = FD(t) + TF

Where:

Example

Each month the demand is 20 units higher than the preceding month.

The trend influence is progressive: there is a relative and progressive trend component. If the Forecast Method field is Exponential Smoothing, LN also uses the Multiplicative term in the forecast calculation. The trend can be characterized by the following formula:

FD(t+1) = FD(t) x TF 

Where:

Example

Each month the demand is 1.2% higher than the preceding month.

There is no trend influence.

• Update the COLT values (that is, the COLT and the noncritical COLT).
• Create a report on the order horizons and planning horizons that are too small, but do not actually update these horizons.

• Update the COLT values (that is, the COLT and the noncritical COLT).
• Update the order horizons and planning horizons that are too small.

• Update the COLT values (that is, the COLT and the noncritical COLT).
• Update all order horizons and planning horizons, resetting them to their minimal levels.