========= Parameter ========= Global settings and parameters are stored here. Some of these parameters are used by the planning algorithm, others are used by the web application. Extension modules also add additional configuration parameters to this table. **Standard parameters** The table below shows the parameters that are recognized by the standard application. ==================================== ======================================================================= Parameter Description ==================================== ======================================================================= currentdate | Current date of the plan, preferred format is YYYY-MM-DD HH:MM:SS but most known formats to represent a date and/or time are accepted. | When the parameter is set to "today", we use today 00:00 / midnight as the currrent date. | When the parameter is set to "now", we use the system time as current date. | If the parameter is missing, empty or has an uncognized format, the system time is also used as current date. currency | Currency symbol. | This parameter may be only set on the default database and will be globally applied, across all the scenarios. | If the parameter is missing or empty the currency symbol will be the $. | By default the symbol will show after the value, i.e. **123 $**. | For the symbol to show before the value a **,** should be added after the symbol, i.e. **$,**, resulting in **$ 123**. display_time | This parameter controls if date time fields display the time. | Accepted values: true or false | This parameter applies to ALL scenarios. date_format | Date format to be used in the user interface and data imports. | Accepted values: month-day-year, day-month-year, year-month-day. | This parameter applies to ALL scenarios. loading_time_units | Time units to be used for the resource report. | Accepted values are: hours, days, weeks. excel_duration_in_days | Determines whether numbers in spreadsheets are considered as days or seconds. Default is true for days. | This parameter is only useful for backward compability. plan.administrativeLeadtime | Specifies an administrative lead time in days. | FrePPLe will plan the sales orders this amount of time ahead of their due date. This creates extra safety in the delivery schedule and also moves all material and capacity needs early. | The default value is 0 days, which is a just-in-time plan, where we try to plan all demands in **backward scheduling mode** from their due date. | Setting this parameter to a high value (eg 999) will result in a plan where everything is planned ASAP in **forward scheduling mode**. plan.autoFenceOperations | The number of working days the solver should wait for a confirmed replenishment before generating a proposed order. | Default: 999 (i.e. wait indefinitely) plan.move_approved_early | The planning algorithm by default will leave approved manufacturing at their scheduled date. In the Enterprise and Cloud Edition they will be delayed automatically to dates where they are feasible. | By setting this parameter to true, the algorithm can also try to reschedule them to earlier dates if there are earlier requirements. | This parameter has thre possible values: | - 0: Inactive. Don't move approved operationplans early. This is the default. | - 1: Active, and preserve existing resource assignments. | - 2: Active, and re-evaluate all resource assignments. plan.deliveryDuration | The duration (in working hours) for the delivery shipment of a sales order to the customer. | Default: 0 (i.e. the sales order due date is treated as the shipping date from our location, not the arrival date at the customer) plan.individualPoolResources | Defines the behavior of aggregate resource. | A operation-resource record with quantity N for an aggregate resource can mean either: | - Find a member resource with size N. Value false, default. | - Find N member resources of size 1. Value true. plan.loglevel | Controls the verbosity of the planning log file. | Accepted values are 0 (silent – default), 1 (minimal) and 2 (verbose). plan.minimumdelay | Specifies a minimum delay the algorithm applies when the requested date isn't feasible. | The default value is 3600. This value should only be changed when the planning run is taking a long time and the log file shows that demands take many iterations to be planned - where the requested delivery date for each iteration is advancing only in tiny increments. plan.fixBrokenSupplyPath | When set to true (which is the default), frepple will scan for items that can't be replenished any longer with purchase orders, distribution orders or manufacturing orders. | FrePPLe automatically creates a dummy/fake supplier for such items. In this way broken supply paths are automatically fixed. Planners will need to review such dummy purchase orders and update the master data to replace them with the correct replenishment method. | When this parameter is set to false, broken supply paths will result in unplanned demand. Analysing the unplanned demand is in most cases more complex than reviewing the dummy purchase orders. plan.rotateResources | When set to true, the algorithm will better distribute the demand across alternate suboperations instead of using the preferred operation. plan.webservice | Specifies whether we keep the plan in memory as a web service for quick incremental planning. This functionality is only available in the Enterprise and Cloud Editions. | Accepted values are false and true (default). COMPLETED.consume_material | Determines whether completed manufacturing orders consume material or not. | Default is true. COMPLETED.allow_future | We assume that completed operations are always ending in the past. The planning engine will automatically adjust the end date to enforce this rule, unless this parameter is set to true. | Default is false. WIP.consume_material | Determines whether confirmed manufacturing orders consume material or not. | Default is true. WIP.consume_capacity | Determines whether confirmed manufacturing orders, purchase orders and distribution orders consume capacity or not. | Default is true. WIP.produce_full_quantity | Controls how material is produced from partially completed manufacturing orders. | When set to "false" (the default) a partially completed manufacturing order is producing only the remaining quantity of material. We assume that the on hand inventory has already been incremented to reflect the produced material. | When set to "true" a partially completed manufacturing ordre will still produce the full quantity of the material. We assume that the produced material will only be booked as inventory when the manufacturing order is fully finished. pathreport_optimization | Activates a fast version of the supply path report, suitable for deep bill of materials with many components. | Default is false. plan.solver | Selects the algorithm to use for generating the plan. | Possible choices are "heuristic" (default), "heuristic_2" (an emerging evolution of the heuristic algorithm) and "distribution" (designed for distribution planning problems, only available in the Enterprise and Cloud Editions). ==================================== ======================================================================= **Demand forecasting parameters** The recommended default parameters for the demand forecasting module are different for daily, weekly and monthly time buckets. The parameters with a value "default" in the parameters screen can get a different value depending on the configured time bucket. ==================================================== =========================================================================== Parameter Description ==================================================== =========================================================================== forecast.calendar Name of a calendar model to define the granularity of the time buckets for forecasting. forecast.Croston_initialAlfa Initial parameter for the Croston forecast method. forecast.Croston_maxAlfa Maximum parameter for the Croston forecast method. forecast.Croston_minAlfa Minimum parameter for the Croston forecast method. forecast.Croston_minIntermittence Minimum intermittence (defined as the percentage of zero demand buckets) before the Croston method is applied. forecast.DeadAfterInactivity Number of days of inactivity before a forecast is marked dead and it's baseline forecast will be 0. Default is 365. forecast.DoubleExponential_dampenTrend Dampening factor applied to the trend in future periods. forecast.DoubleExponential_initialAlfa Initial smoothing constant. forecast.DoubleExponential_initialGamma Initial trend smoothing constant. forecast.DoubleExponential_maxAlfa Maximum smoothing constant. forecast.DoubleExponential_maxGamma Maximum trend smoothing constant. forecast.DoubleExponential_minAlfa Minimum smoothing constant. forecast.DoubleExponential_minGamma Minimum trend smoothing constant. forecast.DueWithinBucket Specifies whether forecasted demand is due at the 'start', 'middle' (default value) or 'end' of the bucket. forecast.Horizon_future Specifies the number of days in the future we generate a forecast for. forecast.Horizon_history Specifies the number of days in the past we use to compute a statistical forecast. forecast.Iterations Specifies the maximum number of iterations allowed for a forecast method to tune its parameters. forecast.loglevel Verbosity of the forecast solver forecast.MovingAverage_order This parameter controls the number of buckets to be averaged by the moving average forecast method. forecast.Net_CustomerThenItemHierarchy This flag allows us to control whether we first search the customer hierarchy and then the item hierarchy, or the other way around. forecast.Net_MatchUsingDeliveryOperation Specifies whether or not a demand and a forecast require to have the same delivery operation to be a match. forecast.Net_NetEarly Defines how much time (expressed in days) before the due date of an order we are allowed to search for a forecast bucket to net from. forecast.Net_NetLate Defines how much time (expressed in days) after the due date of an order we are allowed to search for a forecast bucket to net from. forecast.Net_PastDemand | When this parameter is false (default) only sales orders in the current and future buckets net from forecast. | When set to true also older demands are used for netting forecast. forecast.Net_IgnoreLocation | When this parameter is true the forecasting netting doesn't need a match between location of the sales order and the forecast. | This can be useful when sales orders are often shipped from a non-standard location. forecast.Outlier_maxDeviation Multiple of the standard deviation used to detect outliers forecast.populateForecastTable | Populates automatically the forecast table based on the item/location combinations found in the demand table using parent customer when available. | Default : true forecast.Seasonal_dampenTrend Dampening factor applied to the trend in future periods. forecast.Seasonal_gamma Value of the seasonal parameter forecast.Seasonal_initialAlfa Initial value for the constant parameter forecast.Seasonal_initialBeta Initial value for the trend parameter forecast.Seasonal_maxAlfa Maximum value for the constant parameter forecast.Seasonal_maxBeta Maximum value for the trend parameter forecast.Seasonal_maxPeriod Maximum seasonal cycle to be checked. forecast.Seasonal_minAlfa Minimum value for the constant parameter forecast.Seasonal_minBeta Initial value for the trend parameter forecast.Seasonal_minPeriod Minimum seasonal cycle to be checked. forecast.Seasonal_minAutocorrelation Minimum autocorrelation below which the seasonal forecast method is never selected. forecast.Seasonal_maxAutocorrelation Maximum autocorrelation above which the seasonal forecast method is always selected. forecast.SingleExponential_initialAlfa Initial smoothing constant. forecast.SingleExponential_maxAlfa Maximum smoothing constant. forecast.SingleExponential_minAlfa Minimum smoothing constant. forecast.Skip Specifies the number of time series values used to initialize the forecasting method. The forecast error in these bucket isn't counted. forecast.SmapeAlfa Specifies how the sMAPE forecast error is weighted for different time buckets. ==================================================== =========================================================================== **Inventory planning parameters** ==================================================== =========================================================================== Parameter Description ==================================================== =========================================================================== inventoryplanning.average_window_duration | The number of days used to average the demand to limit reorder quantity and safety stock variability over periods. | Default value : 180 inventoryplanning.calendar Name of a calendar model to define the granularity of the time buckets for inventory planning. inventoryplanning.fixed_order_cost | Holding cost percentage to compute economic reorder quantity. | Default value: 20 inventoryplanning.holding_cost | Fixed order cost to compute the economic reorder quantity. | Default value: 0.05 inventoryplanning.horizon_end | Specifies the number of days in the future for which we generate safety stock and reorder quantity values. | Default: 365 inventoryplanning.horizon_start Specifies the number of days in the past for which we generate safety stock and reorder quantity values. Default: 0 inventoryplanning.loglevel | Controls the verbosity of the inventory planning solver. | Accepted values are 0 (silent - default), 1 and 2 (verbose) inventoryplanning.service_level_on_average_inventory | Flag whether the service level is computed based on the expected average inventory. When set to false the service level estimation is based only on the safety stock. | Default value: false ==================================================== =========================================================================== **Inventory rebalancing parameters** ==================================================== =========================================================================== Parameter Description ==================================================== =========================================================================== inventoryplanning.rebalancing_burnout_threshold | The minimum time to burn up excess inventory (compared to forecast) that can be rebalanced (in days). If the burn out period (Excess Quantity / Forecast) is less than the threshold, the rebalancing will not occur. | Default value: 60 inventoryplanning.rebalancing_part_cost_threshold | The minimum part cost threshold used to trigger a rebalancing. Parts with a cost below the threshold will not be rebalanced. | Default value: 100000 inventoryplanning.rebalancing_total_cost_threshold | The minimum total cost threshold to trigger a rebalancing (equals to rebalanced qty multiplied by item cost). Rebalancing requests with total cost below the threshold will not be created. | Default value: 1000000 ==================================================== =========================================================================== **Report manager parameters** ==================================================== =========================================================================== Parameter Description ==================================================== =========================================================================== report_download_limit | The maximum number of rows that are allowed to be downloaded with a custom report. The limit protects against inefficient SQL report queries that download excessive ammounts of data. | Default value: 20000 ==================================================== =========================================================================== **Plan archiving parameters** Frepple keeps a history of the key metrics of your plan. These metrics are used to display overall trends in your plan, and can also be useful to debug the evolution of certain data elements over time. ==================================================== =========================================================================== Parameter Description ==================================================== =========================================================================== archive.frequency | Frequency of history snapshot. Accepted values are "week", "month" and "none". | Default value: week archive.duration | Archived data older than this parameter in days will be deleted. | Default value: 365 ==================================================== ===========================================================================