Master data

Fig. 4. Reduced time plots, fr = (f/fo.s), for the isothermal decomposition of ammonium vanadyl oxalate using master data for the Avrami—Erofe ev equation [eqn. (6), n = 2], by the application of a method of analysis [73] described in the text. The circles are experimental measurements and the lines correspond to exact agreement with the equation. (Reproduced, with permission, from Thermochimica Acta.)...

The two following examples are different with respect to the demands, constraints, objective functions and the whole master data and transaction data. They were constructed as reference examples out of real life requirements and real life systems. 

Figure 6.10 shows the data flow of the software tool BayAPS PP for optimal capacity assignment for given stochastic demands. Transaction data about demand and inventories is typically imported from SAP R/3 as indicated, production capacity master data and side conditions are stored in the software tool. Forecasts can be taken from a forecast tool or from SAP R/3. The output ofthe tool is a list ofpriorities of products and their lot sizes, which are optimal based on the presently available information. Only the next production orders are realized before the computation is repeated, and the subsequently scheduled production is only a prediction. 

The other master data elements for which an integration process is required are recipes. Recipes used within the PP/DS module are tightly integrated with the recipes in the ERP system. For complexity reduction in master planning, as outlined in the SNP section above, simplified recipes are used in SNP. These are derived from the PP/DS recipes by a flexible, automated conversion process. 

The SNP optimizer is based on (mixed-integer) linear programming (MILP) techniques. For a general introduction into MILP we refer to [11], An SAP APO user has no access to the mathematical MILP model. Instead, the modeling is done in notions of master data of example products, recipes, resources and transportation lanes. Each master data object corresponds to a set of constraints in the mathematical model used in the optimizer. For example, the definition of a location-product in combination with the bucket definition is translated into inventory balance constraints for describing the development of the stock level over time. Additional location-product properties have further influence on the mathematical model, e.g., whether there is a maximum stock-level for a product or whether it has a finite shelf-life. For further information on the master data expressiveness of SAP SCM we refer to [9],... 

In our case study, the problem instances for SNP optimization result from master data of approximately 10000 location-products, 10000 recipes, 400 production resources and 10 resources relevant for campaign production with 3-10 different products per campaign resource. This translates into a MIP model with about 700 000 continuous variables, 1000 binary variables and 300 000 linear constraints. 

An APS planning model contains master data and dynamic data. 

Due to the fact that one might not want to use all ERP business data objects in the APS system, an integration model is used to define for which plants, resources, materials, customers, etc., the integration interface should be active. The APS system also allows to maintain additional master data or to modify and enhance master data that came from the ERP system. Sometimes there are also additional types of master data (e.g. resource setup matrix) or information fields to master data (e.g., scheduling horizon) that really have no analogy in the ERP system and thus have to be maintained directly in the APS system. 

The batch management of production simplifies the process and makes it easier to control the status of transformation between raw and final products [2], Some of the data used to follow the material performance around and out of the product manufacturing process are batch-where-used-list, initial status, batch determinations, master data, and expiration date check [15]. 

The decision over whether a process or fnnction affects GxP shonld be dictated by its operational role and if it is used to maintain GxP master data, as illustrated in Figure 7.2. GxP roles include ... 

Well-characterized test chromatograms derived from standards or real samples are stored on disk as a master file. Chromatograms may be supplied by the vendor as part of the software package or can be recorded by the user. This master data file goes through normal data evaluation from... 

Purchase Order Receipt Control Sales Order Dispatch Control Inventory/Material Requirements Control Eorecast Demand Control Manage Eorecast Master Data Manage MRP Master Data Manage MPS Master Data... 

Changing Shelf Life of Products Reassigning Products Annual Product Review Maintain BOM Master Data Maintain Master Recipes... 

The master "data dictionary" table, which describes all the objects in the database, as well as some parameters that are specific to the database (exact match criteria, version of the database, etc.). This is sometimes referred to as "metadata" or "data about data."... 

The most important feature of Master Data is the simple data base format. This allows manipulation of the data by computer programs designed to assist synthesis. To facilitate use of these programs, MWF and each of the parameters are assigned a numerical code (1-8) as column identifiers. 

In the following sections, the Master Data programs are described with relevant examples. 

Master Data, now in its third edition, is approaching its final length though a few new substituents may be added each year. However, there is plenty of room for new parameters and we expect to add several new sigmas(JL5), Bondi s volume(l6) and some of the Sterimol constants (17) in the next edition. 

Our most ambitious project is the generation of a multisubstitution parameter table. All meta and para combinations of Master Data would total about 100, 000, 000 and be highly populated with synthetically inaccessible examples. Such a data base would be too costly to store and impractical to run. Even very narrow ranges would have printouts with thousands of examples most of which are useless. In order to restrict the data base to synthetically possible combinations we will generate the data in a novel way. One of the sub-tables of Master Data is called Comsub Data and contains 50 common groups. Comsub Data will be used in conjunction with Master Data to generate the additive Multi Data table with the following restrictions. 

For disubstitution, one of the groups will come from Comsub Data, the other from Master Data. If we decide to include trisubstitution, two of the groups will come from Comsub Data. 

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