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Kathy Barthelt
/ Categories: Infor LN & Baan Tips

Infor LN & Baan Tip: Performance improvement by setting the First Free Number Cache (tcmcs0651m000)

Many transactions in all kinds of modules use order numbers or serial numbers. These order numbers are most often automatically generated. In the Number Groups (tcmcs0151m000) session you can define groups of order numbers used for dedicated areas. A Number Group is a group of the first free number series that you can assign to a specific use. All the numbers that Infor LN generates in the number groups that are dedicated to the same purpose are unique.

All the first free numbers are stored in the table tcmcs050.

As many different processes can request a free number from the number groups, we often see delays in the performance, due to locking on the first free number records. This locking issue can have a severe impact on the performance of huge batch-type transactions, but also on the performance perceived by individual users in many areas in LN.

For example:

  • Processing warehouse transactions. Single or in-batch
  • Completing / closing orders
  • Backflushing of production orders
  • Generate Order Planning
  • Cost calculation and warehouse revaluation


How this performance can be improved?

Resolution

In the Number Groups (tcmcs0151m000) session you can open the details of a specific Number Group (tcmcs0651m000) or start the session stand-alone.

In the Number Group, you define the Series with the related First Free Numbers. Per Serie in the First Free Number, you have the option to define the Cache Size.

This Cache size is defaulted on a value of 0 (zero). A cache size of zero means No Cache. How does the First Free Number caching works:

  • When the Cache Size is zero: With this setting a process requests a Free Number from the Serie and the first free number is issued to the process. But the first free number record is not updated yet. At the moment the requesting process is finished, without errors, it reports back that the number is used and the first free number record is updated. All the time that the process is working on the transactions the first free number record is locked. If another process is requesting a free number from the same series, it must wait (retries) until the record is updated and released by the previous process. This is the locking which is causing delays in the other processes.  
  • Setting the Cache Size to a higher value then zero activates the caching. When the Cache Size is set to 1 or higher, the requested free number is sent to the requesting process, the first free number is updated, with the number as defined in the Cache size, and the record is saved. It does not wait until the requesting process has reported back that is finished, with or without errors. In this way the record is immediately released and no locking will occur. If another process is requesting a free number, it does not need to wait until the free number record is released by the earlier process. If the process is ended with errors and therefor the number is not used, this number from the series is lost. This can result in gaps in the numbering. When the cache size is greater than 1, for example it is set to 5, the requesting process receives 5 free numbers. Even if it only needs less than 5. In this way the process only has to request for a new free number after it has used the first 5 numbers from the cache. This will also speedup the process in case of large batch transactions. For ‘warehouse integration users’, like for example Factory Track or WMS users we advise to set the cache size to 5.  

Note that financial documents are not based on number group series / first free numbers. Instead they are based on transaction type series, for which the caching functionality does not exist. Financial documents, like sales invoices, bank transactions, are thus not cached.

The caching is especially important to improve the performance of all logistical processes.

It is strongly recommended (mandatory) to set the Cache Size for all Number Groups to a minimum of 1.

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Kathy Barthelt

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Tips:  LX | BPCS | M3

For years, repetitive manufacturing industries have been applying many of the principles in Just-in-Time philosophy. They have established balanced production lines that depend on a steady flow of material to each work station. They schedule production in daily or weekly rates rather than in discrete shop order lots. They track finished inventory by work center rather than by job. They typically backflush stock balances (decrement stock balances upon completion of specific manufacturing steps rather than issued at the beginning of each production run).

 

Costing is typically based upon a daily rate or hourly rate rather than being associated with specific shop orders. 

 

Repetitive manufacturers use MRP II software adaptable to their environments

in the following key areas:


 Product definition

 Inventory tracking

 MRP/Master Scheduling

 Shop Floor Control

 Purchasing

 Costing

Just-in-Time (JIT) is a management philosophy that focuses on minimizing the resources necessary to add value to your products and to operate your factory in ways that eliminate waste. Resources are labor, materials, equipment, space, and time. Waste is anything that does not add value to your products. Moving work-in-process from place to place, stacking and sorting, investing capital in large work-in-process and raw material inventories, inspecting materials at your vendors' sites, and tying up warehouse space with finished goods are all activities that add cost, not value, to your products. 

JIT is a process that reduces lead time. JIT does not replace an MRP, an inventory program, a scheduling technique to bypass your Master Schedule, or a materials management project. JIT is the never-ending commitment of everyone, from top management to your workers on the floor, to maximize your effectiveness through continuous, incremental improvements.

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Tips: LN | Baan

Instead of sharing tables through logical linking, you can replicate table content between companies. This approach allows certain non-key attributes of a record to vary by company. For example, if you replicate bills of materials rather than sharing them, each company can associate a different warehouse with the same bill of material. This way, the bills of materials are consistent across companies, while the warehouses can differ.

Replication also enables selective availability of records in other companies. For instance, when replicating items, you might limit which items are available in a sales company based on their item group, only including end items. You can further refine replication to specific subsets, such as particular item groups.

Keep in mind that replication requires any referenced tables to be either replicated or shared as well.

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