Manufacturing Execution Systems (MES) by Heiko Meyer & Franz Fuchs & Klaus Thiel

Author:Heiko Meyer & Franz Fuchs & Klaus Thiel
Language: eng
Format: epub
Publisher: McGraw-Hill Education
Published: 2009-07-14T16:00:00+00:00

7.1.4 Scalability

As is generally known, the only constant is change. If we follow this maxim, which applies somewhat for modern production, scalability is another important requirement of the system architecture of the MES in addition to platform independence. On one hand, the system must be adjusted as precisely as possible to the requirements of the customer, and on the other, changes in the production structure, that is, both changes in the scope of functions and in the quantity structure, must be easy to map out in the MES.

Changes in the scope of functions generally arise from the introduction of new products or from new ideas on organization and the changed activities linked with them. Examples here are the introduction of a worker information system or the switch to group work with a changed wage system. Many system suppliers cover such functional expansions with independent software modules, which are offered as add-ons for the basic software.

Scaling as per the quantity structure is more difficult and also affects the software architecture. The following key data of the system should be taken into consideration with regard to scaling:

• Number of machines and workplaces

• Number of articles produced

• Number of measurement values taken/sample rate for the measurement values taken

• Number and frequency of reports created (e.g., disruption reports from production controls)

• Number of simultaneous users (i.e., client stations on the network)

• Number and calculation cycle of key performance indicators (KPIs) and quality data

• Archiving period for KPIs, quality data, measurement values, and reports

• Type and frequency of evaluations of data sets

• Number of interfaces and frequency of data exchange

These points affect the database in particular, whereby the transaction volume (effects on the CPU load and the interfaces of the system) and data volume (effects on the required memory capacity) aspects are taken into account. This means that both the processing power of the database system (usually in the form of additional processors) and the memory capacity (usually in the form of additional hard drives) should be suitable for flexible scaling.

Based on the suggested architecture in Sec. 7.1.2, the second bottleneck arises with growing quantity structures in the application server. Here, too, scaling can occur through adjustment of the processing power (i.e., additional processors), but the individual processes (applications) of the system can be allocated to several processing systems. The option to allocate the processes to several systems is a true advantage for system running and maintenance as well. With the example of the suggested architecture in Sec. 7.1.2, all components represented could be run on a common server in the simplest case. This architecture would lower the costs for a small system with small data quantities. At the other end of the scale, however, each of the software components represented could work in a separate server system. In order to be able to realize both extremes represented, the architecture must be appropriately flexible and as platform-independent as possible (see Sec. 7.1.3).

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