While historians and manufacturing execution systems (MES) have been around for a long time, there are still a lot of questions on how to best integrate both in order to maximize the benefit of each.


In the past historians have been used to store process data and allow comparing current to past process conditions. In the last decade this has changed and historian have now grown into powerful real time calculation engines that allow context specific analysis of a large number of assets (> 1 Million). This allows real time analysis of large and complex systems, such as windfarms, data center or turbines.


In MES systems the historian is mostly used as data source similar to SQL, OPC, LIMS, SCADA or others. This shallow integration only uses the data storage capabilities of the historian without benefitting from the real time calculations, data conditioning and abstraction. The following flow chart show both MES and historians in the ISA-95 functional hierarchy.



In general, there are two types of information flows in a manufacturing enterprise:


  •    Transactional\Relational data
  •     Real time data


Transactional data are found in order processing, resource management, Quality, labor, maintenance etc., while real time data mostly originate from the plant floor. Real time data bubble up from production level (Level 0, 1 and 2) to the site and enterprise level while changing their characteristics:


          Level 0, 1, 2: High frequency data milliseconds to seconds, source specific, noisy

·             Level 3: Medium frequency seconds to minutes, abstract, aggregates

·             Level 4: Low frequency minutes to hours, days or weeks, abstract, aggregates


It is important to note that the main data transformation occurs at the historian level, where data are compressed, aggregated (min, max, total, sum, …) and most importantly abstracted. The abstraction is performed by mapping for example a controller tag TIC01234.PV to the temperature property of a reactor (e.g. Reactor\Temperature). A data scientist will now be able build a reactor model or predictive maintenance calculation based on the abstraction layer, instead of searching through a vast amount of uncategorized data.


For similar reasons the MES system should not consume raw production data. Its primary function is order management, production performance calculations, forecast, quality & resource planning etc.
But performing real time transformations of process data on the MES system itself, will often lead to a loss in both performance and accuracy.

Therefore, interfacing the historian with the MES should be performed on the abstraction layer as the following diagram shows:




To successfully connect the historian to the MES system requires both to adhere to common standards such as S95 for the equipment model and/or S88 for the batch model. The interface will replicate the data structure between systems and validate the structural integrity.

The benefit of the above architecture is a deep integration of historian and MES that maximizes the utility of both systems. It separates the manufacturing data flows and creates common interfaces to exchange data and structures.




Historians play a central role in the manufacturing data flow of real time information. The main historian operations such as data compression, de noising, aggregation and abstraction can benefit the enterprise data analytic as well as the MES operations. This requires a deep integration of the historian by abstracting the data layer using common standards such as S95 and S88 and interfacing with the analog MES data structures. The result is an architecture that utilize both systems to the full extent of their capabilities while acknowledging the differences in the data properties and requirements.

While historians and manufacturing execution systems (MES) have been around for a long time, there are still a lot of questions on how to best integrate both in order to maximize the benefit of each.