Core Concept behind event trigger monitoring inside Litmus Production Record Database

production events occur all the time when running a production process and are also known as steps, procedures, batches, runs or operations regardless of the terminology, they all share that they have a start and and end which is always identifiable by what is often called a trigger this can be as simply as the change of a boolean value for example when switching a motor on or off, opening a valve or pressing a button or can be a complex combination of conditions like for example "the temperature has to be +40°c, the pressure has to be 3 bar and tis valve has to be closed" to allow for the event to start this use of complex conditions is very common in industries like chemical, oil & gas, pharma, food & beverage and energy for simple tag conditions, litmus production record database offers an inbuild event trigger monitoring option the basic requirements are the existence of a data model for event recording > recorded through an eav data model the existence of all the process tags which deliver the data for the data model > recorded through an eav data model the existence of a event trigger monitoring configuration which specifies what the trigger condition is and what data are to be recorded if a trigger is true > stored by a relational database model if these three requirements are fulfilled, litmus production record database is able to monitor the raw process data for all trigger tags constantly for the occurring of the defined trigger condition once a trigger is identified, it then collects from all the tags associated with the event the values and stores them according to the data model it is also capable, of recording calculated values like the minimum, maximum, sum or average of a process tag over the period of the event as it is capable of retrieving all the process values for the event from the database and execute the desired calcualtion monitoring of complex trigger conditions is currently not supported withhin litmus production record database itself as potentially complex relations and calculations often require dedicated coding and simply can't be represented as simple values stored in a database instead it is encouraged to make use of systems more suited to this kind of complex relational monitoring such as for example making use of the programming capabilities of litmus edge flows one option for complex trigger monitoring is provided by the litmus solution " litmus production record event processing flow " for which the documentation can be accessed here litmus production record event processing flow docid\ urgnidlcu3l67mr95hq5p as for complex event trigger monitoring, no raw process data are send to litmus production record database, it by itself can not record the results of calculations like the "minimum", "maximum" or "average" as value for the data model the picture below shows how a the flow of the products and the signals created by the process can be translated into a trigger event monitoring configuration to record them when they happen