Production Event Tracking

In the manufacturing industry, the process or processes which are directly related to creating value are these related to turning raw material into a sellable product.

Success is typically measured profit which is at a high level calculates as revenue, which is typically the quantity of product sold at a specific price reduced by the combined cost associated with making this quantity. This does include cost for:

To maximize profit, lowering the cost of making product is one of the most popular strategies, as increasing the price of your product is often a hard sell in a competitive market.

For reducing the cost of manufacturing, it is of utmost importance to identify where the biggest gains can be made with the least investment. Therefore, recording events related to making a product which include information related to:

are the first step of being able to identify the root causes for high cost and identify solutions for reducing this cost.

A manufacturing company creates four different products using four different lines and one common single separate station for quality testing.

To improve their competitiveness, the organizations seeks to record data related to their manufacturing process, with the goal to use these data to identify potential for improvements.

Data of interest are especially:

The company has Litmus Edge deployed on a line to line base as well as a dedicated Litmus Edge at the quality station.

Data are collected both from the lines control system such as PLC's as well as manual recorded through a Litmus Partner Solution. As the company also uses an Energy Management system, these data are also recorded through Litmus Edge.

As many of the triggers do require the monitoring of different tags as well as are only true if certain combinations of data are present, the trigger monitoring is performed through the flow provided by the solution Litmus Production Record Event Processing Flow.

The data collected for each trigger are send to Litmus Production Record database and are organized and recorded there.



Each line is capable of creating each of the four products, which in turn has its own distinct series of operations and steps to perform.

As the four different products do share some commonalities, a single data model is used where each event is identified by a unique combination of the product number and serial number.

The production process is considered as started, once an operator enters the product number and serial number and acknowledges this combination.

For this trigger, beside the product number and serial number, also the start time, asset and line are recorded.

Further triggers are setup to monitor each specific production step like extrusion, drying, shaping and so on. For each of these process steps, the start and end time are recorded as well as the operational set point and the process value at the start and end of the step.

At each line, the stations are connected via conveyer belt and a signal is recorded if a product does leave or access a station.

The transfer to the quality station is done via a tray system. At the quality station, the operator does manually test each product which arrives using another Litmsu Partner Solution for manual process recording. The data recorded by this system include the product number and serial number which allows to append the quality data to the event record.

If the product do pass the test, the event is considered as finished and the final end time is recorded.

In case the part does fail, two options are available to the operator. Either the piece is marked as scrap, this will also close the event and record the end time with the final status of scrap.

If the piece is considered reworkable, it is returned to the line with a node what to do.

if the piece is then reworked, the respective operation is recorded again against the event.

For steps where data from the energy management system are available, the data for the start and end of the step is recorded to provide an indication about the amount of utilities used.

The picture below shows a graphical representation of the data model.

The orange box shows the Node Name and therefore the name of the Data Model.

The blue boxes show the names of the Stations as Level 1. While the dark gray boxes are operations defined as Level 2. Operations are executed depended on the product and are not run for each product number.

Green Boxes show Items recorded. The Purple boxes are the Item which are also the Identifiers for a Production Event. The Identifiers are what users will typically use to retrieve the data.

Data Models can be created using the Litmus Solution Litmus Production Record Data Model Configurator.

The picture below shows, which tags would need to be defined on each Litmus Edge as the minimum for both event trigger monitoring and as data for the recorded event.

The orange box represents the device name of the device on Litmus Edge, as Litmus Edge.

The blue boxed represent the tag names while the purple box the data type.

The picture below shows the event trigger configurations which are used by flows. Using a flow like the Litmus Solution Litmus Production Record Event Processing Flow, allows the monitoring of triggers which depend on multiple tags. Such as for the start and end of the production process.

As each production line and the quality station have their own Litmus Edge, the flow will run on each of these devices running the respective configuration.

The processed data are all send to Litmus Production Record Database where the data can be stored correctly due to the identifiers transmitted.

The event monitoring configurations used by the flow downloadable from the Litmus Solution Litmus Production Record Event Processing Flow, can be defined using the Litmus Solution Litmus Production Record External Event Configurator.

The picture below shows how flexible the data recording for each event can be.

The last event, highlighted in red, shows how the quality of the product was first set to a fail state (value = 0) and went back to the line for rework.