Shop floor

MES functionality, closing the gap between scheduling and automation

Real-time scheduling isn't possible without accurate and up-to-date information of the physical reality.  This is where the PearlChain shopfloor product provides modern MES functionality that digitizes the factory floor:

Todo list

In the Todo lists, the operators manage the production orders that have been released for execution by the planner.

The production orders are presented in the sequence of execution.  This makes the Todo List the single source of work instructions for the operator, digitizing paper-based flows in the factory.

This process operator dashboard updates automatically during the day, reflecting changes in the plan as operations are ongoing.  The supervisors also can be given the freedom to reschedule the work (as needed), and tge consequences of these actions will be calculated for other orders and material provisioning.

For each machine in the factory, the setup of the todo list can be customized via ShapeIT, defining which activities can be performed and by who.

Carriers / WIP

Moving raw materials/semi-finished products and finished goods on the shopfloor often involves using a vessel/recipient of some kind:

Carriers are used to register goods into and out of these vessels while maintaining

Carriers registration (consumption and storage) is fully integrated into the shopfloor Todo list, validating the correct usage of products versus the BOM of production orders.

QA/Maintenance Integration

Integration of inspection jobs in the production flow, closely following the registrations in production is instrumental to delivering a quality product.

Triggered by any traced event in the system, a workflow can be set up to raise inspection jobs for QA teams (either inline or across production runs).

At the same time, maintenance teams might be needed to fix and install installations.   The shopfloor functionality can allow the operator to raise a maintenance request to the engineers, eg. in case of downtime.

Such a request can be handled in the ERP/Maintenance system, or directly in PearlChain (as a human task).  Even more, automation of order creation is possible by setting up a workflow that reacts to the registration of e.g. downtime.

Scrap/Waste/Cycle registration and OEE

Besides registering production execution and results, it's often interesting to learn more about the OOE/OEE of your installation.

In such case, it's important to collect correct detailed metrics of how you're running:

Ideally, this data can be collected automatically from sensors, without operator input.  PearlChain supports using the ALC technology to measure PLC parameters.

Additionally, for older installations, it is possible to ask the operator to provide the metric via the UI, with a configured time interval.


The collected figures for cycle times/waste/scrap and production results can be investigated in the Todo list, linked to the production orders.

Using real-time OOE/OEE dashboards, visualization across machines are created for supervisors, plant manager, operations manager, and supply chain analysts.

Extraction to BI tooling for further analysis is possible (e.g. to correlate the metrics with data from other systems), or can be analyzed in PearlChain directly, for continuous improvement purposes.


The Manual Rescheduling Gantt chart provides the rescheduling functionality of Todo lists in a graphical representation.  The visual representation provides an easier insight into where production capacity is still available and rescheduling can be done through drag & drop. 

The graphical view is designed to be very user-friendly for planners and supervisors who need to manage plan execution across an extended timeframe and multiple machines. 

The same rescheduling features can be configured on regular Todo Lists, obviously governed by the necessary authorizations.

Downtime Registration

Registration of downtime, including the reasons why, can be easily done by the operator without switching context.

The system helps by providing a list of possible codes that are context-specific, which avoids data entry mistakes.

An overview of the recent outages is available at any time and per order.  When shift change is performed, this helps the knowledge transfer between teams.

When the PLC exposes machine speed/cycle times then downtime can be automatically derived from the data flow.

Lastly, but quite importantly: downtime is taken into account when recalculating the schedule for the machine: the expected finish time for the current order, and all the subsequent orders, will be automatically recalculated behind the scenes.

This, in turn, allows us to provide real-time status updates of logistic processes (staging/picking), and make automatic planning proposals.