Thanks to the recording of process values such as quantities, cycle times or energy values in combination with continuous monitoring by means of defined target and limit values, the software solution enables optimized production efficiency beyond the event of a malfunction. Just as in the event of a standstill, the system provides information about irregularities and deviations and thus offers not only monitoring, but also the basis for optimized decision-making. This allows you to get the best out of your production.

The following screenshot shows such a TopX evaluation – the faults shown in red were identified as particularly relevant, as they have been appearing as top faults over a longer period of time.

A typical representation, a Kanban board, of all open measures is shown in the following screenshot:

You need to know the causes of the rejects in order to take further action. By clicking on a red piece of cake and a menu via the 3 dots at the top right, the corresponding piece count history opens in the sidebar.

In addition to availability and quantities, other key figures are used to increase overall system effectiveness. The following example shows a typical illustration that helps to detect faults in the process. In the lower area, each point represents a cycle time – all points that are not in the green-yellow band are cycle time overruns above the limit values. In each case, there are faults in the process.

As part of the further production data analysis, the diagram is “zoomed” into the affected time range. The 3 dots at the top right of the boardlet can then be used to take a closer look at the respective fault messages for the affected time range.

Tracking & tracing for component traceability is a core function of the Legato Sapient MES solution. It enables seamless tracking and tracing of all products, including all product-relevant data – throughout the entire production process. This creates a complete image of each production unit – a digital twin. This includes all product data (e.g. order, type, features, quality status), product-related process data (e.g. torques, temperatures) and product-related system data (e.g. status, faults).

Furthermore, tracking & tracing via an MES as a global control station has the advantage that you can view and analyze the seamless component tracking of all product-relevant data across the entire production process (from raw material to end product) at any time – unlike with local RFID data storage, for example. An MES can act as a central data hub for this purpose, providing not only transparency within the entire production area – horizontal data integration – but also real-time information from the store floor for the business level – vertical data integration.

With all the collected and stored data, a large number of aggregated values and key figures can be generated (e.g. processing and transport times, quality level), which serve as the basis for the continuous improvement process (CIP) and thus enable an increase in efficiency in terms of costs, time and quality.

For some production processes, it is not possible to transport the production unit itself. For this purpose, special means of transportation are used as “workpiece carriers”. Carriers or skids have their own ID (carrier ID), which is used for identification at the reading points. The identification of the production unit in the PU coordination is then carried out indirectly via the carrier ID to which the PU ID was assigned during merging. This is now a standard method for establishing the link between the identified carrier and the production unit.

The dashboard provides all information on the Track & Trace reading points (identification points) and the production units identified via them. The navigation tree (logical production structure) is displayed in the left-hand area. There are no reading points for the currently selected node “Plant 3” and therefore no information is displayed in the “Reading points” and “Production units” boardlets.

To narrow down the search radius of affected PUs, the list of production units identified here can be filtered by selecting a read point. The PUs now identified (in the example only one PU with ID “PU0000002”) are displayed.

The detailed view shows the complete tracking history of the PU, which was created based on the identification at the individual reading points in combination with automatically recorded process/machine data and operator input. This means that the entire logged process can be viewed and analyzed in terms of tracing. For better analysis, the view of the “Production unit details” boardlet can be maximized and the side navigation tree can be hidden.

In edit mode, it is possible to change the status of the PU (e.g. released, blocked) or the Q status (e.g. n.i.O. for quality inspection), among other things. A preconfigured selection list with the possible states makes it easy to select the parameters. This PU history is updated or extended when the changes are accepted.

Legato Sapient creates digital “maintenance cards” in which the measures carried out are documented, archived and processed in accordance with TÜV requirements. Responsibilities and maintenance intervals are clearly defined. The system automatically calculates due dates based on both time and value using the prescribed, maintenance-relevant criteria. The maintenance team is guided by the interactive dashboards in Legato Sapient and can concentrate on ensuring a trouble-free and efficient production process. Operations is made up of two components, TPM planning and TPM orders.

TPM orders are generated from TPM plans using various triggers. These trigger a maintenance order based on time, value or message. It is also possible for the system operator to submit an ad-hoc maintenance request. Legato Sapient triggers time-based orders as soon as a defined interval of days or shifts has elapsed. For value-based triggering, online data from the control system is evaluated, which triggers an order when threshold or limit values (e.g. number of units produced, throughput or vibration values) are reached. Legato Sapient creates message-based jobs when the control system sends a dedicated alarm.

To make the aforementioned benefits of continuous process optimization tangible, Legato Sapient includes an additional module for TPM analysis. This shows the current situation on the store floor at an operational level. System status and alarms as well as the status of maintenance orders can be visualized and monitored. In retrospect, it enables the evaluation and comparison of historical data, in particular alarms, maintenance-specific KPIs (MTTR, MTBF, system availability, etc.) and the maintenance history (tasks, time stamps, responsibility). This makes it possible to prove the increase in performance and establish an active CIP.

Furthermore, attachments such as technical drawings or similar can be attached to maintenance plans.

The screenshot opposite shows all open maintenance activities in the selected area, including the corresponding filter settings. The display of relevant additional information (columns), such as activity description, reason, status, etc. can be flexibly adapted.

The activities within a maintenance order are then processed by a responsible person (typically assigned to the maintenance order or activity in advance by the maintenance manager or the TPM coordinator).

Once all activities of a maintenance order have been completed (including documentation of completion by the maintenance employee), it is closed and the corresponding due date counter is reset.

The HMI module at a glance

• Device-independent, web-based solution: visualizations available anytime and anywhere without expensive hardware and middleware
• Decentralized perspective: Local operating terminal with system-related visualization
• Insight into system data and holistic overviews from Legato Sapient
  Server-based solution for graphical process visualization and process-related operation
• Support for several hundred individual stations
• Low latency (< 1 second) for production-critical interactions: Data stream without detours via the database
• Control of user-specific functions through rights concept, e.g. for executing safety-critical actions only in the visible area of the system

For the morning meeting in the classic sense, the manual effort required for preparation is often considerable, as the relevant data is compiled and prepared and then posted on the pinboard in paper form. Despite the considerable effort required for preparation, the information is only available locally.

By using a central, database-based store floor system and the corresponding automated provision of data, the information can be accessed anytime and anywhere. This is the only way to ensure that important information is distributed quickly and easily. If, for example, system malfunctions occur, this information is not only important for the participants in the morning round. Rather, this information should be distributed to other areas as quickly and easily as possible.

Rational topics play a major role in the classic morning meeting, and the topic of “employee motivation” rarely finds a place in such a meeting. Archiving the data (e.g. accidents at work or quantities achieved) and viewing it over time also allows information that has an impact on employee motivation to be visualized – in this way, “successes” that have an impact on employee motivation can be visualized in the digital morning round. For example, in the area of occupational safety, the topic “Accident-free since…” can be visualized.

The productivity or performance of the previous shift could be underlined in the form of a smiley face, for example. If the planned number of pieces has been achieved, a smiling smiley appears and turns green. Other scenarios are of course conceivable.

In addition to the contents of a morning meeting presented so far, the CIP (continuous improvement process) and the resulting process improvement is of course one of the core elements. In the classic morning meeting, measures that lead to a possible process improvement are defined and listed on the pinboard, including responsibility and plan date – the measure or its status is only tracked manually.

Start screen of the digital Shopfloor Management of the MES software Legato Sapient. 20 minutes morning round is started. The focus is on safety, quality and logistics.

Predefined process with a fixed number of participants or roles. One store floor meeting per shift or day is held for each area/team. Information is aggregated from the bottom up: Incidents (e.g. delays, accidents) or production figures (unit counters, KPIs) are recorded at the bottom at store floor level. The aggregation of these values is then available at a higher level. The news boardlet is used for announcements and general information, where information flows from top to bottom.

The three calendars Safety, Quality and Logistics are used to record incidents. The option of providing additional customer-specific calendars can be guaranteed. An overview of the existing incidents filtered by area and incident type can be seen at the bottom of the store floor dashboard; when an incident is selected in the list, a window opens with a detailed view of the incident in which it can be edited.

Here you can see an example of the “Logistics” area within Digital Shopfloor Management. Important information on logistics within your production can be viewed here.

Drill down into the areas, lines, shifts, online data from the MES system and the machines.
Viewing all relevant data from machine data acquisition, prepared in the corresponding dashboards, is part of the digital store floor meeting.

Actual quantity:

The adjacent image shows the “actual number of pieces” within production with our software. You can see here how many pieces have been produced and can flexibly track these figures in order to increase your production.

If, for example, quality is discussed, the customer returns, quality problems, etc. are made available in a report. Furthermore, individual customer returns from the CAQ system are further explained. All with drill-down functionality for more detailed information.