Application Monitoring: Dashboard

Application Monitoring: Dashboard#

The Dashboard is the main interface for real-time monitoring of the FlexiVision One system. On this page you can check process efficiency, analyse cycle times, validate component identification and identify any bottlenecks in the system.

Interface Overview#

The Dashboard interface is divided into four main sections: Dashboard Page

  1. Operational Control: Execution commands and status

  2. Vision Analysis: Display of detected parts and details

  3. Performance Indicators: Connectivity and cycle times

  4. Graphical Analysis: Productivity and time log charts

Operational Control - Commands and execution status#

Element

Description and Function

In Run

Status indicator showing whether the system is currently running.
Green 🟢: System on and operational.
Red 🔴: System stopped or paused.

In Run Time

This displays the total system uptime since application start-up.

FlexiBowl® selection

Drop-down menu to select the specific FlexiBowl® to be monitored.

Test Locator

It takes a picture of the vision area and starts the identification of the components present.

Tip

Test Locator Useful to:

  • Verify that the components are actually identified by the vision system

  • If there is a collision between robot and component and I want to check the reliability of the clearances

Vision Analysis#

The data for the components identified by the vision system are displayed in the centre of the dashboard.

Detected Vision Parts#

Detected Vision Parts shows:

  • Image captured in real time by the camera

  • A log chart of detections over the last 30 seconds showing the trend in the number of parts identified per capture.

Detected Models Table#

Detail of identified components

The table below the image lists all components in the pick area with the following parameters:

Field

Data Type

Description

Id

Integer

Progressive unambiguous component identifier (0, 1, 2, …). Id 0 = component with the highest score (best match to the model if sorted with Score Descending as recommended).

X

Millimetres

X coordinate of the component.

Y

Millimetres

Y coordinate of the component.

Rot (Rotation)

Degrees

Angle of rotation of the component.

Score

Percentage

Percentage value (0.00-1.00 or 0%-100%) expressing the degree of identification reliability. It represents closeness/fidelity to the reference model. Higher score = better match.
Score Interpretation#

Score > 0.90 (90%):

  • Excellent match to model

  • High confidence picking

Score 0.80-0.90 (80-90%):

  • Good match

  • Safe picking if Accept Threshold is configured appropriately

Score 0.70-0.80 (70-80%):

  • Acceptable match

  • Check consistency over time

Score < 0.70 (< 70%):

  • Poor match

  • If recurring, review model or Accept Threshold.

State and Performance Indicators#

Connectivity#

Communication with external devices status indicators:

Indicator

Description

FlexiBowl®

Status of the hardware connection between the VisionController (PC) and FlexiBowl®.
Green: Connected and communicating.
Red: Disconnected or communication error.

Robot

Status of communication with the robot.
Green: TCP/IP connection established.
Red: Disconnected or communication timeout.

Warning

Actions in case of disconnection

FlexiBowl® red:

  • Check Ethernet cable FlexiBowl® → VisionController

  • Check FlexiBowl® power supply

  • Check FlexiBowl® IP in FlexiBowl® Setup

  • Try reconnect or software reboot

Robot red:

  • Check Ethernet cable Robot → VisionController

  • Check that robot has open TCP/IP connection

  • Check TCP/IP port in Robot Setup

  • Check robot program (IP address of VisionController and Port inserted correctly in robot setup section )

In production, both indicators must always be green.

Time Analysis#

The system provides a detailed breakdown of cycle times to identify possible bottlenecks and optimise the process.

Time Entry

Description

Camera Processing Time

Time taken to capture the image from the camera sensor. This includes exposure time and data transfer.

Locator Processing Time

Time required by the vision algorithm to locate and identify components in the captured image. It depends on: number of active models, complexity of models, number of clearances.

Total Vision Processing

Sum of Camera and Locator times. It represents the total time it takes for the vision system to process an image and send the co-ordinate(s).

Total FlexiBowl® Time

Time taken by the FlexiBowl® to perform a complete handling sequence.

Total Robot Time

Estimated or detected time for the complete Pick & Place operation of the robot. It includes: approach → pick → place → return.

Total Processing Time

Total time of complete cycle (Vision + FlexiBowl® + Robot). It represents the time from the start of one cycle to the start of the next one. It determines the theoretical maximum productivity (PPM).

Tip

Time interpretation for optimisation

The time chart allows the bottleneck of the system to be identified:

If Total Vision Processing is the highest:

  • Too many active models → Disable unnecessary models

  • Models too complex → Simplify with higher Score Threshold

  • Too many clearances → Reduce number or size of clearances

  • Camera Processing high → Reduce exposure time

If Total FlexiBowl® Time is the highest:

  • Too many pauses → Optimise Flip/Move synchronisation and reduce stabilisation pause (Pause X ms)

  • Movement sequence too slow → Increase speed in Config FlexiBowl®

  • Excessive rotation angle → Reduce Move Angle

  • Shake too long → Increase SHAKE speed and reduce SHAKE cycles

If Total Robot Time is the highest:

  • Robot path not optimised → Optimise robot path planning

  • Robot speed too low → Increase movement speed (if safe)

  • Place distance too long → Reposition place point closer

  • Pick times too long → Optimise gripper opening/closing

Optimisation target: Balance the three times to reduce overall Total Processing Time.

Graphical Analysis#

The charts at the bottom of the dashboard provide a predictive and diagnostic analysis of system performance over time.

1. Parts Per Minute (PPM)#

Productivity chart

Shows the average productivity of the system expressed in components picked per minute (Parts Per Minute).

Features:

  • X-axis: Time

  • Y-axis: PPM (parts per minute)

  • Trend line: Mobile mean to identify trends

Use:

  • Monitor productivity stability over time

  • Identify performance degradations

  • Calculate actual vs. theoretical throughput

Tip

PPM Interpretation#

Constant and stable PPM:

✓ System configured properly
✓ Optimised parameters
✓ No critical bottlenecks

PPM progressively decreasing:

⚠️ Possible component wear (FlexiBowl® grip surface)
⚠️ Hopper emptying
⚠️ Dirt buildup on camera/lighting

PPM with large fluctuations:

⚠️ Instability in the process
⚠️ Intermittent identification problems
⚠️ External interference (vibrations, variable light)

Corrective actions:

  • Analyse correlation with time charts

  • Identify which component (Vision/FlexiBowl®/Robot) causes variations

  • Intervene on specific parameters

2. Fill Hopper#

Hopper activation chart

Represents the log of the unloading pulses sent to the hopper.

Features:

  • X-axis: Time

  • Y-axis: Hopper Activations (events)

  • Peaks: Each peak represents an unload activation

Use:

  • Check effectiveness of Hopper configuration

  • Identify anomalies in unloading behaviour

Tip

Fill Hopper Pattern Analysis#

Regular and constant activations:

✓ Optimal Hopper Configuration
✓ Stable and foreseeable flow of parts
✓ Calculated autonomy (e.g. activation every 10 minutes)

Ever more frequent activations:

⚠️ Hopper is emptying (fewer parts = more activations to maintain level)
⚠️ Insufficient unloading time due to reduced volume
Action: Plan Hopper recharge soon

No activation for a long time:

⚠️ Robot stopped or slowed down (parts not consumed)
⚠️ Possible system problem that does not require parts
Action: Check production status

Very close activations (bursts):

⚠️ Hopper threshold not configured properly (too high)
⚠️ Insufficient steps (parts do not arrive on time)
Action: Review Hopper Config

3. Vision - FlexiBowl® - Robot (Comparative Chart)#

Overlapping time chart

A three-line comparison graph that overlaps the timing of individual processes over time.

Use:

  • Instantly identify which process most affects the total cycle time and how it changes over time.

Quality Monitoring - Critical Indicators to be monitored#

Component Score

Make sure that the Score of the detected components is constantly above the tolerance threshold (Accept Threshold) set during model configuration.

Score Monitoring:

  • Periodically check Detected Models table

  • Check that typical scores are 0.85-0.95

  • Investigate if scores regularly drop below 0.80

Gradually decreasing scores:

⚠️ Real parts different from training (production variations)
⚠️ Lighting changed (weaker backlight, dirt)
⚠️ Camera no longer focused (vibration, blows)
⚠️ FlexiBowl® surface dirty (interfering pattern)

Corrective Actions:

  • Clean camera, lighting, FlexiBowl® surface

  • Check camera focus

  • Consider re-training model if parts have changed

  • Reduce Accept Threshold if scores are still reliable but lower

Production Monitoring Best Practices#

Daily checks#

At the start of production (5 minutes):

  • Check FlexiBowl® and Robot connectivity indicators (green)

  • Check that the initial cycles show normal scores (>0.85)

  • Observe that PPM stabilises at the expected value

During production (check every 1-2 hours):

  • Take a look at PPM to check stability

  • Check Fill Hopper to predict necessary refill

  • Check the log for errors or warnings

At end of shift (2 minutes):

  • Take note of average PPM of the shift

  • Check number of times Hopper activated

  • Check for any anomalies or events

  • Compare with previous day’s data

This minimum routine ensures quick identification of problems and maintains performance traceability.

Performance report#

Tip

Key metrics to be tracked To evaluate performance over time, track:

Daily:

  • Average PPM of the shift

  • Total number of parts picked

  • Number of Hopper activations

  • Total downtime (and causes)

Weekly:

  • PPM trend (increasing/decreasing?)

  • Theoretical vs. real PPM comparison

  • Average score of detected components

  • Any configuration changes and their impact

Monthly:

  • Overall Equipment Effectiveness (OEE)

  • Analysis of main bottlenecks

  • Need for predictive maintenance

  • ROI of the system

This data enables continuous optimisation and justifies investment in improvements.

The system is now operational!
Congratulations! The FlexiVision One system is now fully configured, optimised and validated for production.
Summary of completed process:
✓ Hardware setup (FlexiBowl®, Robot, Camera)
✓ Complete calibration (Camera, Robot)
✓ FlexiBowl® configured for optimal handling
✓ Hopper configured for automatic feeding (if present)
✓ Part models created and optimised
✓ Validated system with Dashboard monitoring
✓ Verified and stable performance
The system is ready to operate in production with minimal supervision.
Latest useful tools:
Troubleshooting
Troubleshooting guide for common problems
Support
Technical support contacts

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