Analyze Process Data – Open Up Efficiency Potential

Do some of your production machineries stop too often due to errors, or do you see room for improvement in cycle time? Do you think your production processes are already perfectly optimized?

The standalone version of our ArtiMinds Learning & Analytics for Robots (LAR) software identifies problems, error cases and hidden efficiency potential in your existing robot systems and automation processes. Continuous process monitoring and detailed analysis of sensor and robot data make it easy to find optimization opportunities, e.g. for greater robustness or shorter cycle times, and you can identify improvements at a glance.
For process analysis, ArtiMinds LAR uses the hardware already integrated in the production machineries and interfaces such as OPC UA and can therefore be easily retroffited at any time – without additional new hardware investment.

Objective Data Analysis with ArtiMinds LAR – Process Monitoring Benefits:

Automatic Data Acquisition &
Monitoring

Simple Troubleshooting

Real-time Data Analysis

Easy Integration & Connection of Components

Local Data Storage

Easy to Retrofit

Reduce Costs

Increase Product Quality

Focused Process Optimization

Reliable Traceability & Transparency

Process Analysis, Optimization, Predictive Maintenance & Documentation

Imagine if you could minimize your troubleshooting, repair and retesting efforts and even prevent production downtime before it occurs.

ArtiMinds LAR pursues a process-oriented approach and ensures maximum transparency. Long-term data acquisition and comparison can be used to determine wear on the workpiece, detect deviations between different product batches, uncover the causes of problems, optimize cycle times, shorten waiting times, improve quality, plan maintenance and minimize maintenance costs, and much more.

Users benefit from synchronized data reconciliation between the robot controller or PLC and the sensor components, which would be difficult to implement manually. The software uses existing process data and already integrated hardware. New investments are therefore usually not necessary.

Dive into the use cases

Continuous Process Monitoring – Without Additional Effort

What if there was hidden efficiency potential in your production facilities?

ArtiMinds LAR records all data permanently and in real time. On the one hand, this increases transparency and processes can be analyzed much more precisely; on the other hand, you will never miss the decisive moment again. Because with ArtiMinds LAR you can “rewind” at any time and retrace the chain of events that led to a problem.

ArtiMinds LAR already has extensive, preconfigured interfaces for industrial components, which greatly simplifies the connection of cameras and robots and the collection of data – without additional programming effort, e.g. via OPC UA interface.

This makes it possible to detect deviations, reduce scrap and increase component quality as well as the degree of digitalization and traceability in production.

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All Process Data at a Glance

Do you know what added value lies in your production data?

With the ArtiMinds LAR analysis software, we provide a tool with which you can gain valuable insights into your robot processes through transparent preparation and interpretation of production data to get the best out of this insights – from commissioning to running production.
Data acquisition takes place in the background, automatically and continuously. ArtiMinds LAR is able to collect a wide range of data from all available sensors, such as forces, energy consumption, hardware wear, etc., and is therefore the central monitoring point.

The software uses cloud technology, which gives you freedom during implementation: Data storage on-premises in the data center, as an edge device on the store floor or under the desk. Thanks to its web-based user interface, LAR still offers access from anywhere in all scenarios.

The added value of the LAR can also be used independently of robots. Brownfield systems can be retrofitted for this purpose with very little effort.

HARD FACTS

Hardware Requirements: IPC with SSD hard disk, locally in the cell, in your own data center or in the cloud
Operating System: Windows
Possible Network Protocols for data connection: OPC UA, Ethernet I/P, PROFINET

continuous process monitoring without additional effort

ONE Central Process Analyzing Tool | VARIOUS Applications

Use Case 1: Predictive Maintenance with Minimal Effort

Minimize downtimes, optimize maintenance – all with on-board resources

In a brownfield plant with over ten robots and several cameras for quality assurance, the customer wanted to reduce unplanned downtimes and optimize predictive maintenance.

The solution could be implemented with minimal intervention and without additional hardware integration: Using ArtiMinds LAR, the individual image recognition results of the cameras used could be automatically compared with the respective process step and saved accordingly.

Using an individual dashboard, the customer was able to monitor the live status of the process parameters, set limit values and identify trends in order to plan maintenance in a targeted manner. This allowed maintenance measures to be postponed to production-free time windows, avoiding unplanned downtimes.

Implementation took less than a day – a maximum efficiency gain without interfering with the existing system, costly conversions and installation of additional hardware.

Use Case 2: Cycle Time Optimization of a Welding Process

Gain transparency, optimize processes – without additional hardware

A customer from the automotive industry wanted to increase the efficiency of its welding processes. Two robots work simultaneously in a spot welding process. Their paths and therefore the movement times to the respective welding points vary. In order to find out which robot ideally takes on which subtasks, the first step was to determine the real waiting times and real cycle times of the two robots.

With ArtiMinds LAR, the real actual state of the system could be mapped digitally and automatically without integrating additional hardware. This created the data basis for precisely recording the cycle times of the individual robots for the first time.

With the collected and visualized data, the welding tasks could be redistributed to the two robots in the next step in order to achieve efficient utilization and optimal cycle times.

Process analysis without programming effort

Process monitoring force measurement assembly process

Use Case 3: Analyzing & Optimizing Force-controlled Assembly Processes

Identify causes of errors, increase cycle time & robustness – thanks to a data-driven approach

Many applications struggle to reconcile the various process data. This is also the case with a joining process in which components are assembled in the drive train of a car. After plant commissioning the process was not yet running optimally in terms of cycle time and robustness.

The task was to find out exactly when errors occur within the many process steps. In the next step, the sensor data associated with this point in time had to be determined and related to the problem.

Here, too, the already integrated hardware was used, a force-torque sensor that had been installed to prevent collisions. The existing sensor was quickly “repurposed” to use ArtiMind’s LAR to measure the forces occurring during the joining process and correlate them with individual robot movements.

Based on the necessary adjustments calculated by the LAR, the user can optimize the process, for example by adjusting parameters or reteaching individual teach points.

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Ana­lyze Process Data – Open Up Effi­ciency Potential

Objec­tive Data Analy­sis with ArtiMinds LAR – Process Mon­i­tor­ing Benefits:

Process Analy­sis, Opti­miza­tion, Pre­dic­tive Main­te­nance & Documentation

Con­tin­u­ous Process Mon­i­tor­ing – With­out Addi­tional Effort

Get the Full Know-how

All Process Data at a Glance

ONE Cen­tral Process Ana­lyz­ing Tool | VAR­I­OUS Applications

Use Case 1: Pre­dic­tive Main­te­nance with Min­i­mal Effort

Use Case 2: Cycle Time Opti­miza­tion of a Weld­ing Process

Use Case 3: Ana­lyz­ing & Opti­miz­ing Force-con­trolled Assem­bly Processes

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