With Artificial intelligence (AI) you are also smart beforehand. Mitsubishi Electric puts his corporate AI now also for Predictive Maintenance in machines, systems and robots. Thanks to real-time analysis technology for recorded operating data, maintenance reaches a new level. Maintenance needs are identified early, before they arise. In this way, necessary measures can be planned in advance and reduced to a minimum. You can find an overview of the condition monitoring solutions below:

Mistubishi Electric Predictive Maintenance



Trends in Automotive - Data means Energy

Sep 21.09.2023, XNUMX | The automotive industry is the innovation driver for future-oriented manufacturing processes. Quick adjustments to the latest developments are particularly necessary in this industry in order to stay at the top. The integration of Real-time data generation and management in all vehicle and parts production processes helps to overcome market and supply chain challenges. Lucas Majewski, Global Director of Automotive/EV Industry, Factory Automation, at Mitsubishi Electric, explains this in detail in the videocast "Trends in Automotive - Data means Energy".

Conventional automotive production is being tested by the combined impact of a changing regulatory landscape, changing customer demands and ongoing supply chain issues. However, the industry has so far proven that it is agile and therefore resilient. It is one of the most automated areas and has grown significantly in recent decades digital technologies invested.

The automotive industry's value chain can therefore benefit from its pioneering role, not least thanks to its forward-looking approach and its existing infrastructures. The Automobile production is already state-of-the-art automated. she has Robotsupported production lines and can incorporate additional innovative digital technologies.

In improving performance, flexibility and sustainability Real-time data the key, says Lucas Majewski, highlighting the potential to improve almost all aspects of automobile production. The actors can gain insights into machines and production systems. This improves your decisions and allows you to react automatically with predictive maintenance and process optimization.

With real-time data and predictive analytics, companies can gain insights into energy consumption and CO2-Footprint determine. This helps to implement measures to reduce emissions and electricity costs. It also leads to more efficient and environmentally friendly operations.

The full interview with Lucas Majewski


Predictive maintenance with artificial intelligence for robots

March 02.03.2020, XNUMX | Mitsubishi Electric's AI technology is called type of maize. It can be easily implemented on the Melfa robot using the Melfa Smartplus add-on card. For predictive maintenance, Maisart takes over the pre-processing of the data stream Sensors. The artificial intelligence implemented on the Melfa Smartplus add-on card extends the CR800 controller for the Melfa robot the FR series to provide computing power and other functions.

Handling robots for efficient forklift add-on parts production

Based on motor characteristics, current and power consumption as well as vibrations determines the AI ua, whether attached to Transmission, Servomotor or Warehouse Sign off maintenance. This can be due to wear of lubricating grease, toothing, bearings or damage. Corresponding recommendations for maintenance are issued in plain text and enable efficient planning. Downtimes are prevented, maintenance costs are reduced.

Difference between predictive maintenance and preventive maintenance

"With the terms Preventive Maintenance or Predictive Maintenance there is often a lack of selectivity, ”says Michael Finke, Product Manager for Robots at Mitsubishi Electric. “As predictive maintenance, predictive maintenance is based on the live evaluation of data recorded in the field and evaluated in real time. It offers corresponding diagnoses and forecasts for the health status of individual components of the robot using AI. preventive Maintenance As preventive maintenance, it means intelligent, computer-aided functionality that is based on the respective robot program. "

With preventive maintenance, the analyzes are carried out in advance in the programming and programming uniform for all Mitsubishi Electric robots simulation environment RT Toolbox3. This can be done online directly with the Robot or without robots in the simulation. After completion of the Robot programming wear and load simulations are carried out and corresponding periods for maintenance are calculated.

Programming robots | software and controls

When combined, both maintenance concepts of the Smartplus functional solution Preventive and Predictive Maintenance, by definition, enable machine downtimes to be minimized, among other things through batch processing of the maintenance data from several robots for entire production systems - in the spirit of Industry 4.0.

Predictive maintenance, time-sensitive and cobots

02.10.2019 | Mitsubishi Electric presents itself as Your solution partner for smart manufacturing. The company will be showing its latest range of products and technologies at the stand Automationthat give users a competitive edge. This allows them, for example, to optimize their maintenance and avoid system failures.

Frequency converter innovations: decentralized, networked with app and much more.

Solutions presented include predictive maintenance, time-sensitive networking (TSN) and increasingly collaborative robotics and Cobots – all to improve production. The help in dealing with large amounts of data by Edge Computing will be a priority alongside the wider application of AI to improve machine and system intelligence.

The realization and application of these technologies is achieved through cooperation with partners from the eF @ ctory Alliance supports. Another area of ​​focus is mechanical engineering, with several product developments offering improvements in performance and integration.

Predictive maintenance for robotics with machine diagnostics

13.03.2019/XNUMX/XNUMX | As a solution partner for Smart manufacturing Mitsubishi Electric presents applications for the areas Engineering, manufacturing and maintenance. New solutions for predictive maintenance play a central role. Examples are the “Melfa Smartplus” for all robots in the FR series and the HMI devices with integrated machine diagnosis “GOT Drive”. Because this allows the condition of components to be determined at an early stage Robotic can be seen, costly failures can be avoided.

The new functional solution Melfa smartplus for the FR series is an embeddable add-on card for highly specialized, intelligent functions, including predictive maintenance. Characteristic values ​​from the servomotors can be called up directly in the CR800 controller and analyzed for imminent damage or wear. The corresponding service recommendations are issued in plain text and enable optimized maintenance as required. Other Smartplus functions include higher positioning accuracy through temperature compensation and the coordination of additional axes (spline tracking).

For value retention and cost savings through predictive maintenance, the automation specialist also has the GOT Drive function developed for machine diagnostics. GOT Drive+ frequency converter compares the frequency and torque curve with a reference range and outputs maintenance requirements directly on the operator panel.

Lifetime monitoring of the capacitors is integrated. GOT Drive + Servo records friction and vibration values, compares them to the user-defined specification and reports the need for maintenance or cleaning. Both condition monitoring functions of the machine can also be accessed from a cell phone or tablet with GOT Mobile.

Safety brake protects Robco robot kit

Further highlights are an antistatic robot for the Electronicsproduction and a high-speed delta robot with Mitsubishi Electric steering. In addition, with eF @ ctory partners realized vision applications and product solutions for industry 4.0 and the intelligent manufacturing of the future.

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