Predictive Maintenance

Always stay ahead that decisive step using artificial intelligence.

The “Why”

The goal of Predictive Maintenance is to prevent downtimes, reduce unplanned breakdowns and faults or predict the optimal maintenance time in order to increase the productivity and performance of machines and ultimately reduce the overall costs. Using artificial intelligence in the condition monitoring of Big Data and in the analysis of real-time data is the step into the future.  

Your Benefits

– 20% reduction in downtime 

– 15% less disruption and downtime 

Symbolisches Icon für Produktivitäten

+23% higher productivity  

– 30% fewer maintenance costs 


The first step is to make machines and process data available permanently to the AI to enable an automatic analysis and evaluation of the data. The AI models used – either “edge” on any machine or in the production process in general – analyze the data in real-time to calculate the probability of certain results and occurring correlations. This enables an early intervention in the production process.  

Next Level of Predictive Maintenance

Predictive Maintenance requires data from sensors, which might not always be available. Thus, future malfunctions or failures are not apparent through data. That’s why we also rely on the symbiotic approach. The expert worker with his knowledge about the production plant generates additional data via an HCI (Human-Computer Interface) and enriches the AI models to get even better results.  

Business Value

  • Reduce downtimes 
  • Reduce malfunctions and failures
  • Increase the service life of machines and systems
  • Calculate optimal maintenance time using AI 
  • Improve operation, maintenance and machine planning
  • Improved productivity and performance of machines 

Request AI Experts

We look forward to your questions on the use of artificial intelligence.

Industries & Fields of Application

Symbolbild für Automotive - ein KI-Einsatzgebiet


#predictive maintenance #manufacturing #deliverers

Machine and process data analysis directly on the production line in the area of transmission manufacturing to reduce downtime, optimize set-up processes, and predict end-of-line test results.  


#condition monitoring #manufacturing #medical supply

Analysis using image recognition to detect malfunctions and failures at an early stage and improve operation planning, thereby increasing productivity and throughput on the entire production line.  

Rail transport 

#predictive quality #lifetime #logistics #expedition 

Analysis from Big Data to predict the life cycle of vehicle and rail components in order to avoid failures directly during operation and to enable early replacement of components.  

Solution. Through Composite AI.

We use AI models which support data generation or analyze data in real time and deliver the corresponding results in order to derive measures at an early stage. The solution analyzes time series’, recognizes patterns, and interpretes images or log files. In addition, Natural Language Understanding (NLU) analyzes the input via the HCI.

Skill 08
AIDataInformation Retrieval

Human Computer Interaction

Enable interaction between humans & computers in a satisfying way that likens human-to-human interaction as, for instance, in open dialogues.

Skill 06
AIDataInformation Retrieval

Predictive Maintainance

Always be in the know which parts need your attention next, e.g. replacing. Don’t sweat over it and get the cumbersome details done by this AI model.

Skill 03
AIDataImage Recognition

AI Image Classification

Automatically classify images according to a certain scheme in the blink of an eye. Use this skill to make time for the tasks that really matter to you.

AIOS – The “How”

Implement the use case 5-10x faster with AIOS.

Leftshift One’s AIOS (AI Operating System) software enables end-to-end Predictive Maintenance to be deployed 5 to 10 times faster. The system uses the necessary pre-configured AI models in the internal marketplace to perform real-time condition monitoring and data analysis. The software aims to monitor the production process 24/7 and to provide the necessary insights.   

How To Start A Project