Predictive Maintenance and Fleet Management

More reliability, less down time

Industry 4.0

More reliability, less down time

Today, many machines possess a high quantity of sensors, which continuously collect data. Meanwhile reliability data of many components are made available by their manufacturer. Data, produced within service can be processed with Big Data Methods and Predictive Analytics. Later this data can be analyzed within Predictive Maintenance.

Industry 4.0 uses this data to detect irregularities within service and to preventively find timeframes for maintenance. Predictive Maintenance is a crucial step in order to achieve a complete supply chain management.

Your benefits

  • Demand-based planning of maintenance windows for your customers

  • Reliability for your fleet management as a service provider

  • Reduce unscheduled outages

  • Avoid further damage

  • Decrease energy usage

  • Increase system reliability

  • Use your sensor data for process automation

  • Online overview on manufacturing data and machine condition

Increase efficiency and avoid outages

Decrease outages and optimize machine workloads

As a service provider, you can operate your fleet management more flexible using Predictive Maintenance. Furthermore you proactively provide your customer with maintenance schedules, spare parts or new devices. By applying Predictive Maintenance to your machines  you reduce unscheduled outages as well as any financial damage caused by this. In addition, Predictive Maintenance combines a smart sales management with an efficient supply chain management, as you know in advance which part is needed where. On the long run, you reduce warehouse costs by taking complex connections into account, when ordering new machines or spare parts.

Alltogether, Industry 4.0 gives you the opportunity to systematically assess all costs. This provides benefits for both large, as well as mid-tier corporations. We are also experienced in introducing mid-tier companies to data-driven processes.

According to a study by the Business application Research Center (BARC) in Würzburg, Big Data initiatives often exceed expectations when it comes to strategic and operative decision making.

Predictive Maintenance

We transfer all data from your machine’s sensors into a self-learning system. Based on weighted input factors we calculate probabilities of outages. To achieve this, current machine parameters are compared to specifications and historical data. Finally, we develop a Predictive Maintenance Model, which quickly and reliably detects irregularities.

Fleet management

Since the development of CAN bus, it is common procedure to equip commercial vehicle fleets with ISDN-modems and maintenance modules. This enables your fleet management to carry out remote diagnoses in case of maintenance or repair. Today, it is beneficial to equip one’s fleet with LTE or GPRS, to permanently receive automized assessments of the vehicle’s condition. Thus, you can act early and dispatch a repair. The goal is, to identify future problems at an early stage, in order to have enough time to react. Meanwhile, you decrease unnecessary maintenance costs.

Predictive Maintenance thus allows you, to reduce maintenance windows as well as the costs for spare parts. In other words, it allows you to work more efficiently. Vehicle fleets and machine fleets can thus be monitored using predictive algorithms and the internet.

In case you already dispose of a large number of sensors within your machines or your supply chains, we offer consulting and implementation services with our products Analytics and Data Stratosphere. We provide you with efficient tools for process optimation and reduction of outages. Already established processes like LEAN and SixSigma are fully automized. Furthermore, you detect variations in production and service after a training period. In the end, you receive a gapless supply chain management.