The innovative approach for higher efficiency and reduced downtime

In order to stay competitive, airports and airlines as well as parcel service providers need to effectively manage their mission critical assets. They need to ensure that their systems – both hardware and software – are available at all times. Unplanned downtime and emergency maintenance are the major challenges. Failures and downtimes affect the available capacity of the systems and therefore need to be predicted and eliminated.
Current maintenance strategies, such as usage-based or time-based maintenance, are limited. Condition data collection and analysis offer opportunities for improvement. Streamlining maintenance is crucial for achieving high levels of system reliability, increasing efficiency, productivity, competitiveness, and lowering cost.

The Service 4.0 program

To meet the demand for digitally supported maintenance, Siemens established the Service 4.0 program, which makes full use of the progress in systems technology in an increasingly digitalized industry. Service 4.0 increases the productivity, availability and reliability of assets and systems through targeted system data gathering, evaluation and failure prediction.

Condition Monitoring Solutions form the basis for Predictive Analytics. Data processing with predictive algorithms provides end-of-life information of components. Service providers benefit from predictive maintenance planning and execution with just-in-time equipment servicing, balanced workload for the service team and the optimized utilization of spare parts, as well as stock management. These key highlights are part of a Lean Service Approach that enable higher equipment reliability and improved system availability.

Siemens‘ Service 4.0 program leads to improved productivity, greater flexibility and agility of the service team as well as longer asset lifetime and cost reduction.

Benefits

  • Reliability and availability: Operational downtime is significantly reduced or eliminated, and operational risk is minimized through predictive analytics and transparency of the system condition
  • Efficiency: By planning maintenance activities according to the assets’ conditions, unnecessary work is reduced and/or eliminated
  • Effectiveness: Service 4.0 enables predictive maintenance, material and resource planning as well as focused execution of maintenance activities in an optimized manner
  • Asset optimization: The useful lifetime of assets is extended through data-driven root-cause analysis and equipment optimization
  • Safety: Workplace safety is improved by reducing maintenance activities that have special safety requirements, such as working in heights