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  • MPDV
  • Innovation & Knowledge
  • Future Concept MES 4.0

Future Concept MES 4.0

The MES of the future

IT support in production plays a key role for Integrated Industry (in Germany called Industry 4.0). In order to cover future production processes new standards and functions are required, which will especially affect MES applications. With MES 4.0 MPDV introduced a concept for the Manufacturing Execution System (MES) of the future.

Processes can be significantly improved and every day production routines can be tackled more efficiently - also in a decentralized production moving towards Industry 4.0.

MES 4.0 covers the following:

  • Interoperability
  • Flexibility
  • Management support
  • Horizontal integration
  • Online capability
  • Mobility
  • Integrative data management
  • Decentralization
  • Unified Shop Floor Connectivity
  • Big Data
  • Security by Design
  • Human Factor

Other forward-looking MES theories

  • Smart Factory Elements

    Smart Factory Elements

    A model for innovative production IT

    The challenges facing production have grown enormously. These challenges are leading to increased complexities like a high product diversity, short delivery times, fast process changes, smaller batch sizes up to batch size 1. In times of Industry 4.0, this is clearly a case for the Smart Factory - which in turn needs certain processes, functions and applications to meet the growing demands. This is a job for the Smart Factory Elements.

    The Smart Factory Elements make up a control loop.  According to this control loop, production is planned based on specifications from different sources and a plan is then implemented. The data collected is analyzed to make forecasts. Subsequently, the findings from analytics and prediction flow back into planning. The Industrial Internet of Things (IIoT) supports this cycle by collecting and providing data. It also provides real-time applications for the shop floor.

    >> Request white paper <<

    • Planning & Scheduling

      Planning & Scheduling contains typical tasks of the work preparation and planning: 

      • Orders and operations
      • Resources and employees
      • Quality assurance
      • Maintenance activities
      • Material and energy use
    • Execution

      Execution ensures that the specifications are implemented and documented efficiently and correctly:

      • Production control 
      • Monitoring process quality 
      • Process interlocking 
      • Online monitoring 
      • Early detection of deviations
    • Analytics

      Analytics uses statistical methods and innovative algorithms to prepare collected data for:

      • KPIs Performance and correlation analysis 
      • Root Cause Analysis 
      • Self service analytics 
      • Machine learning based on Big Data
    • Prediction

      Prediction enables the prediction of events based on executable models and artificial intelligence. 

      Typical applications are:

      • Predictive quality
      • Prediction of dates
      • Predictive Maintenance
      • Projection of material ranges
    • Industrial Internet of Things (IIoT)

      Industrial Internet of Things (IIoT) connects the operator and the real world of production with the digital image of the Smart Factory by means of networking and edge computing.

      The following applications are used:

      • Data transfer from IIoT sensors D
      • igital machine connections 
      • Manual data collection 
      • Providing information to the shop floor 
      • Flexible operator guidance
  • The Four-Stage-Model

    The Four-Stage-Model

    The future of manufacturing IT

    Today, MES systems are confronted with new tasks in addition to the daily in the production environment.
    Increasing digitalization offers required, basic technologies but also the applications must adhere to new challenges. Thus, the MES experts from MPDV have developed the four-stage-model "Smart Factory" and support production companies on their way to Industry 4.0.
     

    >> Request white paper <<

    Stage 1
    Transparent factory

    The first stage on your way to the Smart Factory is the transparent factory. That means, that the responsible production employees know at all times what is happening in the shop floor. 

    Stage 2
    Reactive factory

    Stage 2 is the reactive factory. Collected data is compressed and properly visualized in order to quickly recognize the impact if changes are introduced to the shop floor. This is essential in order to react quickly with targeted measures to interruptions in the shop floor. 

    Stage 3
    Self-Regulating Factory

    The third stage is the self-regulating factory, where you can develop local standards for production processes based on achieved reactivity.

    Stage 4
    Functionally Networked Factory

    And finally, you arrive at the fourth stage the functionally networked factory. This final step considers associated processes and systems like PLM, energy and site management.

  • Beyond MES

    Beyond MES

    Our vision for Industry 4.0 and Smart Factory

    From the monolith to the ecosystem. From rigid applications to flexible mApps. From vendor-bound to vendor-neutral. From isolated solutions to interoperability. This is just a small excerpt of what manufacturing IT will have to be able to do in the future. With MES HYDRA X, APS FEDRA and the Manufacturing Integration Platform (MIP), we are setting these trends and not just following them. Because in our vision of Industry 4.0, manufacturing IT goes beyond the required minimum standard and is so flexible that it can easily handle new requirements.

Smart Factory Elements

Smart Factory Elements

A model for innovative production IT

The challenges facing production have grown enormously. These challenges are leading to increased complexities like a high product diversity, short delivery times, fast process changes, smaller batch sizes up to batch size 1. In times of Industry 4.0, this is clearly a case for the Smart Factory - which in turn needs certain processes, functions and applications to meet the growing demands. This is a job for the Smart Factory Elements.

The Smart Factory Elements make up a control loop.  According to this control loop, production is planned based on specifications from different sources and a plan is then implemented. The data collected is analyzed to make forecasts. Subsequently, the findings from analytics and prediction flow back into planning. The Industrial Internet of Things (IIoT) supports this cycle by collecting and providing data. It also provides real-time applications for the shop floor.

>> Request white paper <<

  • Planning & Scheduling

    Planning & Scheduling contains typical tasks of the work preparation and planning: 

    • Orders and operations
    • Resources and employees
    • Quality assurance
    • Maintenance activities
    • Material and energy use
  • Execution

    Execution ensures that the specifications are implemented and documented efficiently and correctly:

    • Production control 
    • Monitoring process quality 
    • Process interlocking 
    • Online monitoring 
    • Early detection of deviations
  • Analytics

    Analytics uses statistical methods and innovative algorithms to prepare collected data for:

    • KPIs Performance and correlation analysis 
    • Root Cause Analysis 
    • Self service analytics 
    • Machine learning based on Big Data
  • Prediction

    Prediction enables the prediction of events based on executable models and artificial intelligence. 

    Typical applications are:

    • Predictive quality
    • Prediction of dates
    • Predictive Maintenance
    • Projection of material ranges
  • Industrial Internet of Things (IIoT)

    Industrial Internet of Things (IIoT) connects the operator and the real world of production with the digital image of the Smart Factory by means of networking and edge computing.

    The following applications are used:

    • Data transfer from IIoT sensors D
    • igital machine connections 
    • Manual data collection 
    • Providing information to the shop floor 
    • Flexible operator guidance
The Four-Stage-Model

The Four-Stage-Model

The future of manufacturing IT

Today, MES systems are confronted with new tasks in addition to the daily in the production environment.
Increasing digitalization offers required, basic technologies but also the applications must adhere to new challenges. Thus, the MES experts from MPDV have developed the four-stage-model "Smart Factory" and support production companies on their way to Industry 4.0.
 

>> Request white paper <<

Stage 1
Transparent factory

The first stage on your way to the Smart Factory is the transparent factory. That means, that the responsible production employees know at all times what is happening in the shop floor. 

Stage 2
Reactive factory

Stage 2 is the reactive factory. Collected data is compressed and properly visualized in order to quickly recognize the impact if changes are introduced to the shop floor. This is essential in order to react quickly with targeted measures to interruptions in the shop floor. 

Stage 3
Self-Regulating Factory

The third stage is the self-regulating factory, where you can develop local standards for production processes based on achieved reactivity.

Stage 4
Functionally Networked Factory

And finally, you arrive at the fourth stage the functionally networked factory. This final step considers associated processes and systems like PLM, energy and site management.

Beyond MES

Beyond MES

Our vision for Industry 4.0 and Smart Factory

From the monolith to the ecosystem. From rigid applications to flexible mApps. From vendor-bound to vendor-neutral. From isolated solutions to interoperability. This is just a small excerpt of what manufacturing IT will have to be able to do in the future. With MES HYDRA X, APS FEDRA and the Manufacturing Integration Platform (MIP), we are setting these trends and not just following them. Because in our vision of Industry 4.0, manufacturing IT goes beyond the required minimum standard and is so flexible that it can easily handle new requirements.

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