Download PDF

Fleet Manager for Machine Tools is designed for MindSphere, the industrial IoT ecosystem from Siemens. The MindApp Fleet Manager provides an overview of the connected assets configured in MindSphere and the ability to quickly search for relevant assets based on various criteria.

It is a single app for:
- Displaying and managing your global machine fleet
- Combining critical machine data to get sound analytical data
- Developing your own digital service offering
- Instant and easy connection of SINUMERIK

more...
  • SUPPLIER
  • Digital Factory (Siemens)
    The Digital Factory (DF) Division offers a comprehensive portfolio of seamlessly integrated hardware, software and technology-based services in order to support manufacturing companies worldwide in enhancing the flexibility and efficiency of their manufacturing processes and reducing the time to market of their products. Siemens is the largest engineering company in Europe. With their positioning along the electrification value chain, Siemens has knowhow that extends from power generation to power transmission, power distribution and smart grid to the efficient application of electrical energy.
  • SNAPSHOT
  • Platform as a Service
    Open website
  • Application Industries
  • Chemicals
    Equipment & Machinery
  • Application Functions
  • Maintenance
  • USE CASES
  • Machine Condition Monitoring
    Early predictions on equipment malfunctions and service maintenance can be automatically scheduled ahead of an actual part failure by installing sensors inside equipment to monitor and send reports.Machine condition monitoring is used to determine the condition of a machine with the intent to forecast mechanical wear and failure. The predicted data provides health information about the machine and helps to predict machinery failure. The monitoring equipment tracks changes in temperature, vibration, and output of machines in order to detect an imbalance, corrosion, wear, misalignment, sediment build-up, or poorly lubricated parts.Condition monitoring has gained importance in line with increased company focus on productivity and asset utilization. 
    Process Control & Optimization (PCO)
    Process Control and Optimization (PCO) is the discipline of adjusting a process to maintain or optimize a specified set of parameters without violating process constraints.The PCO market is being driven by rising demand for energy efficient production processes, safety and security concerns, and the development of IoT systems that can reliably predict process deviations.Fundamentally, there are three parameters that can be adjusted to affect optimal performance:- Equipment optimizationThe first step is to verify that the existing equipment is being used to its fullest advantage by examining operating data to identify equipment bottlenecks.- Operating proceduresOperating procedures may vary widely from person-to-person or from shift-to-shift. Automation of the plant can help significantly. But automation will be of no help if the operators take control and run the plant in manual.- Control optimizationIn a typical processing plant, such as a chemical plant or oil refinery, there are hundreds or even thousands of control loops. Each control loop is responsible for controlling one part of the process, such as maintaining a temperature, level, or flow. If the control loop is not properly designed and tuned, the process runs below its optimum. The process will be more expensive to operate, and equipment will wear out prematurely. For each control loop to run optimally, identification of sensor, valve, and tuning problems is important. It has been well documented that over 35% of control loops typically have problems. The process of continuously monitoring and optimizing the entire plant is sometimes called performance supervision.
    Factory Operations Visibility & Intelligence
    Visualizing factory operations data is a challenge for many manufacturers today. One of the IIoT initiatives some manufacturers are pursuing today is providing real-time visibility in factory operations and the health of machines. The goal is to improve manufacturing efficiency. The challenge is in combining and correlating diverse data sources that greatly vary in nature, origin, and life cycle.Factory Operations Visibility and Intelligence (FOVI) is designed to collect sensor data generated on the factory floor, production-equipment logs, production plans and statistics, operator information, and to integrate all this and other related information in the cloud. In this way, it can be used to bring visibility to production facilities, analyze and predict outcomes, and support better decisions for improvements.  
© 2020 IoT ONE