Monitoring machines and systems on a permanent basis is the essential prerequisite for condition-based maintenance. This strategy replaces conventional reactive or preventive maintenance, which is carried out at fixed intervals and components are checked or replaced as a preventive measure.
The condition of a component or system can be continuously monitored by electronically recording and digitizing suitable machine data and evaluating these data with professional accuracy, thus enabling a conclusion to be drawn about its functional efficiency. Examples include the use of sensors to record runtime, rotational speed, velocity, pressure, vibration, water parameters, humidity (room humidity and material humidity), as well as temperature (mean and/or ambient).
Any deviations occurring in the current production process compared to the historical trends of previous machine analyses (mainly due to component wear) can be remedied at an early stage during ongoing operation, or minor repairs can be performed, and shutdowns can be scheduled ahead of time. This helps avoid unplanned downtimes or total outages of machines and systems and the associated financial losses.
Condition monitoring is an essential prerequisite for predictive maintenance. IoT projects usually begin with the capture of operating data and measurements; predictive maintenance can only be implemented after the successful introduction phase. The table below shows the distinction between the two areas:
A prerequisite for trouble-free production in companies is the availability of machinery and equipment without downtimes. One important way of ensuring this is through predictive maintenance and the associated investment. Predictive maintenance represents a key step for manufacturing companies on their path towards digital transformation within the so-called Industry 4.0 and IoT.
A maintenance alert on the display of a machine tool does not mean that a defect has occurred in the machine or in an assembly. Rather, it indicates that the next scheduled maintenance is due. This strategy to maintenance is becoming outdated in the age of AI, machine learning, and Big Data. Predictive maintenance, as one of the core components of Industry 4.0, takes a anticipatory approach to keeping downtimes to a minimum and proactively service machinery and equipment. The method calculates forecasts and probabilities of occurrence based on measured values as well as operating and machinery data collected by sensors.
This means that in the future, maintenance and technical services will no longer be carried out at fixed, regular intervals; predictive maintenance will kick in at an earlier stage. For example, immediate action can be taken if wear is detected on a component. This avoids unnecessary maintenance, successively reduces downtimes, and significantly increases productive operation as a result.
In order to make dependable forecasts for predictive maintenance, it is necessary to collect, store and analyze a large amount of data. Big Data techniques and databases are used owing to the huge volumes of data. The readings and diagnostic data are then sent from the machines to the IoT platform via networks for further processing. Five steps are required to run predictive maintenance efficiently:
MicroNova’s concept involves a anticipatory and systematic approach. An example from production: we first analyze and classify operating equipment in a bottleneck analysis. The machines and systems are mapped according to their importance for the production process.
Using these analyses as a basis, MicroNova develops a concept for mapping the relevant machinery and equipment within the IoT framework. The prerequisite IoT services for collecting and processing the data are adapted to the characteristics of machines and systems, as well as to the operating technology. A combination of rule- and AI-based evaluations, based on the analyzed data, provides a constant flow of information about any production backlog and initiates timely action in the event of deviations. This enables companies to implement a continuous improvement process, gain transparency, and massively increase the uptime and availability of their production. At the same time, they minimize the risk of their machinery and equipment failing as a result of damage.
Predictive maintenance reduces unplanned machine downtime to a minimum, while optimizing the availability of operating equipment. Cost savings can be realized compared to routine or time-based preventive maintenance because tasks are only performed when they are actually necessary.
At a glance
- Integration of control & sensor data from the entire machine and plant fleet
- Permanent capture and monitoring of operating data
- Rule-based analysis and evaluation methods
- Significant increase in productivity due to extended machine runtimes
- Optimization of maintenance & repair as well as of the deployment of service staff in the field
- Elimination of unscheduled machine downtime
Companies can optimize their machine availability and production capacities using MicroNova’s services. Put the expertise of our specialists to work for you.
The Asset Tracking & Monitoring solution from amplía allows companies to track valuable assets anytime, anywhere – across wide-ranging process chains. The cloud-based solution is ready to use and is based on the OpenGate© IoT Framework. As such it offers a complete toolset for optimized asset tracking and monitoring.
Asset Tracking & Monitoring is primarily aimed at the logistics industry and includes ready-to-use devices, communication, and a pre-configured deployment of the OpenGate© platform. Companies can immediately and very easily start using it as part of a Proof of Concept (PoC) or even as extensive use case. Logistics and industrial firms involved in the transport of container systems, the transport and/or use of vehicles etc. can benefit from the solution in particular.
Logistics companies have usually already achieved a high level of productivity. Significant efficiency gains therefore require effective, innovative concepts that support new ideas and business models.
This is precisely what MicroNova and amplía make possible – through a powerful combination of engineering, planning and design skills as well as industry know-how.
- Web-based SaaS solution, accessible via an intuitive user interface
- Pinpointing and traceability
- Real-time detection of defined events (geofencing, unplanned stops, movement, etc.)
- Monitoring of additional parameters (position, shocks, inertia, temperature, etc. can be logged)
- Simple integration into existing systems
- Full remote control of the entire inventory (asset/device/communication)
- KPIs & custom dashboards and reports according to user type
- Sorting according to definable parameters
- Rule-based engine: create custom alarms and automatic action rules
Asset Tracking & Monitoring improves the tracking and precise geolocation of assets. Status monitoring and usage statistics improve the performance of the services and therefore the added value for companies. The ready-to-use solution is compatible with almost any tracker (based on amplía’s Southbound API). For optimum deployment, amplía recommends the use of VTrack (GPS and GSM tracking, mains or battery operation, CE-certified, IP68 and more; detects movements, shocks, temperatures, positions, and more).
SmartMetering is an integrated solution that is particularly suitable for measuring, analyzing and optimizing the consumption of electricity, water, or gas. Used in residential, industrial, or commercial environments, it can even perform smart metering functions in multi-apartment buildings, and so on, enabling a corresponding cost reduction through the optimization of energy consumption.
Monitoring and management of multi-utility infrastructures (water, gas, electricity, etc.)
SmartMetering is aimed at energy suppliers that need an infrastructure for collecting and processing data. The solution allows providers to control the management of participating assets centrally, from a single platform.
- Measurement, analysis, and optimization of energy consumption: Electricity, gas, water, etc.
- Flexible and adaptable solution
- Centralization of all energy consumption data in one platform
- Fast return on investment (RoI)
- All-in-one solution: Management of the entire infrastructure via one tool
- Secure role-based access and traceability
- Ready-to-use platform with simple deployment of end-user applications
- Support for adaptation and compliance with regulatory requirements
- Data visualization tools and customizable dashboards can be configured with the role-based system in OpenGate© via the associated responsive web platform
- MDM integration and APIs to interact with external systems
- Advanced data processing tools to implement new ad-hoc algorithms, aggregations, analyses, and more.
SmartMetering runs on the OpenGate© IoT-Platform. This means it benefits from the advantages offered by the complete set of tools for monitoring, managing, and remotely controlling assets and devices:
- Inventory management: Detection and automatic collection
- Location management (geolocation)
- Complete management of digital assets throughout their life cycle
- Monitoring of operational status
- Planning and execution of device or bulk operations and diagnostics
- Remote update and configuration of associated firmware
- Customizable automatic rules and alarms
- Integrated security management
- Support during service calls
Smart meters and other measuring devices exchange data securely, efficiently, and cost-effectively with SmartMetering, regardless of the communication technology used. This means that both wired and wireless data transfer is possible. The line paths themselves can be managed through OpenGate©. Alternatively it is possible to connect to an existing facility management system.
The following functions are available:
- Line inventory and life-cycle management
- Correlation of line inventory and device inventory
- Integration with operators’ managed connectivity platforms
- Automated user-defined reports to assess operator performance and service quality
- Support for eSIMs, legacy SIMs, and hybrid infrastructures in the same solution