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Big Data and Predictive Maintenance
Technology Category
- Analytics & Modeling - Big Data Analytics
- Automation & Control - Programmable Logic Controllers (PLC)
- Cybersecurity & Privacy - Endpoint Security
- Cybersecurity & Privacy - Identity & Authentication Management
- Cybersecurity & Privacy - Intrusion Detection
- Cybersecurity & Privacy - Network Security
- Infrastructure as a Service (IaaS) - Cloud Computing
- Infrastructure as a Service (IaaS) - Cloud Storage Services
- Networks & Connectivity - Gateways
Applicable Functions
- Maintenance
Use Cases
- Predictive Maintenance
The Challenge
Predictive maintenance refers to techniques that help determine the condition of in-service equipment in order to predict and/or optimize when maintenance should be performed. Predictive maintenance is one of the most important benefits of the Industry 4.0 revolution.
The Customer
the Roth Group
About The Customer
Founded in 1984 the Roth Group develops individual automation solutions for its customers
from various industries. With its companies Roth Steuerungstechnik GmbH, Roth & Schoder
GmbH and Roth Sondermaschinen GmbH the corporate group covers the entire auto
The Solution
By consolidating the machine data from many different locations in a central place, the optimization of machines and production processes is possible. Thanks to a remote maintenance solution from the Roth Group including components from Endian and the cloud solutions from Amazon Web Services, customers in any industry can benefit today from the advantages of digitization.
Related Case Studies.
Case Study
Remote Monitoring & Predictive Maintenance App for a Solar Energy System
The maintenance & tracking of various modules was an overhead for the customer due to the huge labor costs involved. Being an advanced solar solutions provider, they wanted to ensure early detection of issues and provide the best-in-class customer experience. Hence they wanted to automate the whole process.
Case Study
Predictive Maintenance for Industrial Chillers
For global leaders in the industrial chiller manufacturing, reliability of the entire production process is of the utmost importance. Chillers are refrigeration systems that produce ice water to provide cooling for a process or industrial application. One of those leaders sought a way to respond to asset performance issues, even before they occur. The intelligence to guarantee maximum reliability of cooling devices is embedded (pre-alarming). A pre-alarming phase means that the cooling device still works, but symptoms may appear, telling manufacturers that a failure is likely to occur in the near future. Chillers who are not internet connected at that moment, provide little insight in this pre-alarming phase.
Case Study
Aircraft Predictive Maintenance and Workflow Optimization
First, aircraft manufacturer have trouble monitoring the health of aircraft systems with health prognostics and deliver predictive maintenance insights. Second, aircraft manufacturer wants a solution that can provide an in-context advisory and align job assignments to match technician experience and expertise.
Case Study
Integral Plant Maintenance
Mercedes-Benz and his partner GAZ chose Siemens to be its maintenance partner at a new engine plant in Yaroslavl, Russia. The new plant offers a capacity to manufacture diesel engines for the Russian market, for locally produced Sprinter Classic. In addition to engines for the local market, the Yaroslavl plant will also produce spare parts. Mercedes-Benz Russia and his partner needed a service partner in order to ensure the operation of these lines in a maintenance partnership arrangement. The challenges included coordinating the entire maintenance management operation, in particular inspections, corrective and predictive maintenance activities, and the optimizing spare parts management. Siemens developed a customized maintenance solution that includes all electronic and mechanical maintenance activities (Integral Plant Maintenance).
Case Study
Asset Management and Predictive Maintenance
The customer prides itself on excellent engineering and customer centric philosophy, allowing its customer’s minds to be at ease and not worry about machine failure. They can easily deliver the excellent maintenance services to their customers, but there are some processes that can be automated to deliver less downtime for the customer and more efficient maintenance schedules.
