KMO Applications with external partner supports different industries
Heavy Machinery
KMO Applications works with a number of Heavy Machinery customers. We help to reduce maintenance and repair cost by analyzing the technical condition of rolling stock in a single data center. Costs of downtime in the Heavy Machinery industry are extremely high and it is very important to ensure that production equipment is reliable and efficient.
Our solution has helped:
Increase efficiently of manufacturing process
Optimize planned maintenance and extend asset life
Increase the productivity of technical services
KMO Applications with external partner are providing predictive maintenance solutions for machine building enterprise. Due to the constructed mathematical model, we were able to predict and prevent the shutdown of several compressors in time. This allowed us to avoid unplanned costs and increase the credit of customer confidence.
Industries
Railway
KMO Applications offers the specialize solution for the railway industry for monitoring and predicting the technical condition of equipment. We supply innovative, individual decisions which can help you to achieve:
Reducing the time for the diagnosis of components and repairing process
Improved the operational reliability of locomotives
Reduced chance of breakdowns during operation
KMO Applications with external partner are providing predictive maintenance solutions for the one of the largest suburban railway carrier in Europe. The solution allowed the company to reduce repair costs and line failure penalties
Context
Solution
Current status
Trains departed with unresolved defects

No opportunity to check the repair results
Centralized collection of information on the technical condition of rolling stock in a single data center

Automatically determined the scope of over-cycle repairs

Automated the checklist of train acceptance from repair
The system is being optimized in the area of works assignment within the framework of maintenance, repair and quality control of comments elimination identified by the system

Business process refinement of interaction between the master receiver and the service employee
KMO Applications with external partner supports 4 industries
Industries
Automotive
We work with companies with the Automotive industry to improve the quality of operations and work efficiency. KMO provides range of tools which allow automotive companies to:

Increase fleet performance

Reducing the number of downtime, unplanned repairs of transport units and fuel costs

Monitoring the technical condition
KMO Applications with external partner are providing predictive maintenance solutions for the one of the automotive companies. The solution allowed companies to reduce repair costs and line failure penalties
Industries
Automotive
KMO Applications offers the solution for chemical industry which was created for maintain and predict technical condition of assets. Our solution has helped:
Monitor technical processes in real time
Developing models of equipment
Reduce the number of maintenance staff
KMO Applications with external partner are providing predictive maintenance solutions for the Chemical industry. The solution allowed the company to optimization of the movement process using the example of an RTG crane on a container site and to found anomalies in the pipe.
22%
20%
reduction in the number of operations
reduction in operation
time
human risk reduction
Projects
One of the largest suburban railway carrier in Europe
Calculation of temperatures of the winding, active steel and hot air of the stator of a turbo generator
On the generated dataset, the model of physical processes calculated the "output" temperatures. Visually, the temperature distribution inside the stator package of the turbo generator is shown in the figures
Hybrid model of the turbo generator TZFP-220-2UZ
Calculation of the reliability of the oil pump
«ased on the identified anomalies in the operation of the oil pump, the threshold of the total error was revealed and the reliability indicator was calculated over the entire interval of the data provided (2015-2017)
An increase in indicator values indicates a decrease in pump reliability - the development of malfunctions.
Context
Solution
A large number of unplanned repairs and failures
Manual data processing
The platform:
Automated and centralized data processing
Automated the appointment of super-cycle work in a depot
Reduced time costs for diagnosis
Improved the operational reliability of locomotives
Service company
We automated: locomotives diagnostics in the depot, violations of operating modes search and super-cycle work appointment.
>50 000
hours have processed daily by our platform
>50
mathematical models
>1 000
algorithms are used to search for precautionary states
Large power generating company
Waste heat recovery boiler
Large power generating company
Turbine generator
Industrial equipment manufacturer
Compressor
Locomotive service maintenance
Electric traction motor
Proven Models
Model objectives:
An analysis of historical boiler operation data, determination of relevant parameters that characterize boiler condition, detection of abnormalities and defects in waste heat boiler operation
Results:
147 abnormal deviations from balanced condition have been detected, out of which 18 were stop-and-start type
Model objectives:
Detection of undisclosed compressor shutdowns that were unknown to the specialists
Results:
21 out of 24 undisclosed compressor shutdowns have been detected
Pre-failure conditions have been determined for 15 undisclosed and 12 disclosed shutdowns
Shutdown of two compressors has been predicted
Model tasks:
Prediction and detection of electric traction motor failures
Results:
Electric motor failures have been predicted
Abnormal conditions in the operation of the electric traction motor have been identified
Model tasks:
Analysis of historical turbine generator operation data, identification of deterioration trends for structural parts, and interpretation of possible failure causes
Results:
Over a period of 18 months, systematic occurrences of excessively high temperature in the stator winding have been identified, which caused further breakdown
Made on
Tilda