KeTech utilises expert data
11/10/2024
Australian company KeTech claims it has reshaped the way train operators and builders can manage their assets through smart remote condition monitoring (RCM).
KeTech has utilised its expert data understanding, and 25 years of experience in rail, to create an RCM system tailored to the rail industry: to prolong asset life, prevent failures and equipment malfunctions and present actionable insights for a seamless maintenance operation, centralised and in real time.
KeTech has engineered an RCM system, with intelligence at its core, through a blend of machine learning and asset expertise.
The company fine-tunes algorithms for each specific asset to align with its characteristics and the environment in which it sits, providing a holistic view and the complex interactions between assets.
Railway maintenance activity in Australia has an expected growth of nearly 20% over the coming decade. Rail maintenance activity is expected to increase each year over the forecast period for each state and territory.
The need to maintain a growing rail network and rising rail remediation works due to climate change-influenced events, such as floods, droughts, bushfires and coastal erosion, is driving investment in Australia’s rail transport networks. With this comes the addition of new assets to maintain.
Some of the assets on the railways are more than 100 years old, as are the methods used to inspect them. The rise of digitalisation has led to the development of ‘game-changing’ technology in the rail industry, with RCM being a prime example.
RCM has the potential to empower the rail industry to preemptively oversee the status and wellbeing of essential assets, anticipate potential malfunctions and refine maintenance approaches through the use of sensors to make maintenance works more efficient.
However, it is important to recognise that RCM alone is not enough. Many RCM systems rely on historical data alone to predict equipment failures, whereas KeTech takes it to the next level.
Sensors collect multiple pieces of data, sometimes duplicates, that are then stored in silos. This can quickly lead to redundant, outdated and trivial (ROT) information, which in rail can cause more harm than good if decisions are based on outdated information, particularly in the realms of maintenance.
Discussions around digitalisation often highlight the topic of big data and how it has potential to reshape the industry. However, the big data revolution may not live up to its promises if it is led by the premise of ‘the bigger, the better’. Therefore, collecting more data is not the answer. The first step towards it is through collecting better quality data.
A problem arises when monitoring systems collect data based on its subject alone. It creates a data silo that has no understanding of how the data collected may or may not be influenced by another asset. This violates the fundamental rule of understanding data: no data has meaning without context. Without context, this data is just noise. Without it, operations staff will not know if the data collected reflects a positive or negative outcome, leaving them uncertain about the appropriate actions to take. This can lead to longer resolution times as they navigate from one graphical user interface (GUI) to another.
The only way to find true context across all data is to combine RCM with engineering expertise and centralised intelligence to extract actionable insights in real time.
KeTech has been collaborating with train operators and train builders for 25 years, providing real-time journey information systems tailored to specific requirements through the use of intelligent data and real-time processing and presentation of information.
KeTech’s RCM is no different. It helps train operators and builders to target specific real-world problems.
Its teams collaborate with asset experts to define a set of rules for the pieces of equipment that are being monitored. Here it creates algorithms to separate normal variations and true threats, allowing the data to be interpreted in a meaningful way so both the root cause can be identified and a course of action taken.
Although relying on historical data alone is not the best way to predict potential failures, it does play an important role, but only in conjunction with artificial intelligence (AI), machine learning and context provided by the engineering expertise, to identify the most accurate trends, conduct real-time analysis and present meaningful information.
Using only historical data does not account for unforeseen failure modes, which is why engineering expertise is necessary to take the system to the next level. KeTech ensures that the rules for each asset are specifically tailored and fine-tuned to align with the characteristics of the asset and the environment in which it sits. Unlike other systems, KeTech’s RCM does not only provide information on singular assets, but also offers a holistic view of all assets on one centralised dashboard. It is also able to understand complex interactions between different components and provide usable information in real time.
Developed to the latest cybersecurity certification, KeTech’s system is created by data experts for the rail industry and unlocks the power of RCM.
KeTech combines years of expertise, intelligent data processing, real-time technology, AI and machine learning to provide a centralised end-to-end solution. Its system will move away from fix-on-fail to predict and prevent, allowing the operations team to be proactive and optimise its maintenance strategy.
