Predictive Maintenance Services

Pushing the reliability envelope to the edge!​

In the realm of industrial operations, the pursuit of efficiency and reliability stands as an eternal quest. In this landscape, where the heartbeat of productivity resonates through intricate machinery and equipment, the advent of predictive maintenance emerges as a beacon of innovation. Arshon Technology, with its pioneering approach, stands at the forefront of this revolution, providing unparalleled solutions for predictive maintenance. Through a meticulous amalgamation of data gathering, scientific inquiry, and cutting-edge machine learning techniques, Arshon Technology transcends the traditional boundaries of maintenance, paving the way for a future defined by precision and foresight.

What is Predictive Maintenance (PdM)?

Predictive maintenance (PdM) is a data-driven approach to maintenance that leverages sensor, IoT technologies and analytics to assess the real-time health of an equipment. Unlike preventive maintenance with fixed schedules, PdM aims to predict when failures are likely to occur and schedule maintenance interventions accordingly. This proactive strategy optimizes resource allocation and minimizes downtime.

graph about the importance of predictive maintenance

When Does it Make Sense to Employ Predictive Maintenance Services?

  • In situations where the cost of downtime is very high.
  • When equipment isn’t designed to last a certain number of operating hours before replacement.
  • If a critical process relies on equipment, its failure will lead to significant material wastage.
  • When a single equipment failure could cause additional risks to people or catastrophic consequences.
  • When it’s not feasible or cost-effective to provide backup equipment.
  • When implementing data collection helps improve future equipment designs.
  • When equipment is very complex and normal or traditional maintenance techniques do not work
Predictive Maintenance helps avoiding leaking in our fluid passage system

What Techniques are Used in the Core of a Predictive Maintenance System?

Condition Monitoring

Sensors embedded within equipment continuously collect data on various parameters like vibration, temperature, or current draw. This data serves as a real-time window into the equipment’s health. Some companies are using condition monitoring only without any prediction system in place and they get benefits from live data provided by it.

Data Analysis

Advanced analytics techniques, often employing machine learning (ML), are used to identify patterns and trends in sensor data. Deviations from normal operating baselines can be indicative of emerging issues. Although not every collected data is good for a specific failure, selecting the right data is an art in the world of PdM.

Prognostics And Scheduling

ML algorithms are trained on historical data, including past equipment failures, to predict the probability and timeframe of future breakdowns. This allows for scheduling maintenance precisely when it’s needed, preventing catastrophic failures and maximizing equipment uptime.

Use case of PdM tools on a power generator

Benefits For Engineers

There are many advantages in employing PdM and it can significantly reduce downtime, cost of production and improve the financial index associated with the equipment purchased for the production. In some cases, ROI on equipment cost shows an improvement of up to 60%.

Improved Decision-Making

PdM provides data-driven insights into equipment health, enabling engineers to prioritize maintenance tasks and allocate resources effectively.

Reduced Downtime

By anticipating failures, PdM helps avoid unplanned outages, improving operational efficiency and production output.

Extended Equipment Lifespan

Early detection of anomalies allows for preventive measures to be taken, preventing minor issues from snowballing into larger problems and extending equipment life.

Enhanced Safety

PdM can identify safety hazards before they escalate, creating a safer work environment for personnel.

Implementation Considerations

  • Sensor selection: Choosing the right sensors for specific equipment and monitoring objectives is crucial for capturing meaningful data.
  • Data integration: Seamless integration of sensor data with analytics platforms is necessary for efficient data processing and visualization.
  • Expertise: Interpreting sensor data and building robust predictive models often requires collaboration between engineers and data scientists.

In conclusion, PdM empowers engineers with a proactive approach to equipment maintenance. By leveraging data analytics, PdM optimizes maintenance schedules, minimizes downtime, and extends equipment lifespan, ultimately contributing to a more efficient and reliable operation.

female engineer-PdM

Arshon Technology's role in PdM

At the core of our methodology lies a commitment to comprehensively understand the intricacies of industrial equipment. The journey begins with a meticulous process of data acquisition, where Arshon Technology’s experts engage in extensive interviews with technicians and engineers possessing firsthand experience with the targeted machinery. These interviews serve as a treasure trove of insights, delving into the nuances of failures and operational conditions encountered by the equipment. By tapping into the collective wisdom of these seasoned professionals, Arshon Technology garners a holistic understanding of the challenges at hand.

The dataset collected through these interviews serves as the foundation upon which our analytical talent thrives. Each data point encapsulates a narrative of failure, a tale of conditions pushed to the brink. However, amidst this sea of information, discerning patterns and extracting actionable insights pose a formidable challenge. Herein lies the domain of our expert team, tasked with unraveling the complexities embedded within the data.

Leak detector sensor

Armed with a deep understanding of the underlying science and engineering principles governing industrial equipment, our team embarks on a journey of discovery. Through rigorous analysis and empirical investigation, they strive to crack the root causes behind each failure. This quest for enlightenment exceeds ordinary problem-solving; it is a pursuit of knowledge, a quest to unravel the mysteries of machinery.

Air, Humidity and temperature sensor

Central to our approach is the development of mathematical models that encapsulate the behavior of the system under scrutiny. These models serve as a bridge between theory and practice, offering a lens through which failures can be simulated and understood. However, the road to modeling is often troubled with challenges, especially in the face of complex systems. In such instances, Arshon Technology cleverly pivots towards a data-centric approach, harnessing the power of machine learning to derive insights directly from the wealth of available data.

Machine learning techniques form the cornerstone of Arshon Technology’s predictive maintenance concept. By leveraging advanced algorithms and computational models, Arshon Technology transcends the limitations of traditional analysis, unlocking hidden patterns and correlations buried within the data. Through techniques such as supervised learning, unsupervised learning, and reinforcement learning, Our algorithms go through vast amounts of data, distilling actionable insights with unparalleled accuracy.

The culmination of our efforts manifests in the form of predictive maintenance solutions that redefine the paradigm of industrial upkeep. Armed with a comprehensive understanding of failure modes and operational conditions, Arshon Technology empowers organizations to preemptively address issues before they escalate into costly downtime or catastrophic failures. By embracing a proactive stance towards maintenance, businesses can optimize their operations, minimize disruptions, and unlock new realms of efficiency.

Vibration sensor

Beyond the realm of reactive maintenance lies a future illuminated by the promise of predictive analytics. In this future, machines are not merely tools of production; they are sentient entities, endowed with the ability to anticipate their own needs and mitigate potential risks. Our Technology stands as a harbinger of this future, a beacon of innovation guiding industries towards a new era of reliability and resilience.

Therefore, Arshon Technology represents a paradigm shift in the field of predictive maintenance. Through a meticulous blend of data gathering, scientific inquiry, and machine learning techniques, Arshon Technology transcends the limitations of traditional maintenance practices, offering unparalleled insights into the operational dynamics of industrial equipment. As industries march towards an era defined by precision and foresight, Arshon Technology stands as a steadfast ally, empowering organizations to navigate the complexities of modern industrial landscapes with confidence and conviction.

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