Understanding Machine Diagnostics and Remote Monitoring

Managing machine health and ensuring sustainable asset performance is an important control objective in manufacturing environments. In both discreet and process-based manufacturing industries, net plant productivity, operational costs, and return on assets (ROA) depend on how well the available assets are utilized. This makes monitoring and diagnosing faults in all available assets a high priority for maintenance teams.

This article will cover what machine diagnostics are and how remote monitoring enables maintenance teams to track machine conditions, detect existing or impending faults, isolate the root cause, and initiate procedures to restore machine health.

What is Machine Diagnostic?

Machine diagnostics is an equipment control measure that focuses on tracking machine conditions and detecting faults that can lead to machine breakdown. The process includes fault detection, followed by root cause analysis. Machine diagnostics is critical in rotating machinery that operates round-the-clock and is essential for undisrupted production in a manufacturing environment.

Diagnostic data is collected with the help of various offline and online techniques, depending upon the scope of the maintenance. This data is then analyzed using methods like high-resolution spectral analysis, wavelet analysis or transform, Fast Fourier Transform (FFT), Wigner-Ville Distribution, waveform analysis, etc. The analyzed data is used to determine the root cause of faults and recommend corrective actions to the maintenance and operation teams.

For instance, a boom conveyor in a steel manufacturing plant can break down due to faults in motors, pulleys, or gearboxes. In a complex machine like this, it is difficult to determine what could have caused the breakdown and what kind of maintenance activity is required. With machine diagnostics, tri-axial vibration trends of the boom conveyor can be monitored to determine the root cause of machine breakdown.

If the machine’s health is deteriorating due to misalignment or bearing defects in the gearbox, then data-backed maintenance action can be carried out to restore machine function. (Read the full case here.)

What is Remote Monitoring?

To make machine diagnostics efficient and empower maintenance teams with real-time data, machine health can’t be measured manually at sporadic intervals. There needs to be a system of continuous monitoring with complete data accessibility across the connected enterprise. This is achievable through remote monitoring of plant assets, using IoT-enabled technologies.

Remote monitoring deploys one or multiple cloud-enabled solutions to remotely monitor machine conditions. Machine vibration data is collected in real time and relayed via the cloud to a centralized repository. Any anomalies in the machine vibrations are analyzed and compared with pre-defined specifications to determine whether a fault exists or building up within the equipment. The maintenance teams can get complete visibility of machine health from any time, anywhere; facilitating a planned shift to the predictive maintenance approach.

Remote monitoring services also help create safer working conditions for maintenance and production teams. Potentially hazardous conditions can be detected from a safe distance, without any manual intervention on the site. At the same time, all maintenance-related decisions can be guided by data-backed insights, leaving very little to chance.

Remote Condition Monitoring for Machine Diagnostics

The most preferred method of remote monitoring is Condition Based Monitoring (CBM) in manufacturing industries. Condition monitoring is a non-destructive and non-disruptive technique of monitoring plant equipment to determine its health or condition at any point in time. Remote condition monitoring determines the stability or possible deterioration of equipment condition. The rate of deterioration and where exactly is the equipment in its life cycle are also determined and conveyed to concerned stakeholders.

Commonly used condition monitoring techniques in manufacturing industries are:

Vibration Analysis: Measuring vibrations within a component, machinery, or machine group.

Oil Analysis: Analysing oil contamination, and machine wear to determine asset health.

Electrical Analysis: Analysing incoming power quality from the equipment, using motor current readings.

Ultrasonic Analysis: Detecting high-frequency sound waves through ultrasonic analysis.

Infrared Thermography: Detecting radiations and temperature changes using a thermal imager.

Of all these, vibration analysis is best suited for rotating equipment in process-based manufacturing environments. Abnormal machine vibrations are used to generate displacement, velocity, and acceleration maps, which in turn help in diagnosing the underlying causes of faults in the machine. Predictive analytical insights can be generated from this exercise which can support maintenance teams in planning focused repair and replacement events.

Conclusion:

In sum, machine diagnostics and remote monitoring are instrumental in managing asset performance and improving overall plant reliability. Real-time machine diagnostics using sophisticated, IoT-enabled techniques can give maintenance teams better visibility of asset conditions. With remote monitoring, machine diagnostics can be performed in a cost-efficient and secure manner, giving improved data accessibility across the organization. As machine faults are predictively diagnosed, corrective actions can be taken before the incidence of actual machine breakdown.

Infinite Uptime offers responsively designed machine diagnostics, remote condition monitoring, and predictive maintenance solutions in diverse industries such as Cement, Steel, Mining and Metals, Tire, Paper, Automotive, Chemicals, FMCG, Oil and Gas, and more. To understand how predictive maintenance applies to your process plant and can help in achieving plant reliability, explore the comprehensive solutions of Infinite Uptime.

FAQs

What is machine diagnostics in manufacturing?

Machine diagnostics in manufacturing refers to the process of monitoring and analyzing machine conditions to detect faults or potential breakdowns. It involves collecting data through techniques like vibration analysis or spectral analysis to pinpoint the root cause of issues affecting machine health.

How does machine diagnostics benefit manufacturing industries?

Machine diagnostics helps manufacturing industries by minimizing downtime through early fault detection and predictive maintenance. By identifying issues before they escalate, maintenance teams can plan proactive repairs, thereby optimizing asset performance and reducing operational costs.

What is remote monitoring ?

Remote monitoring involves continuously monitoring machine conditions in real time using IoT-enabled technologies. It allows maintenance teams to access data from anywhere, facilitating proactive maintenance decisions based on real-time insights. Remote monitoring enhances the effectiveness of machine diagnostics by ensuring comprehensive and continuous visibility of asset health.

What are the common techniques used in machine diagnostics?

Common techniques include vibration analysis, oil analysis, electrical analysis, ultrasonic analysis, and infrared thermography. These methods help in detecting anomalies such as vibrations, contamination levels, electrical irregularities, and temperature changes, which are indicative of potential machine faults.

What are the benefits of remote condition monitoring in manufacturing?

Remote condition monitoring offers benefits such as enhanced safety for maintenance teams, as potential hazards can be identified remotely. It also supports cost-efficient operations by enabling predictive maintenance strategies based on real-time data, thereby improving overall plant reliability and reducing unplanned downtime.

How can machine diagnostics and remote monitoring improve asset performance?

By continuously monitoring machine health and diagnosing faults early, these technologies help in maintaining optimal asset performance. Predictive maintenance driven by machine diagnostics and remote monitoring ensures that maintenance activities are proactive rather than reactive, leading to improved operational efficiency and extended equipment lifespan.

What industries can benefit from machine diagnostics and remote monitoring solutions?

Industries such as Cement, Steel, Mining and Metals, Tire, Paper, Automotive, Chemicals, FMCG, Oil and Gas, among others, can benefit significantly from these solutions. The ability to monitor critical equipment remotely and predictively address maintenance needs is crucial for enhancing productivity and reliability across diverse industrial sectors.

What are the key features of Infinite Uptime's machine diagnostics and remote monitoring solutions?

Key features include real-time data accessibility, predictive analytical insights, and responsive design tailored to meet the specific needs of process plants. Infinite Uptime’s solutions enable seamless integration of machine diagnostics and remote monitoring into existing operational frameworks, ensuring continuous improvement in asset performance and reliability.