Industrial Maintenance

How Accelerometers and Vibration Sensors Work

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A vibration sensor is a device that converts mechanical motion into an electrical signal. This signal is used to measure the amplitude, frequency, and acceleration of vibrations occurring in operating equipment. They are key in predictive monitoring, as they allow fault modes to be identified before they occur.

The accelerometer is the most common type of vibration sensor. It measures the acceleration of motion in one or more directions and can convert that acceleration into velocity and displacement values through integration. This makes it a versatile sensor for monitoring the condition of rotating machines, motors, compressors, and gearboxes.

Types of Accelerometers

  • Piezoelectric: the most widely used in industrial environments. High sensitivity, ideal for monitoring mechanical vibrations.
  • Capacitive: used at low frequencies. Lower sensitivity but useful for specific applications.
  • MEMS (Micro Electro Mechanical Systems): compact, cost-effective, and low power consumption. Key in wireless sensors for predictive maintenance.

How They Work in Predictive Monitoring

Vibration sensors are installed at strategic points on the asset. They detect changes in vibration patterns caused by imbalance, misalignment, bearing, or gear failures. When vibration exceeds certain thresholds, the monitoring system generates alerts.

In Maper’s case, wireless sensors collect data 24/7 and send it to the cloud, where artificial intelligence algorithms and certified analysts identify faults in advance.

Advantages of Using Accelerometers and Vibration Sensors

  • Continuous monitoring without human intervention
  • Early detection of critical faults
  • Reduction of unplanned downtime
  • Extended asset lifespan
  • Optimization of maintenance resources

Common Applications

  • Electric motors
  • Speed reducers
  • Fans and turbines
  • Compressors
  • Industrial pumps

This type of sensor is compatible with cloud-based analysis platforms and can also be integrated with solutions such as SCADA or CMMS.

At Maper, we develop predictive monitoring solutions that integrate wireless vibration sensors with high-precision accelerometers. Our system detects more than 30 fault modes and enables complete traceability of your industrial assets’ condition.

Our specialists are certified under ISO 18436 for vibration analysis, ensuring reliable diagnostics and data-driven decisions.

Request a demo and find out how Maper’s vibration sensors improve the maintenance of your assets.

Written by

Luis Villanueva

Operations Coordinator.

What Is Power Factor and How Does It Impact Your Industrial Assets?

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Electrical energy waste is a silent enemy of industrial productivity. It represents high costs, accelerated asset wear, and low operational efficiency. How can you diagnose it and act in time?

Energy monitoring and power factor control make it possible to identify inefficiencies and prevent electrical failures. In this article we explain its impact, how to calculate it, and what tools to use to improve your energy management.

What Is Power Factor?

Power factor indicates how much energy is being converted into useful work and how much is lost as reactive energy. It is the ratio between active (useful) power and apparent (total) power.

When the value falls below 1, it means that a portion of the energy consumed is not being used efficiently, generating losses and potential penalties from electricity distributors

Impact of Power Factor in Industry

  • A PF close to 1 improves energy utilization.
  • A low PF can generate penalties, overloads, and failures in critical equipment.
  • The most common causes include oversized motors, poorly calibrated transformers, and low-efficiency lighting.

How to Correct a Low Power Factor

  • Install capacitor banks.
  • Resize loads according to demand.
  • Implement a real-time energy monitoring system.

Energy Monitoring with Maper’s WEMS

WEMS (Wireless Energy Monitoring System) is Maper’s solution for visualizing and analyzing the electrical behavior of each piece of equipment in your plant in real time.

It allows you to:

  • Measure consumption, current, voltage, and power per asset.
  • Detect load deviations or energy inefficiencies.
  • Identify critical power factors and optimize them.
  • Plan electrical maintenance before failures occur.

Installation is non-invasive and wireless, and it integrates easily with existing management systems. Data is analyzed with AI and accessible from any device.

Monitoring power factor is essential for maintaining efficient industrial assets and avoiding financial losses. WEMS provides key data to anticipate failures, reduce costs, and comply with energy regulations. Request a WEMS demo and optimize your plant’s energy consumption starting today.

Written by

Daniela Racioppi

Key Principles of Vibration Analysis for Fault Detection

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Vibration analysis is an essential technique for identifying mechanical faults in rotating equipment. Thanks to technological advances, it is now possible to monitor asset health without invasive intervention, anticipating failures through sensors and data processing.

This discipline is key to implementing predictive maintenance. By collecting signals with accelerometers and processing them through algorithms, it is possible to detect imbalance, misalignment, bearing failures, and other fault modes before they impact operations.

Among the fundamental principles of vibration analysis:

  • Does not require stopping the machine: performed under normal operating conditions.
  • Based on measurements of acceleration, velocity, and displacement.
  • Each fault mode generates a characteristic vibration signature.
  • FFT (Fast Fourier Transform) is key for visualizing spectra.
  • Signals are interpreted through parameters such as amplitude, frequency, and RMS.
  • Enables predictive and proactive maintenance.
  • Compatible with IoT sensors and online monitoring.
  • Can be integrated with cloud-based platforms.
  • Uses envelope alarms and machine learning algorithms.
  • Reduces unplanned failures and optimizes operational performance.

Vibration analysis is part of industrial predictive monitoring. At Maper, we apply triaxial sensors, early detection algorithms, and spectral analysis to increase asset availability.

If you want to implement vibration analysis and predictive maintenance on your assets, contact us today and find out how Maper can help you prevent critical failures.

Written by

Nicolás Sonzini

Operations Leader.

Six Sigma: How to Apply This Methodology in Industrial Maintenance

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Six Sigma is a methodology focused on reducing variability and eliminating defects in industrial processes. Its goal is to optimize operational efficiency, improve asset reliability, and increase customer satisfaction.

In predictive maintenance, Six Sigma makes it possible to quantify performance, standardize procedures, and make decisions based on real data collected by sensors and digital platforms.

Origin and Concept of Six Sigma

The term “Six Sigma” comes from statistics: “sigma” represents standard deviation. Operating at six sigma means achieving fewer than 3.4 defects per million opportunities (DPMO) — in other words, 99.99966% quality.

Its application has expanded to industries seeking to reduce failures and optimize asset performance, where tools such as vibration analysis and reliability engineering are essential components of variability control.

The 5 Phases of the DMAIC Method in Six Sigma

DEFINE Identify the problem from the customer’s perspective and establish clear objectives. In maintenance, this means detecting the most critical failure points and the assets that most impact production.

MEASURE Collect data on the current process. Maper’s IoT sensors measure variables such as vibration, temperature, and energy consumption — all essential for establishing an accurate baseline.

ANALYZE Use tools such as root cause diagrams or statistical analysis to identify the origin of failures. This stage is complemented by condition-based maintenance, which helps understand how variations affect reliability.

IMPROVE Implement solutions and measure their impact — for example, recalibrating machinery, standardizing procedures, or optimizing lubrication frequency.CONTROL Monitor the process to sustain results. At this stage, continuous monitoring with wireless sensors helps maintain the standards achieved and detect deviations in real time.

Key Six Sigma Tools Applied to Maintenance

Pareto Chart: identifies the main sources of asset failures.
Statistical Process Control (SPC): evaluates the operational stability of machines.
Capability Analysis (Cp, Cpk): determines whether a process meets expected tolerances.
Root Cause Analysis: detects recurring deviations and helps prevent mechanical failures.
These tools, combined with data collected by predictive sensors, transform maintenance into a quantifiable, continuously improving process.

Benefits of Integrating Six Sigma with Predictive Maintenance

  • Reduction of defects and greater asset reliability.
  • Optimization of technical and energy resources.
  • Decrease in unplanned downtime.
  • Real-time data-driven decision-making.

Implementing Six Sigma alongside predictive monitoring technologies turns plant data into actionable knowledge, increasing the efficiency and profitability of industrial operations.

Six Sigma not only improves quality — it reinforces operational reliability through rigorous process control and a data-driven culture.

At Maper, we integrate industrial sensors, vibration analysis, and predictive platforms that complement Six Sigma strategies to achieve sustainable continuous improvement.

Contact us and discover how to take your industrial maintenance to Six Sigma level.

Written by

Diego Ismirlian

Engineering Director.