Advanced handheld analyzers can collect vibration-based data from rotating assets, indicate potential problems on the spot, store and share the data. However, even with the modern technological advancements, handheld analyzers lack certain advantages that Industrial IoT sensors offer.

Monitoring the operating health of equipment within a plant is essential to any strategy aimed at reducing downtime, lowering costs, and improving the productivity of manufacturing operations. Rapidly diagnosing the occasional mechanical issues in the production equipment is a survival mission in today’s competitive business world. Traditionally, condition monitoring was very expensive and required specialized skilled personnel, making it a challenging investment.

Handheld analyzers are used for collecting condition monitoring data that is later used to analyze the health & performance of this equipments. Firstly, one collects (walk around) and stores the data such as vibration, acceleration, temperature, etc. This data (overall, spectrum, time waveform, etc.) is later uploaded into a cloud or traditional software platform for manual analysis by expert users.

Spectrum Analyzers measure the magnitude of the input signal vs frequency within the range of interest. The primary use is to identify the amplitude of known and unknown frequency components. The input signal which is provided for the analyzer is assessed depending on a different frequency and amplitude levels. This kind of assessment is mainly helpful for testing, handling RF circuitry, and designing. Due to its accuracy, the spectrum analyzer has gained a lot of applications in the field of electrical and electronic measurements. It is used to test many circuits and systems. These circuits and systems operate at a variety of frequency levels.

Handheld analyzers allow to monitor parameters such as vibration, temperature, and other types of complex machine data that helps maintenance and reliability professionals to improve the reliability of equipment. These analyzers also allow transferring the data to a software platform that allows expert users to analyze the data and provide insights.

Advanced handheld analyzers can collect vibration-based data from rotating assets, indicate potential problems on the spot, store and share the data. It can be connected to the cloud or on-premise platforms and dashboard software to generate meaningful insights from the machine data. However, even with the modern technological advancements, handheld analyzers lack certain advantages that Industrial IoT sensors offer.

Issues with Handheld Analyzers

  • While handheld analyzers can measure accurate data, the data collection is highly influenced by the consistency of the inspector/technician. The most important factor is the periodic collection of data from the same exact point on the machine. Even slight variation can cause delayed detection of faults. So, it is essential to ensure that the data is collected from the same exact point on the machine, every time.
  • If a machine with variable speed/load is being monitored, it is essential to note the speed/load at the time of data collection and consider these variations during analysis.
  • Moreover, the monitoring routine needs to be accurate and at periodic intervals to gain insights into the performance of the machine on a regular basis.
  • While handheld analyzers can collect and analyze machine output data, they are most often not capable of automatically identifying faults and providing the Remaining Useful Life of equipment.
  • In addition, Handheld analyzers are found to be expensive in comparison to the Return on Investment provided by wireless sensors to the end-users.

Value Creation with MachineDoctorTM

MachineDoctorTM is a unique 6-in-1 IIoT sensor, that measures the 6 most important parameters, Vibration, Acoustics, RPM, Temperature, Humidity & Magnetic Flux, to provide real-time insights about the health and performance of equipment.

MachineDoctorTM is a Plug & Play Sensor, that can be installed without the hassle of complex wiring and overcomes the challenges of manual data collection and analysis. The sensors are available in various form factors with flexible mounting options. The installation ensures consistent data collection from the machine in near real-time. This ensures that the plant staff is aware of the machine’s health at all times. The system set-up can be completed in a matter of a few hours, without proprietary wireless infrastructure, thereby providing an interconnected network of equipment.

Moreover, MachineDoctorTM can capture and provide full visibility of the raw data for analysis. This allows experienced analysts to review faults & notifications in depth before making decisions that impact the manufacturing and production operations.

In addition, MachineDoctorTM sensors have onboard edge computing capability which is a unique feature that allows sample collection every few minutes and subsequent evaluation of this data for anomalies. If anomalies are detected, then data sets are uploaded immediately for in-depth, automated, cloud analysis. This allows nearly full-time monitoring without full-time connectivity, thereby preserving the battery life on wireless devices.

While handheld analyzers can collect and analyze machine output data, it is not capable of automating fault identifications. The AI-based solution can detect even small changes in the equipment, to prevent any impact on production. It characterizes faults based on the specific fault frequency and provides a graphical representation (Amplitude, Exponential Moving Average Curve, etc.) for the analysis of trend progression. It is capable of distinguishing between process upsets & faults, allowing it to predict faults before they happen. It can also evaluate the Remaining Useful Life of equipment sets, thereby allowing maintenance & reliability professionals to schedule repairs/maintenance at appropriate schedules.

Automated end-to-end Predictive Maintenance Solution

The automated end-to-end predictive maintenance solution from Nanoprecise offers anomaly detection, fault diagnosis, remaining health prediction, and decision support tasks. Furthermore, the dynamic data-driven method is able to detect the specific components that would behave abnormally much in advance before the malfunction. The method is also capable of detecting almost all types of failure modes and enabling predictive maintenance activities.

The system not only detects any anomaly but also predicts mechanical faults related to unbalance, misalignment, looseness, bearing, and gearbox. Moreover, by using the fault characteristic frequency of a particular equipment set, the solution can predict the remaining useful life of that equipment.

In-Depth Comparison of MachineDoctor with Handheld Analyzers

Continuous Monitoring

Handheld analyzers focus on periodic condition monitoring of equipment. This will provide only a snapshot of the condition of the equipment at the time of inspection. For example, if a part experiences a serious problem before the next inspection, assets will fail anyway. This may result in higher costs.

MachineDoctorTM allows for continuous monitoring of the equipment with near real-time data about its health & performance being conveyed to the engineers & technicians. This reduces the time & cost spent on maintenance activities and increases the reliability of the equipment.

Data Collection & Analysis

Handheld analyzers require manual data collection, upload, and analysis for obtaining meaningful insights about the health & performance of machines.

MachineDoctorTM on the other hand, offers automated data collection, upload, and analysis, thereby enabling maintenance & reliability professionals to focus on value-added tasks rather than repetitive ones.


The Sensor and handheld analyzer are calibrated using a shaker and signal generator to adjust sensitivity accordingly by comparing with the standard. This process is required to be repeated (bi-)annually and is a manual process, requiring skilled personnel, translating into higher cost and time.

MachineDoctorTM is calibrated before installation and does not need to be calibrated during their service life. This reduces the set-up time and ensures that engineers & technicians focus on the important tasks rather than on calibration & data collection.


Handheld analyzer is costly hardware that requires dedicated personnel to operate. Generally, a handheld analyzer with a single axis sensor costs approximately INR 1,60,000 – 25,00,000, while one with a triaxial sensor costs approximately 30,00,000.

However, MachineDoctorTM wireless sensors can be installed on the equipment to capture the complex machine data in real-time. This is a much more cost-effective alternative that offers better data and automated insights to maintenance professionals.

Direct Comparison of MachineDoctorTM and Handheld Analyzer

Nanoprecise has successfully validated the data from MachineDoctorTM sensors in comparison to industry-standard handheld analyzers on many occasions and it was found to be highly accurate. Below is a snapshot of comparison between MachineDoctor and a handheld analyzer.

ID Fan#1 Handheld Analyzer (Uniaxial) Nanoprecise Amplitude Difference Nanoprecise Triaxial Amplitude Difference
MIH 1.59 10.23 AM 1.46,1.49 10:29 AM,10:31 AM 0.1 1.49 0.1
M1V 0.59 10.32 AM 0.66 10:36 AM 0.07 0.58 0.01
M1A 0.67 10.39 AM 0.64 10:43 AM 0.03 0.54 0.13
M2H 1.91 10.47 AM 1.88,1.82 10:51 AM,10:53 AM 0.03 1.88 0.03
M2V 0.4 10.54 AM 0.43 11.00 AM 0.03 0.9 -0.5
M2A 0.25 11.03 AM 0.26 11.07 AM 0.01 0.29 -0.5
M2A 0.25 11.03 AM 0.26 11.07 AM 0.01 0.29 -0.04
F1H 1.57 11.10 AM 1.56 11.14 AM 0.01 1.56 0.01
F1V 0.52 11.14 AM 0.28, 0.29 11:18 AM, 11:20 AM 0.23 0.95 -0.43
F1A 1.09 11.21 AM 1.01 11:25 AM 0.08 1.8 -0.71
F2H 1.51 11.28 AM 1.47 11:31 AM 0.04 1.47 0.04
F2V 0.33 11.32 AM 0.22 11:36 AM 0.11 0.56 -0.23
F2A 0.78 11.38 AM 0.72 11:42 AM 0.06 0.87 -0.09

All vibration data is displayed in Velocity (RMS) mm/s

It is seen that all data which was collected within the same time (+/-5mins) gives very comparable values indicating that both devices are very accurately capturing the machine vibration and data can be used for accurate machine health evaluation and fault mode identification.


While the handheld analyzers are considered to be more accurate for collecting machine condition data, the recent technological advancements in wireless technology have significantly improved the data capturing capability of wireless sensors, making their data quality at par with the high-end handheld devices.

Nanoprecise helps Fortune 500 companies overcome the challenges of condition monitoring, with the help of MachineDoctorTM wireless sensors. MachineDoctorTM captures the output parameters of the machines & equipment sets to provide real-time information about their health & performance. This offers complete transparency of the operations to the plant staff.

MachineDoctorTM offers a number of advantages over the handheld devices such as Plug & Play Deployment and real-time analysis of machine health & performance. Handheld analyzers demand technicians to travel to the location of the machine and collect data manually at particular time periods, whereas MachineDoctor can be deployed in a matter of minutes, and captures the complex machine health data in real-time, to provide meaningful insights about its performance. Moreover, they do not require constant maintenance as these sensors receive updates Over The Air (OTA) and can analyze data on edge. All of these factors ensure that MachineDoctor sensors evaluate the machine health & performance accurately in real-time.