Predictive Maintenance in Manufacturing: What, Why, and How?

Bhagyashri Kambale | March 14, 2022 | 767 views
PREDICTIVE MAINTENANCE IN MANUFACTURING
Predictive maintenance analytics is a type of maintenance that frequently monitors an asset's health. This timely maintenance or monitoring of assets or machines reduces unexpected breakdowns and allows manufacturers to plan around their production schedule.

“Even the best-built machines need proper preventive maintenance to remain productive and reach their maximum working life.”

- PMI (PREVENTATIVE MAINTENANCE INSPECTION) 

Predictive maintenance methods and software have evolved. Companies no longer need to import data into spreadsheets and extract insights manually. Businesses can now effectively estimate maintenance tasks using AI and machine learning algorithms in predictive maintenance systems. Robots and Internet of Things (IoT) devices are also generating more data than ever before, helping manufacturers be more insightful in their operations and processes.


Why Should Predictive Maintenance Manufacturing Be Considered?

The depreciation cost is significant in industries like manufacturing, where the cost of advanced equipment is very high. This makes it important to make sure that the assets of the manufacturing company are well-managed.

Using the predictive maintenance model in these situations saves money on multiple levels. Even though there are protocols like lean management and six-sigma, their usefulness is being questioned when it comes to existing business practices.

In a world where technology dictates practically every aspect of our lives, it is essential to have efficient procedures powered by cutting-edge technology. In essence, predictive maintenance aims to upgrade asset management using IoT.

According to a PwC analysis, manufacturing predictive maintenance
  • Cuts cost by 12%
  • Increases uptime by 9%
  • Extends the life of old assets by 20%
  • Reduces safety, environmental, quality, and health hazards by up to 14%


Types of Predictive Maintenance Technologies

 
 
Vibrational Analysis Acoustical Analysis (sonic) Acoustical Analysis (ultrasonic) Infrared Analysis
This is the preferred method for predictive maintenance in high-rotational industrial plants.

It is cheaper than other condition monitoring methods because it has been around longer.

Vibrational analysis can detect imbalance, misalignment, and bearing wear in addition to looseness.
This form of analysis is employed for low-and high-rotating machines. It's popular among lubrication technicians.

However, it does not focus on identifying the reasons for rotating equipment failure by measuring and recording vibrations at discrete frequencies for trending purposes.

Instead, acoustic bearing analysis targets lubrication technicians and focuses on proactive lubrication.
Ultrasonic acoustical analysis is solely used for predictive maintenance.

Its ultrasonic detection capability can distinguish between ultrasonic noises of machine friction and stress.

This form of analysis is more accurate than vibration or oil analysis.
This form of analysis is not affected by an asset’s rotational speed or volume. As a result, it is ideal for a wide variety of asset types.

When the temperature is a good indicator of possible problems, infrared analysis is the most cost-effective way to keep things running smoothly before they break down.

It is frequently used to diagnose cooling, airflow, and even motor stress issues.


How to Apply Predictive Maintenance Analytics in Practice?

Management is supplied with ROI scenarios prior to implementing predictive maintenance on the factory floor. Additionally, maintenance personnel and machine operators require training on how to use PdM technology (predictive maintenance). Following this, the true implementation of predictive maintenance equipment begins.


Establish Benchmarks

The maintenance team establishes acceptable condition thresholds for sensor-equipped assets.


Connect Gadgets to the Internet of Things (IoT)

The sensor is attached to the asset. A vibration meter, for example, is attached to a mechanical asset through gears, while a temperature sensor is attached to a boiler.


Integrate Hardware and Software

In this case, the IoT device is connected to a central management system (CMMS) or a remote dashboard, which collects and analyzes data.


Establish a Maintenance Schedule

Inspections are initiated automatically by a CMMS when a condition limit is exceeded or manually by the person monitoring the dashboard.


Predictive Maintenance Example


Preventing Power Outages

Power outages can be extremely inconvenient for those affected. They can be discovered early and so avoided with predictive maintenance technologies. Sensors would once again be used in this situation to deliver artificial intelligence-based insight into assets. This intelligence-based insight alerts the plant supervisor when equipment is about to malfunction.


Manufacturing Supervision

Since industrial plants typically contain many expensive assets and valuable equipment, they may invest in infrared imagers to monitor various elements of assets, such as temperature, to avoid overheating. This predictive maintenance technology assists plants in avoiding excessive use of critical equipment, which might result in disruptive breakdowns.


Final Word

Predictive maintenance is an advantageous tool for larger organizations that have outgrown typical preventative maintenance approaches and have an additional budget. It can generate a positive return on investment, transforming the maintenance department into a source of cost savings and increased revenues.

Predictive maintenance has some drawbacks, such as high startup costs and the requirement for specialized expertise. However, it helps to conduct maintenance only when necessary, assisting facilities in cutting costs, saving time, and maximizing resources.

Consultation with equipment makers and experts in condition monitoring should be conducted prior to determining whether predictive maintenance is the best approach for specific assets.


FAQ


Is predictive maintenance cost-effective?

Yes. Predictive maintenance saves between 8% and 12% compared to preventive maintenance and up to 40% compared to reactive maintenance, according to the U.S. Department of Energy. 


What is the difference between predictive and preventive maintenance?

Predictive maintenance saves money on labor and materials, whereas preventive maintenance is less expensive to undertake. Moreover, preventive maintenance is scheduled on a regular basis, whereas predictive maintenance is scheduled on an as-needed basis, depending on asset conditions.


What is TPM?

TPM, i.e., Total Productive Maintenance is a team-based method that focuses on proactive and preventative techniques to increase plant and equipment reliability.

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