IoT Transitioning Industries from Scheduled to Predictive Maintenance

IoT Business Solution

Since the first industrial revolution, machines have become an integral part of manufacturing companies. Even after three centuries, it is nearly impossible to find an industry where you can’t hear the thuds and clamor of mechanical components colliding with each other.

Clearly, it is almost impossible to comprehend the existence of any industrial segment without machines. Their use boosts the quality of goods being produced, reduces material wastage, and most importantly enhances the production rate of any company. They also optimize the entire end to end supply chain, influencing all the essential industrial operations such as mixing, grinding, fabrication, manufacturing, assembly, warehousing, logistics, and distribution.

When machines are in good condition, they are an invaluable asset that enhances the speed, accuracy, and efficiency of any workshop or factory setup. However, with their deterioration and breakdown, a company can witness equipment downtime and even plant shutdown, resulting in the inability to fulfill demand conditions and subsequently, financial losses.

Hence, for uninterrupted and continuous functioning of machines and long-term profitability, a robust inspection and maintenance regime is followed that allows operators to identify vulnerable mechanical components and conduct necessary repairs.

While maintenance includes corrective, preventive, time-saving, risk-reducing, and condition improving measures; standard repair and maintenance procedures are categorized into below-mentioned sub-categories:

1) Scheduled Maintenance

2) Predictive Maintenance

Let us have a quick look at both these approaches:

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Scheduled Maintenance – A Pre-Designed Inspection Regime

Any regular task that is given to a technician or operator with a deadline optimizes the performance of a machine inculcates in the scheduled maintenance operation. These tasks include recurring cleaning, inspections, adjustments, overhauls, and replacements that are often accompanied after the plant is taken in downtime condition.

A standard example of scheduled maintenance will be the oiling needed between two sliding components of a machine on a regular basis.

The purpose of scheduled maintenance regimes is to prevent reactive maintenance where a machine is repaired after it fails. Regular checkups of the entire mechanical apparatus increase the lifetime of assets and allow companies to reduce unnecessary repairs and replacements while efficiently optimizing the allocation of resources and assets over a prolonged period.

However, there are several drawbacks to using scheduled maintenance as well. First of all, to conduct scheduled maintenance, the whole industry is required to be kept in shutdown mode, that affects the productivity of the company. Furthermore, the entire apparatus has to be inspected and repaired on a single go that consumes a lot of manual hours and valuable resources that could be used for other productive purposes.

Predictive maintenance, a concept that focuses more on conducting tweaks and adjustments as required, is a much better maintenance technique that eliminates all these challenges.

Predictive Maintenance – Approach to Conduct Repairs as Needed

Predictive Maintenance is a proactive maintenance strategy that caters to the repair of any machine or equipment just before its performance is about to deteriorate. In this technique, the failure or breakdown of equipment is forecasted based on its performance and condition. Subsequently, necessary repairs and replacements are made on the particular to- be-damaged asset, that eliminates the need to shutdown the entire apparatus and streamlines the operations for continuous production.

Here are some benefits of using predictive maintenance over scheduled maintenance:

A. It helps in predicting unexpected breakdowns before the malfunctions even occur. This increases the availability and uptime of the machines resulting in improved asset reliability and better machine utilization.

B. Since predictive maintenance doesn’t require workers to follow a strict pre-planned regime for inspection and maintenance, they can be utilized for more productive work. This also reduces operational costs by saving time wasted due to excessive maintenance and making workers available for other necessary tasks.

C. It also increases the efficiency of the entire supply chain by reducing the time wasted in inspecting the whole apparatus and by maximizing the efficiency of workers.

The predictions made to determine machine failures are made based on the analysis of data gathered from various condition monitoring systems and techniques about the status and performance of equipment and machines. One such technology that enables data ingestion and processing from such a large-scale industrial apparatus is the cutting-edge technology of the Internet of Things.

IoT – The Technology Enabler for Predictive Maintenance in Industries

Internet of Things technologies uses advanced and intelligent sensor devices that collect vital data about the working and performance of equipment installed in a factory. The data passes through a series of IoT infrastructure and finally stores in a cloud platform.

The stored data can then be processed via analytics and data processing units; and compared with pre-entered thresholds to determine if the parameters being checked are within the permissible range or exceeding it. This helps technicians and operators to determine if the machines are operating as per the industrial standard, allowing them to mitigate laborious inspection tasks.

If the value of a particular parameter associated with machine performance crosses the permissible range, the operators can be alerted via a notification on their mobile monitoring devices enabling them to take proactive measures and conduct repairs and tweaks on the susceptible component before its breaks.

Furthermore, the gathered data from different embedded sensors on assets can be analyzed collectively to determine insights, trends, and patterns about the estimated machine failure in the future. Subsequently, maintenance and inspection tasks can be planned accordingly when the probability of failure is at the peak.

Hence, IoT acts as a condition monitoring system for companies to supervise the status and performance of their machines and equipment, and adjust and maintain them predictively.

IoT – The Future of Manufacturing

The growth of predictive maintenance is powered by the increasing focus of industries over reducing asset downtime and operational/maintenance costs. The market value of predictive maintenance is expected to grow at a CAGR of 25.2 % from the current value of $ 4.0 billion to $ 12.3 billion in 2025.

IoT as an enabler for condition monitoring will have a major role in this growth and allow companies to revolutionize their maintenance operations.

Additionally, the technology of the Internet of Things also empowers industries to improve human-to-machine interaction and machine-to-machine synchronization; resulting in optimized on floor activities and automated manufacturing respectively.

Hence, IoT not only allows the optimization of maintenance techniques, but also offers new possibilities in terms of improving overall equipment effectiveness, boosting plant efficiency, and increase its production rate.