Why your Manufacturing Enterprise needs a Data catalog

Today, all industries prioritize digital transformation. And the manufacturing segment is no exception. Things have changed today. Businesses are seeing more customer expectations, increased customization demands, and the complexity of the global supply chain. So, they are now left with no other options but to find more innovative products and services.

To deal with these challenges, manufacturing companies are increasingly investing in the Internet of Things(IoT).

What is IoT?

It will help if we acquaint ourselves with the definition of IoT. However, before we conclude a definition conforming to the manufacturing industry, let us go through a generic version of the definition.

From a generic point of view, you can regard IoT as a system of interrelated computing devices, mechanical and digital machines, objects, or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.

Now, let us define IoT from the manufacturing industry perspective. The definition goes as — IoT is a means to digitize industry processes by using a network of sensors to collect critical production data to use it in various software to translate the data into valuable insights about the efficiency of the manufacturing operations.

How the Manufacturing Sector Uses IoT?

The manufacturing sector uses IoT in many ways. For example, the sector uses many IoT applications that deal with facility and asset management, security and operations, logistics, and customer servicing.

To develop a deeper understanding, let us go through the following use cases of IoT in manufacturing:

Predictive Maintenance

Unexpected downtime and breakdowns are the most significant issues in the manufacturing sector. Therefore, the industry should identify the possible machine failures, their occurrences, and consequences.

To deal with these potential challenges, manufacturing companies now use artificial intelligence(AI) and machine learning(ML) for faster and wiser data-driven decisions.

With the help of ML, the companies can identify patterns in available data and predict future machine outcomes. And to achieve that, they should identify the correct data set and combine it with a machine to feed real-time data. With such information, manufacturers can determine the current condition of their machinery, warning signs, transmit alerts, and start repair processes.

IoT-enabled predictive maintenance can help manufacturing companies lower maintenance costs, lower downtime, and extend equipment life. As a result, their productivity increases due to the smooth running of machines.

Asset Tracking

Tracking assets with the help of IoT has become a widespread practice among many manufacturing companies.

According to industry speculations, there will be 267 million active asset trackers in use globally by 2027 for agriculture, supply chain, construction, mining, and other markets.

Notably, the manual practice of manufacturing companies spending a lot of time tracking and checking their products is likely to become a thing of the past in the future.

IoT can make things easier by using sensors and asset management software to track products automatically and quickly.

The sensors broadcast the location information continuously over the internet, and the software displays that information to keep you updated. And the result is that manufacturing companies can reduce their time in locating materials, tools, and equipment.

The automotive industry is the best example of IoT helping businesses achieve effortless and efficient asset tracking for vehicles. For example, Volvo Trucks uses IoT-based connected-fleet services to navigate vehicles intelligently with real-time road conditions. The company obtained the road condition from other local Volvo trucks.

Weather analytics is likely to work faster and more accurately using real-time data from vehicles in the future. For example, windshield wiper and headlight use during the day can indicate that the weather is rainy. IoT-based sensors can route the weather information to the company. It can then reroute the vehicles to maximize asset usage.

The e-commerce company, Amazon, is another example of using IoT to track assets. The company uses WiFi robots to scan QR codes on its products to track its orders.

The bottom line is that if manufacturing companies can track their inventories at the click of a button, they will never miss deadlines. Moreover, they can use the data to analyze trends, making their manufacturing process more efficient. And IoT can play a significant role in the asset tracking and management process.

Promoting Innovation

IoT can help manufacturing companies collect and audit manufacturing data. With such a facility, the companies can efficiently track the production processes. And at the same time, they can collect massive amounts of data.

Let us go through the example of JCDecaux Asia implementing their displaying strategy leveraging the capabilities of IoT. Their idea was to test whether the ad campaigns they carry out can elicit interest from people. And to attract people, they used more and more animations in their ad campaigns. In addition, they installed small cameras on some screens to determine whether people slow down in front of their ads or not. If people slow down in front of their ads, their ads draw interest from people.

The company plans to display ads tailored to individual profiles in the future. For example, they plan to run ad campaigns at airports based on a specific time of day or landing a plane coming from a particular country.

The working mechanism will involve connecting IoT sensors to the airport’s arrival systems. The data thus generated will send the information to the displaying terminals, which will display a specific ad for the arriving passengers.

As a result of using IoT, manufacturing companies can develop innovative products, services, and new business models.

The Final Words

Manufacturing companies need a data catalog to leverage the capabilities of IoT in their businesses. You can regard a data catalog as a central repository of metadata. With a data catalog, all employees in a company can have access, understand, and trust the necessary data to achieve a particular goal.

For the companies to use advanced analytics, they need to collect data from sensors, guarantee digital security and use AI and ML. And for that, they need to unlock data, meaning centralizing data in an innovative and easy-to-use corporate Yellow Pages of the data landscape.

It becomes easier for manufacturing companies to extract meaningful insights from data through a data catalog.