Are you wondering why data collection has become so important for manufacturing? The days of traditional manufacturing have long gone. With technological advancements, manufacturers have realized the importance of modern ways of manufacturing. As a result, they have adopted data collection and analytics techniques to remain competitive in the industry. Earlier manufacturing was all about mechanical processes of producing goods with machinery, equipment, and manpower. However, as companies understood that manufacturing is much more than simple mechanical operations, data collection became a vital component of the modern manufacturing process.

The data collection process is adopted across industries and from automotive to healthcare, collected data is helping organizations improve their operational efficiency. Over the years, manufacturers have also started implementing data collection techniques to improve their manufacturing processes. With access to real-time data, manufacturing companies can better monitor operations and control costs to ensure smooth plant operation. It allows operations managers to view, analyze, and act upon collected information with greater speed and accuracy. But, what exactly this data is and how it is collected?

What is the IoT Data Collection?

If you look around, you can find devices that are connected over the Internet of Things (IoT). Possibly, you’re using some type of consumer IoT devices, such as security systems, smart appliances, smart TVs, and wearable health meters. There are also commercial devices like traffic monitoring devices, and weather tracking systems.  These devices and equipment are embedded with sensors to detect, measure, and send data in some form. This means that IoT allows monitoring and measuring data in real-time to gain valuable insight. IoT data collection is the process of using sensors to monitor the conditions of physical objects to save time, energy, and resources. So, how exactly IoT sensors work to collect, process, and analyze data? The data is collected by connected devices through sensors or wearables. Internal sensors collect data that is transmitted, saved, and can be retrieved later. The data that IoT sensors and devices generate is then processed before using any type of analytics. The data coming from different devices is transformed into a uniform format and then data analysis tools or procedures are applied.

Why do Manufacturers Need to Prioritize Data Collection?

The modern manufacturing units produce a massive amount of data. The collected data often go wasted due to a lack of proper data analytics procedures. If manufacturers properly collect and utilize this data, the collected valuable information could help companies make making smarter business decisions.

For manufacturing plants, it can be challenging to collect and capture all of the relevant data. However, by implementing proper IoT data collection techniques throughout the plant, it’s possible to use the gathered data to streamline their processes. Now, let’s take a look at the benefits of a data-driven manufacturing environment to understand why it’s important to prioritize manufacturing data collection.

1.      Better Insights into the Manufacturing Process

The gathered data is processed to get access to advanced analytics that can help in identifying opportunities to increase production yields. A connected factory or plant produces a lot of data that can tell how the manufacturing processes are running and where improvements need to be made. When managers get real-time data and accurate reports, it helps in observing trends in production and labor time. A data-driven manufacturing facility can better track workers’ performances, work progress, detect flaws and quality issues, as well as take measures to minimize workers’ safety and business risks.

2.      Cost Savings

By implementing IIoT applications, manufacturing companies can significantly reduce costs. An efficient data collection solution gives managers real-time access to crucial information. This data can reveal extremely useful information such as when employees are logging on and off to work. Managers can also check labor costs by shift, as well as determine labor shortages or an over-allocation of manpower resources. The real-time data helps manufacturers improve productivity and profitability by detecting flaws. This helps in minimizing waste in production processes and reduces production costs.

3.      Improved Customer Satisfaction

Whether it’s a manufacturing company or any other industry, the goal of every business is to satisfy their customers. For a manufacturing company, it becomes even more important to meet the needs of its customers. The manufacturers keep looking for the best ways to offer what their customers are looking for. And the best solution for finding the changing needs and demands of customers is to collect data. Many manufacturing companies are already using various methods to reach their customers and get data on their preferences. Online forms, as well as outlets and dealerships, can help in collecting the data. The gathered information can be collected and analyzed to identify the commonalities and differences between customers. The analyzed data can help in meeting the needs of the majority of customers. When manufacturers become more adaptive to the needs of their customers, it helps in improving customer satisfaction. This data also gives manufacturers a head start to develop new products.

4.      Efficiency and Transparency

A connected manufacturing environment helps in bridging the gap between machines and humans and allows managers to interact with machines even from a distance. When everyone involved in the manufacturing process get access to the same actionable information it helps in maintain transparency across the board. It ensures that all member of the team is on the same page to avoid mismanagement and resource wastage. The data insights help management in making the right strategic decisions and maintain operational efficiencies. Consistency is maintained throughout the system by eliminating wasteful mistakes. One of the greatest applications of IIoT in manufacturing units is predictive analytics.  The historical data saved electronically is of immense help for a Predictive Analytics system. The data manufacturers collect today can be used tomorrow for avoiding downtime and boosting productivity.