How to use Internet of things in manufacturing industry?

Stronger demand for customization & increasing customer expectations encourages manufacturers to find more innovative ways to implement the Internet of Things in the manufacturing industry. In an attempt to increase productivity and uncover new ways of enhancing supply chain operations, businesses resort to digital transformation.

Hence, the Industrial Internet of Things in manufacturing is a way of digital transformation. And IoT employs a network of sensors to collect critical data and uses the cloud to turn this data into insights. These valuable insights help to measure the efficiency of the manufacturing operations.

Reasons for Adopting the Internet of Things in Manufacturing


Businesses are motivated to use IoT in manufacturing for a variety of reasons. The following are the primary adoption drivers for Industrial IoT solutions:

1. Reduction in Operational Cost

Due to optimized asset and inventory management, reduced machine downtime, and more agile operations, companies reduce operational costs. These provisions will also help them to create new sources of revenue. For instance, smart, connected products allow the shift from selling products to selling experience – product usage and post-sale services. 

2. Easier Connectivity to Market 

You can reduce product cycle time by faster and more efficient manufacturing and supply chain operations. For example, Harley-Davidson used IoT to reconfigure its York, PA, manufacturing facility. As a result, it can reduce its time to produce a motorcycle from 21 days to 6 hours.

3. Mass Customization of Products 

The mass customization process requires a dramatic increase in the variety of produced SKUs. It causes inventory to go up and become more diverse. Tracking the manufacturing operations becomes burdensome. The IoT in manufacturing facilitates mass customization by becoming a source of real-time data required for thoughtful forecasting. 

4. Provision for a Safer Workplace

IoT contributes to a safer workplace. When combined with wearable devices, IoT allows for monitoring workers’ health and risky activities that can result in injuries. IoT addresses safety issues in potentially hazardous environments and ensures worker safety. For example, the oil and gas industry uses IoT to monitor gas leaks.

IoT-Driven Manufacturing Operations

The IoT in manufacturing has several applications. Here we are mentioning a few of the important operations below –

1. Monitoring Equipment Utilization

According to ITIF research, IoT applications for monitoring machine utilization can boost manufacturing productivity by 10 to 25%. IoT solutions for machine utilization provide businesses with real-time metrics on equipment utilization.

As a result, it provides a detailed view of what is happening at each stage of the manufacturing process. Monitoring machine utilization begins with gathering pertinent data about machine operating parameters, such as run time, product output, etc.

Data is collected in real-time and sent to the cloud for processing. The cloud collects data and transforms it into useful insights about equipment utilization KPIs. The factory workers can visualize the results of the data analysis and display those results via a user app after analyzing the data.

2. Product Quality Control 

There are two methods for monitoring the quality of manufactured goods. The first method is to inspect a WIP (work in progress). As it moves through the production process cycle or to monitor the condition and calibration of machines used to manufacture a product.

Although quality control based on inspecting WIPs yields more accurate results, the method’s use is hampered by several limitations. On the other hand, the second method depends on monitoring machine conditions and calibration and provides less scope differentiation.

It also provides a simple binary classification of “good” and “bad.” It does, however, aid in the detection of bottlenecks in manufacturing operations and the identification of poorly tuned or underperforming machines. 

3. Monitoring Process Safety

For workers in various industrial sectors, such as mining, oil and gas, transportation, and so on, RFID tags that collect data on their location. The wearable sensors record heart rate, skin temperature, galvanic skin response, and other parameters.

The sensor data is sent to the cloud and compared to contextual data to identify unusual behavior patterns. It protects workers from falls, overexertion, and other injuries and promptly alerts them to safety threats.

A combination of high skin temperature, increased heart rate, and no movement patterns for about a minute, for example, could indicate that a person is overheating. An IoT solution notifies an employee’s responsible person via a mobile application whenever such a situation is detected.

4. Industrial Asset Tracking

IoT-based asset management solutions relieve employees of the tracking burden by providing real-time data about an enterprise’s assets, locations, and movements. They eliminate errors associated with manual data entry methods. IoT collaborates with RFID to enable asset tracking in manufacturing.

Whether a magnetic locator or a crane, each asset is labeled with an RFID tag that serves as an asset identifier. Each tag has a unique ID linked to information about a specific asset. The ID, as well as the associated asset data, are both stored in the cloud. The asset data may include physical parameters, cost, serial number, etc.

5. Enterprise Inventory Management

Inventory management solutions powered by IoT assist manufacturers in automating inventory tracking and reporting. They also maintain constant visibility into the statuses and locations of individual inventory items, allowing them to optimize lead time.

Smart inventory management solutions are said to save 20% to 50% of an enterprise’s inventory carrying costs due to these advancements. Inventory management systems used in manufacturing are based on IoT devices and RFID technologies.

Each inventory item has a passive RFID tag attached to it. Each tag has a unique ID that contains information about the attached item. RFID readers have a habit to retrieve data from tags. A reader also captures the IDs of tags and sends them to the cloud for storage and processing.

6. Predictive Maintenance & Monitoring

According to Deloitte, predictive maintenance solutions based on Industrial IoT reduce factory equipment maintenance costs by 40%. The solution is at the forefront of IoT adoption, with 55 percent of businesses piloting predictive maintenance projects.

Predictive maintenance is based on the information gleaned from continuous equipment condition monitoring. A piece of equipment has sensors attached to it, which collect data on various parameters that determine its health and performance.

After being collected, real-time data from multiple sensors is transmitted to the cloud. It is also combined with metadata and equipment usage history. Along with this the system also collects maintenance data retrieved from ERP, maintenance systems, and other sources.

IoT’s Impact on Manufacturing


IoT technologies are transforming the way manufacturing systems are built and run. It is resulting in improvements across three major dimensions of the digital transformation:

1. Visibility into the storefront and business operations from the top floor

The IoT in manufacturing provides a revolutionary level of visibility into the shop floor and field operations, and it also provides the possibility of convenient control over enterprise resources. IoT technologies bridge the gaps that cause systems such as ERP and MES to reach their limits.

IoT enables businesses to significantly increase manufacturing process productivity by providing manufacturers with second-by-second shop floor data. According to IBM, using IoT insights for manufacturing process optimization can result in a 20% increase in product count from the same production line.

2. Supply chain visibility throughout the manufacturing supply chain

End-to-end supply chain visibility still appears to be a long way off for 52 percent of managers. The adoption of IoT-driven manufacturing supply chain management solutions, on the other hand, is looking up. According to IDC, by 2020, 80 percent of interactions will occur over cloud-based networks.

According to the same source, the transition to IoT-enabled supply chain management solutions is expected to increase the productivity of objects by 15% and cost efficiency by 10%. For example, smart supply chain management solutions give manufacturers real-time visibility into all objects’ locations, status, and conditions.

3. Access to information about remote and outsourced operations

High logistics costs, rising demand for customization, the complexity of the global supply chain, and a scarcity of local talent necessitate the distribution of shop floor operations. When a company constructs or purchases a manufacturing facility in a different city, state, or country, it must maintain its manufacturing and production standards.

You can also monitor compliance with production standards, using traditional methods of IoT. Predictive maintenance based on IoT and timely prediction of potential failures enable scheduling maintenance activities in advance, and it removes the need for a local maintenance team. Similarly, Consequently, IoT-powered utilization monitoring solutions assist manufacturers in monitoring the efficiency of manufacturing operations.

To wrap it up


The Industrial IoT enables manufacturing businesses to maximize productivity by ensuring production uptime, lowering costs, and eliminating waste. Thus, manufacturers better understand the manufacturing and supply chain metrics by leveraging IoT with big data.

It also improves demand forecasting, reduces time to market, and improves the customer experience. However, given the scale and complexity of Industrial IoT initiatives, successful IoT adoption necessitates careful orchestration. Thinklytics helps industries apply the Internet of Things IIoT in manufacturing and accelerate IoT Projects as per business requirements. 

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