Predictive Maintenance, Quality Control, and More with IoT

Businessman who is glad to have implemented IoT in his plant since he can now perform predictive maintenance on his machines.

The IoT connects products, processes, and individuals to help create a new age of intelligent and smart manufacturing. The penetration of digital sensors can vastly benefit all components of the manufacturing value chain. They allow for better visibility of production processes, predictive maintenance of machines, as well as the ability to automate tasks. 

The Internet of Things (IoT), a key component of industrial transformation worldwide, is being led by the manufacturing sector in harnessing this technology. According to IDC, $178 billion was invested in IoT by the sector in 2016. The main spending user case was operations, followed by maintenance and field service. 

Analysts cited a variety of reasons to support the belief that manufacturing will remain at the top of the industry during 2022, one of them being the estimated IoT spending of $1,2 trillion for this year.   

It offers applications that provide almost instant returns and give manufacturers an opportunity to aid in implementing digital transformations from multiple perspectives, including automation, customer centricity, reduced time to market, and increased visibility. 

Hereunder, we will discuss the most important uses, benefits, and applications of IoT within the manufacturing sector. 

Quality Control and IoT 

Manufacturers produce an item and then test it with their quality control unit. They hope to find and fix any flaws before the product goes on the market. IoT allows this to be proactive by using thermal and video sensors to collect all product data throughout a product cycle.  

To assist in verifying that the products meet specifications, manufacturers can test them at every manufacturing stage. Instrumentation and monitoring of equipment during manufacturing allow quality control personnel to find out where calibration deviations from standards are occurring. This is crucial to help prevent misalignment. With IoT, manufacturers can take immediate measures to improve the situation. 

IoT, together with radio frequency identification (RFID), makes inventory management efficient and seamless. Each item in an inventory is assigned a RFID tag. Each tag contains encoded digital information and a unique identification number (UID). RFID readers can scan the tags, and the cloud receives data it must process. 

Industrial IoT is about transforming RFID reader data into valuable business insights. It records the location and status of inventory items and allows users to compare the results. 

IoT-based inventory management architecture, for example, can use data about inventory quantity and location to calculate the required volume of raw material for a forthcoming manufacturing cycle. IoT-based inventor management outputs can be used in many ways. The system can alert users when they lose an inventory item or notify them when they need to replenish it. 

IoT provides cross-channel visibility for supply chain managers. It gives them a realistic estimate on available materials, new materials arrivals, and work in progress. This allows them to optimize shared costs throughout the value chain. 

Manufacturers can better prepare for receiving raw materials by tracking their speed and traffic flow. This reduces handling time and allows for more efficient production. 

Predictive Maintenance and IoT 

Manufacturers have used a time-based approach to plan maintenance schedules for their equipment and machinery. According to a survey, only 18% of equipment fails due to ageing. However, 82% of equipment failures are random. This shows that a time-based approach to equipment is inefficient and can lead to higher long-term costs. 

By leveraging industrial IoT, data science and predictive maintenance, manufacturers can avoid inefficient maintenance.  

Besides, they can use IoT sensors to monitor the equipment’s operating environment and analyze the data stored in the cloud using the relevant data to determine the wear and tear.  

Quick service and repair give way for greater efficiency in maintenance, better work allocation to field technicians, and more significant cost savings. 

Steel plants use water cooling panels that control several furnaces. This is extremely importance since leakages in panels can cause safety problems and production losses. Plant managers can use predictive maintenance that is IoT-based to identify and fix anomalies. This will prevent production delays and machine failures. 

Safety in Operation 

IoT, when combined with big data analytics, can optimize safety for workers, equipment, and operations in a manufacturing facility. It can also track KPIs, such as worker absences, machinery damages, vehicle mishaps, and any other mishaps that may affect normal activities. 

IoT wearables can be a crucial solution in this instance. For example, these devices allow for constant employee monitoring in terms of health metrics, even while they work in factories or fields.  

Employee monitoring can give employees information regarding their exposure to fumes, heart rate, fatigue, and stress levels. With this information, manufacturers can improve compliance and lower insurance costs for business owners. 

Since IoT can pose security risks if there are many suppliers, security protocols and standards that differ, manufacturers using IoT should link their IT infrastructure and operations technologies to prevent their assets from being targeted by malicious attackers.  

To aid in regulating the interaction between personal devices and manufacturing operations, they should think about how to plan their BYOD policies. This is where cloud/IoT service vendor support is crucial. 

Hardware and Software Design Leader in 4i Platform.
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