Applications of Real-time data in Manufacturing Operations

As Industry 4.0 technologies like IoT, AI, Big Data, RPA, etc are evolving the value of real-time data is increasing. In this Blog I have added the top 3 applications of real-time data in the manufacturing process that will have an impact on operations and processes:

1. Production planning and control

Installing a real-time data system in manufacturing equipment and processes keeps track of production regularly. Raw material and usage of inventories can be tracked daily, which helps in planning and demand forecasting. All the upcoming requirements of inventories can be accurately planned. Real-time data reports measure the performance of machine operators and the efficiency of their work.

Supply chain managers can get complete visibility of all the processes starting from raw material usage until the final product gets ready. Real-time data allows you to understand what potential changes need to be done and which areas help reduce the time of uncertainty in production management. Calculated decisions can be taken through regular reports and updates. Regular updates increase the trust of all the stakeholders/members involved in the organization.

2. Quality Assurance

In a manufacturing enterprise, the quality of products manufactured has to be maintained. Real-time quality reports of manufacturing are essential so that uncertain things can be immediately identified and resolved. This helps to reduce the time in aligning things in their place. Sensors should be used on manufacturing equipment to check the quality of manufactured products. Such sensors are directly connected to the internet gateways, transmitting data through the internet in real time. Through data analytics, reports are made that are visible to the stakeholders involved in the operations that help to maintain the quality of manufacturing.

Setting up alerts for when there is a dip in quality performance can quickly let management, production engineering, and scheduling know when there is a deviation in performance, which can help save you money due to lost production time. Forming KPI (Key Performance Indicator) and updating KPI results in real-time can be the best step that enterprises can take to maintain their quality assurance. Improving product quality and increasing Overall Equipment Effectiveness (OEE) by being able to better track machine utilization, scrap, and downtime reporting is also a high priority.

3. Equipment Maintenance

The regular maintenance of machinery and manufacturing equipment is important for manufacturers because it ensures quality production and reduces maintenance costs. Machinery and other manufacturing equipment in an enterprise are huge, therefore the cost of repairing is extremely high, so manufacturers must keep the upkeep from time to time. Integrating real-time data systems in machinery allows the manufacturers to stay daily tracking of machinery performance.

Sensors connected to the machinery and engine detect real-time conditions like temperature, usage, energy, quality, pressure, life cycle, etc. Regular data of these factors of the machine gives accurate condition reports that help in planning and strategizing maintenance activity. Regular updates of machinery make sure the trust of the standard assurance team, Stakeholders, and provide chain members. All of those factors contribute to raised business results, driving up Return on Invested Capital (ROIC) as machinery lasts longer.

For fault diagnosis and prediction, sensors are embedded in production equipment to detect a variety of data, including variables such as location, weight, temperature, humidity, vibration, and flow rate.

Read our 1st Blog -?What is Industry 4.0?

Read our 2nd Blog -?What is Supply Chain Management and its importance?

Read our 3rd Blog -?What is Intelligent and Smart Manufacturing?

Read our 4th Blog -?Industry 4.0 Technologies and their Applications - IoT, AI

Read our 5th Blog -?Indian Industry 4.0 Challenges that affect the adoption

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Written by -?Dhruman Gohil