Innovations have been key drivers of development and they will continue to be the same. The technological advancements are easing the jobs for us and they are being used in every sector. One such sector that has benefited a lot from the technological developments, is the manufacturing industry.
Revolutions have been regular in the manufacturing industry. The introduction of machinery reduced the workload of humans. The demand for manual labor fell and yet the efficiency increased by the use of such machines. Humans were required to operate these machines but nowadays, even humans as operators are also being replaced. This is not the end at all. In the future, probably everything will be intelligent.
Talking of the developments in technology, we have Artificial Intelligence (AI), the Internet of Things (IoT), and Big data Analytics as examples before us. In particular, IoT has provided a lot of benefit in the areas which require faster development along with quality products. The manufacturing industry has similar requirements and hence IoT provides crucial help.
In this blog, we will be looking at the ways in which the Internet of Things is easing the job of manufacturers. To start with, a brief description of IoT will help to understand the main part of the blog.
Internet of Things means a network of interconnected devices ranging from computers and electronic gadgets to vehicles, all connected to the internet. IoT allows these devices to seamlessly exchange and consume data with minimal human intervention. An IoT system consists of sensors/devices which “talk” to the cloud through some kind of connectivity. Once the data gets to the cloud, software processes it and then might decide to perform an action, such as sending an alert or automatically adjusting the sensors/devices without the need for the user. An example to give you a better understanding is smart homes where we can control our gadgets from any corner of the house. The geysers can be turned on minutes before we are to take a shower.
There are many such areas in which IoT has facilitated its users. The travel industry, ridesharing industry, movies, eCommerce, and even disaster management require the assistance of the Internet of Things.
So, moving ahead with a better understanding of IoT, we will now look at the role of IoT in the Manufacturing Industry.
IoT has multitudes of applications in manufacturing plants. It can facilitate the production flow in a manufacturing plant, as IoT devices automatically monitor development cycles, and manage warehouses as well as inventories. It is one of the reasons investment in IoT devices has increased over the past few decades.
“Smart homes and other connected products won’t just be aimed at home life. They’ll also have a major impact on business. And just like any company that blissfully ignored the Internet at the turn of the century, the ones that dismiss the Internet of Things risk getting left behind.”
– Jared Newman, Tech Journalist
5 Ways in which IoT is being used
Digital Twins is the concept of creating a replica of the developing product in digital form. Whereas, by retrofitting sensors, industries gather data about their product’s entire working mechanism and the output expected from each module. The data collected from the digital replica is used by the managers to analyze the efficiency, effectiveness, and accuracy of the system.
Any shortcomings in the final product increases the burden on the employees and also increase the expenditures. Digital twins also help to identify such shortcomings and eliminate them to get a better version of the product. Lastly, digital Twins streamline operations like asset management and failure management. It supports industries in forecasting the completeness of their baseline and successfully get the work done before the deadlines.
Supply chain management is one of the most important things to look after in the production cycle. IoT devices are used by industries to track inventories on a global scale. Industries use IoT to monitor their supply chain and thud get meaningful estimates of the available resources. The estimates include information regarding the undergoing work, equipment collection, and the delivery date of required materials.
IoT devices also eliminate the need for manual documentation for operations and introduce Enterprise Resource Program (ERP). They avail the facility of having cross-channel visibility into managerial departments and help the stakeholders in examining the undergoing progress. It reduces the expenditure due to mismanagement and lack of analysis in the organizations.
Manufacturing of products requires the operations of big machines. Machines can fail and that may lead to quality alteration of the produce. To fix the issues with the machines is time and labor-consuming. The consolidation of IoT and machine learning enables machines to deduct issues and fix them on their own. It enables the machines to auto-heal using the self-automated healing systems and regains control whenever a downtime occurs.
The embedded sensors notify the production team about the underlying issues. The automated system saves manual efforts and reduces time consumption as well. This way it provides the freedom to the production unit to concentrate on other critical issues. Self-dependant systems provide resilience to industries and help them boost their productivity as well as to achieve a faster time to market.
IoT can help interlink the Market Ready Solutions(MRS) and the enterprise management systems. It helps industries to automate the control of IoT-enabled manufacturing activities that are executed in workshops. With the use of IoT, industries can access, identify, and control the manufacturing execution process. It allows the industries to cover everything from the start of production to the delivery of the final product. The data from IoT-enabled manufacturing layers are utilized by the production unit as the product-related input for the industry. IoT devices enable enterprises to rightly addresses the issues related to connection, computing, and control.
IoT can help industries to lessen the wastage of water by providing smart pumping solutions. Sensors embedded in the water tanks would regulate the pressure and control the flow of water. The predefined metrics would direct the pumps to automatically turn off. Along with this, they also bring real-time data that is used by the industries to monitor the performance. IoT technology helps industries to reduce electricity expenses, save manual labor, and achieve maximum productivity with efficient use of water. IoT-enabled pumping systems enable industries to install a connected, flexible, and efficient pumping system.
“With the IoT, we’re headed to a world where things aren’t liable to break catastrophically – or at least we’ll have a hell of a heads’ up. We’re headed to a world where our doors unlock when they sense us nearby.”
-Scott Weiss, Former CEO IronPort Systems
Use of IoT in different sectors
So, these are the areas in which IoT contributes and eases the job of manufacturers. The use of IoT is not only the manufacturing industry but it has extended its root in almost every sector. An IDC forecast expects global IoT spending growth rate to return in double digits in 2021 after being severely affected by the COVID-19 pandemic. They expect it to achieve a compound annual growth rate (CAGR) of 11.3% over the 2020-2024 forecast period.
IoT facilitates many sectors and the manufacturing industry is the prime beneficiary of it. In the coming days, the reliance on technologies like IoT, AI, Big Data will increase and almost every sector will seek the use of these.
Reliance Jio and JioMart: Marketing Strategy, SWOT Analysis, and Working EcosystemREAD MORE
6 Major Branches of Artificial Intelligence (AI)READ MORE
Top 10 Big Data TechnologiesREAD MORE
8 Most Popular Business Analysis Techniques used by Business AnalystREAD MORE
7 types of regression techniques you should know in Machine LearningREAD MORE
Introduction to Time Series Analysis in Machine learningREAD MORE
What is the OpenAI GPT-3?READ MORE
How Does Linear And Logistic Regression Work In Machine Learning?READ MORE
Deep Learning - Overview, Practical Examples, Popular AlgorithmsREAD MORE
7 Types of Activation Functions in Neural NetworkREAD MORE