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Technologies that will revolutionize the industry are IOT, AI, AR, VR-based products or devices. Many of the industries like IT, Textile, Automobile, Chemical, and Food are also seeing how to implement this technology. It would allow them to create one unit quickly, speeding up research and taking cost effect. Specifically thinking about the manufacturing, these disruptive technologies will allow many smaller companies to enter the market. The most of the manufacturing industry needs development mainly in production, Quality control, and Inventory Management. So the thirst for development will be satisfied with these disruptive technologies.
Every manufacturing industry’s growth depends on Predictive maintenance, energy management, time and cost-effective, quality assurance, data loss, and security. Through these benefits will evolute the industry.
Customer relationship is also one of the most important things. Adapting predictive maintenance with manufacturing industry’s, companies came forward to know what and why’s in the business and can able to know many insights about the future trends. By connecting to devices and monitoring data it produces, patterns can be identified that leads to problems. By using this insight, issues came to know before they are going to happen. This type of predictions helps to optimize equipment and lessen the downtime for the organization. In addition to the earlier preventive measures, the use of predictive maintenance is called Reliability-Centered-Maintenance (RCM).
Predictive maintenance is all about the smart business. For example, if the weather forecast reported being rainy, a system for retailers automatically adjusts, and umbrella opens up. There is a platform called Alice, it is a technology by Circular Board. It is a world’s first artificial intelligence system for women entrepreneurs. By using machine language based Alice platform helps businesses to manage in a more correct way. In all departments predictive maintenance is the part of process. But mainly in the manufacturing industry predictive maintenance is much needed process because of its application is high which we have seen above. In predictive maintenance, if we may know priorly about the defect of a device, which can prevent failure and reduce maintenance cost using the latest Internet of things.
Every industry will be willing to invest in predictive analytics, because of its future scope. So the integration of predictive analytics will lead to the industry easier, they can accurately and consistently predict the future. For example, the managers want to know, which parts will be the first in line to fail, whereas the failure could be identified. The knowledge about the defect should be intimated in prior to both manufacturer and user. After the defect is confirmed, the field serviceman can be track what kind of issues? Whether there are raw materials in inventory to solve this issue. And also manufacturer can predict the user review or feedback using the sentimental analytics. Using user applied forces, vibrations and motions help to sense the feel of the user. So the manufacturer can collect the feedback from the customer using the device.
Let’s think about the above phrase, the sentimental analysis will give the raw data of user feedback to the manufacturer. Why don’t we use this technology in analyzing the worker’s stress level when they are using the machines in manufacturing industries? Yeah, there is a solution. The sentimental analysis is calculating the feeling of a person. Some popular companies gathering the user emotions and experience via Social Media like Facebook, Twitter, and Instagram. In here, the user updates his daily status about the family, workplace stress, etc. After collecting this data the companies are advising to the user. For example, Aron was working for X company, he posting the status in Facebook –“I am too stressed”. So the status is monitored by the concern, after a few times they replied to him as a text or gossip messages to cool Aron. Sentimental analysis helps to understand about stress level of employees. The Sentimental analysis helps when dissatisfaction is found – The employees do not approach the company to resolve their concern, usually they share their opinions about their work ethics through social media etc. Here sentimental analyses can help you to know about your employee’s attitude towards you and steps can be taken if they are satisfied with any policy.
Predictive maintenance in manufacturing is a depth research about the customer needs, status quo and so on. Encourage transparency and open communication – Every company expects open and honest communication among the employees, but when an organization takes corrective measures which it results in transparency and open communication. Today, company HR and recruiting firms started a sentiment analysis tool to get the opinion of the employee about their feedback. There are many employee review sites are available in many popular companies, are new trends that are used to analyze about employee’s emotion. Nowadays, companies are using predictive maintenance at a faster rate. So, this helps them to understand better and provide service for the customers.
Sentimental analysis is gradually increasing phase all manufacturing industry. Sentimental analysis over Employees will have a great impact in organization production rate increase, with data analytics it can also predict what all the parameter currently affecting the workforce and environment of employee. To reduce depression level of employee which affects the productivity can be solved now with a sentimental analysis platform which is great beneficial technology in support of companies in coming days.
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