Artificial intelligence, big data, and machine learning are among the digital technologies that are becoming increasingly significant in the industrial industry. Sandvik has collaborated with IBM on a number of digital important initiatives.
What will be the influence of digital activities on traditional manufacturing?
Industry 4.0 integration has begun at Sandvik in order to improve the efficiency of its manufacturing operations. Dormer Pramet, a global cutting-tool manufacturer under the Sandvik brand, is collaborating with IBM, one of the world’s premier data analytic organisations, on a number of important initiatives.
Using large amounts of data to map the value chain throughout every department of our production unit in Sumperk, Czech Republic, and incorporating computer software to identify defects in tools during the early stages of manufacture are two examples, according to Radim Bullawa, Dormer Pramet’s Industry Engineering Manager.
With respect to the first project, powerful algorithms and statistical approaches were utilised to track every indexable product order placed over the course of two years, determining how the item travelled through the production unit, and generating a network model of the entire factory.
Machines that communicate with one another
This model depicted how the machines interacted with one another and demonstrated how any process interruption, such as unscheduled machine downtime, can propagate throughout the entire system to other machines. In the words of Radim Bullawa, “it highlighted important points in the process where little inefficiencies might lead to big inefficiencies later.” “All were ranked by severity to assist in focusing on the areas where modifications were required to enhance performance and have the most impact,” says the author.
All of these digital aspects and projects are intended to raise the bar on our already excellent manufacturing standards.
During the second phase of the project, they looked at the definition of metrics that could be used to quantify concerns such as quality, maintenance downtime, and compliance with the production plan, among other things. These metrics were re-examined in order to find further areas for operational improvement and to make specific recommendations.
Inserts for scanning
While this is going on, Dormer Pramet is employing an IBM inspection station, which has been integrated into a pressing machine, to scan inserts with a system of cameras, lights, and mechanical elements that move. This occurs during the early phase of the manufacturing process and can aid in the improvement of the quality of the company’s products at the very beginning of the production process.
Using automatic machine image recognition, we can locate and identify the type of fault, as well as the degree of the issue,” Bullawa continued. “This detection makes use of artificial neural networks, which are a computerised model whose performance improves with time. As a result, the success of the system is dependent on the accuracy of recognition.”
The quantity of faulty photos that are entered into the system, as well as the diversity of those images, have an impact on the accuracy of the system. Making use of as many instances and as much information as possible will help to consistently train the machine what is correct and what is incorrect on a certain product or service. This not only improves the accuracy of recognition, but it also aids in the detection of less evident flaws, as well as the reduction of false alarms and the identification of problematic traits.
In Bullawa’s words, “all of these digital features and projects are intended to strengthen our existing high standards of manufacturing capabilities, which are built on a century of experience and competence.” The company says it would utilise the funds to further improve its manufacturing processes, improve the quality of its cutting tools, decrease waste, and improve the service it provides to consumers.
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