Address More Manufacturing Challenges with Composite and Metal 3D Printing

whitePaper | March 9, 2022

The nine pillars of Industry 4.0, originally outlined by Boston Consulting Group (BCG) in 20151 and summarized below, are the technological advancements that make the Fourth Industrial Revolution possible. They bring together the physical and digital human and machine. Many of these technologies have been used in manufacturing for some time, but it’s their convergence that makes Industry 4.0 a reality.

whitePaper | January 1, 2020

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whitePaper | July 26, 2023

In recent years, considerable progress has been made in the field of amorphous metals, also known as metallic glasses. Here, new insights were gained into the composition of alloys in order to achieve a better glass forming ability and thus enable larger components. While the first amorphous alloys usually consisted of two elements, the currently most promising amorphous alloys often consist of four to five elements. Occasionally zirconium-based alloys show the best glass-forming ability, with which the largest component dimensions can be realized.

whitePaper | December 14, 2021

This paper provides insight and analysis based on research and survey data on the evolving automotive supply chain and the emergence of smart manufacturing associated with industry mega trends, in particular the escalating shift to electric vehicles (EV). The automotive industry is the crucible for so many of the fundamental changes that are taking place in manufacturing because of technology convergence.

whitePaper | July 7, 2022

Production scheduling primarily deals with arranging different jobs in various machines based on the timelines for each job. There can be numerous combinations of schedules possible. Production schedules can be designed to maximize the capacity utilization, minimize idle time of the machine, earliness, overall costs etc. Manual design of a schedule can be a tedious and time consuming task. There are a lot of dependencies which the scheduler needs to tweak based on a single change. Generating a production schedule targeting a specific objective function can be done using mathematical models. Mathematical models involve formulating the production scheduling problem as an optimization model wherein there is a certain objective function which needs to be optimized based on a set of constraints. Mathematical models generally outperform manually designed schedules which involve a lot of inter-dependencies among the jobs. Due to improvement in computational power, developing a production schedule using mathematical models is relatively quick and efficient.

whitePaper | November 12, 2022

Since the first Industrial Revolution, the manufacturing process has been revolutionised from water and steam-powered machines to electrical and automated ones. The term "Industry 4.0" or simply I4 was introduced by the German government in 2011, which encourages the use of modern technology in the manufacturing process. It defines that automation technology can be improved by offering different methods of self-configuration, self-optimisation and self-diagnosis. The fourth era of revolution (Industry 4.0) is all about connectivity trends, advanced material, processing technology, service orientation and collaboration in advanced manufacturing networks. It presents a unique level of control and coordination over the whole value chain of the products. Internet of things (IoT) and machine to machine communication (M2M) are merged to improve communication and automation. It creates a new set of design principles for effective and computerised control of the manufacturing process which includes