HP Metal Jet technology

whitePaper | July 31, 2022

Additive Manufacturing (AM) developments go back several decades, but stereolithography was the first commercial use of AM in the late 1980s using polymeric materials, and was widely used initially in the automotive industry sector. The aerospace industry adopted AM in the mid-1990s using polymer AM parts for non-structural production applications, and there are now a multitude of AM parts on commercial aircraft such as air ducts, brackets, and clips.

whitePaper | April 28, 2022

The growing trade friction between Western countries and China encompasses numerous products and industries, but few more critical than semiconductors. Essential to all electronics manufacturing, the semiconductor industry has been in upheaval since the start of the pandemic and, given the industry’s concentration in Taiwan and downstream dependence on China, is likely to remain of subject of concern for the foreseeable future.

whitePaper | August 1, 2020

The latest generation of scanCONTROL 30xx laser scanners is extremely powerful, precise and individually adaptable. The scanners are used for high-precision 2D / 3D profile and gap measurements in automation, production monitoring and quality control. For demanding surfaces such as red-hot objects or transparent objects, the patented blue laser scanners are ideally suited. This White Paper shows various applications examples and explains more about the benefits of high performance scanners.

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 | January 12, 2022

Henry Ford’s visionary ideas and inventions well outlived him: the assembly line made its way from Industry 3.0 to Industry 4.0, where it became more “connected” and efficient.In this white paper, we explore how cutting-edge technologies such as machine learning (ML), artificial intelligence (AI), computer vision, and cognitive systems can be fine-tuned to support mass personalization and add a much-needed human touch to production (and beyond).

whitePaper | May 13, 2023

Across every major industry segment, the application of advanced digital technologies and Industry 4.0 capabilities offers manufacturers powerful new capabilities to enable flexible production, improved product quality and real-time insight into the performance of their operations. However, these factories and production lines aren’t built by themselves. Designing, engineering and building these advanced systems demand intense investment in time, resources and know-how to solve some of the world’s most complex technology challenges.