Comparative Analysis of Undercarriage Components

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 | October 1, 2021

Digitalization is changing how humans live and behave in many ways. It has a huge impact on almost all aspects of society. Just look at manufacturing. Factories have used digital applications for decades, but the impact of a new technological paradigm founded on the Industrial Internet of Things, or IIoT, and realized in the Industry 4.0 concept, is driving the world of manufacturing into a completely different playing field.

whitePaper | April 18, 2023

There is a seismic shift happening now in the manufacturing industry as it advances towards Industry 4.0. And private cellular network solutions like Private Networks and Industry Connect, provided by Ericsson, are supplying the connectivity needed to shape manufacturing into a more agile, secure, reliable, and intelligent process.

whitePaper | March 23, 2023

The fourth industrial revolution is transforming the manufacturing industry as we speak. Industry 4.0 is digitally driven, and like all other revolutions, the transformation did not happen overnight. Since the first personal computer on a factory floor in 1970s, computer-aided design has developed and matured exponentially. Strategically eective evolutionary steps has resulted in productivity and eciency gains in manufacturing. We live in the Industry 4.0 era, characterized by the digitization of manufacturing processes. Inevitably, today, information plays a significant role for an enterprise transformation. Data on how the product’s design and manufacturing information is authored, exchanged, and processed is critical to competitiveness. Information ‘silos’ for various life cycle processes are gradually connected to form a digital thread of information, envisioned to integrate and drive modern product design, manufacturing, and product support service processes.

whitePaper | July 8, 2022

Manufactured goods are placed into products in multiple verticals. For example, a battery will be placed into an electric car or a magnet into an MRI machine in a hospital. Manufacturing, therefore, covers all industrial internet of things’ verticals, from smart cities, to automated vehicles to healthcare and mining. Not to mention the factories themselves. The GIO Smart Manufacturing Working Group was established to bring these threads together and examine factories, deployments and modes of manufacturing, from batch-size-one to discrete manufacturing and continuous-process manufacturing. Our focus so far has been in the factory, which will be discussed throughout this paper

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.