Huawei Wireless Factory Solution for Manufacturing

whitePaper | June 28, 2022

Enhancing product development using HPE systems powered by AMD EPYC processors with AMD 3D V-Cache technology

whitePaper | February 23, 2022

Fully automated assembly lines with industrial robots are highly efficient, fast and precise – as long as they are in operation. When unplanned downtimes occur, the economic damage can be immense within just a matter of minutes. Prevention is better than repair. Using high-performance lubricants during regular maintenance of industrial robots prevents unscheduled downtimes, optimizes the robotics and maximizes the uptime of the assembly line. In this white paper, you will learn more about the right lubrication for your industrial robots.

whitePaper | November 30, 2022

The promise of metal additive manufacturing (AM) to completely transform how core parts are produced has largely been just that: a promise. The ability to 3D print parts has been deployed across countless industries, but limitations within conventional iterations of metal AM have relegated the technology to use primarily in prototyping or niche use cases.

whitePaper | September 15, 2023

Global megatrends are creating increasingly frequent disruptions to economies and organizations, which in turn are reshaping global value chains and pushing industries and manufacturing to transform themselves. These megatrends include geopolitical tensions and economic instabilities, climate change, technology integration and changing people dynamics.

whitePaper | June 20, 2022

It is almost cliché that the automotive industry is undergoing transformational change. Perhaps not since the Model T first revolutionized the industry has so much change come so quickly. Driving this evolution is the unstoppable momentum of a Connected, Automated, Shared, and Electrified (CASE) driven digital transformation, which is upending established norms and re-imagining the industry from the inside out. Linear, product-focused business models built on structured data are being replaced by collaborative, data-driven business ecosystems incorporating a broad group of traditional and non-traditional stakeholders and data types. The new value creation frontier is a differentiated, highly-curated, personalized customer experience.

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.