Speed design time and streamline manufacturing with Solid Edge Sheet metal

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 | May 20, 2022

In today’s Industry 4.0-driven market, companies strive to meet customers’ needs and offer the most competitive and valuable solutions while being efficient and reducing costs. To face this challenge, manufacturers need to leverage the advantages of digital transformation.

whitePaper | November 15, 2022

The need for modernization based on digital capabilities is evident in almost all areas of the manufacturing enterprise today – not just on the shopfloor, but also in the sales, planning, engineering, and service functions. Significant shifts are underway in the manufacturing industry driven by world events as well as technology. This paper discusses these shifts in the industry along with key business and technology capabilities manufacturers need today to navigate this disruption and stay competitive. It also shows how Infosys Discrete Manufacturing Solution can empower manufacturers with these capabilities.

whitePaper | August 12, 2020

For industrial machinery and equipment manufacturers, delivering personalized, unique products is the key to doing business in an increasingly competitive environment. Read this best practice guide to learn how you can increase sales and reduce costs through. Facilitated configuration, quoting, order management, and customer communication utilizing CPQ automation

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 | September 30, 2022

Until 2020, progress towards digital transformation for most manufacturers was slow. But the urgency for manufacturers to make successful digital transformations escalated during the first 8-12 months of the global pandemic. As COVID-19 reshaped consumer buying behaviors, the pace jumped from a crawl to a sprint: According to one study, 85% of organizations accelerated their digital transformation initiatives in 2020.[1] Some industry observers believe we witnessed 6.5 years of digital progress in the last eight months of 2020 alone.