A day in the life of 2024: our vision of the factory of the future, including the people and processes that will be impacted.
Let’s start with the word “autonomous”, which means “self-governing”. Autonomous manufacturing is the manifestation of “self-governing” systems at every step of the manufacturing process.
To understand the basic principles of autonomous systems, consider a scenario in which a human driver approaches a stop sign.
To address social, political, and economic challenges, manufacturers are accelerating digital transformation efforts and prioritizing the application of artificial intelligence (AI) and machine learning (ML) to solve their complex production challenges.
In March 2020, the Pharmaceuticals industry faced one of its most public-facing and time-pressing challenges to date: develop, manufacture, and distribute a vaccine for COVID-19 globally as quickly and safely as possible. While sheer human perseverance played a pivotal role in driving the notable speed to market for the vaccine, this approach is not sustainable nor practical for commercial drug products. Digital methods and tools should be leveraged to achieve similar results in a sustainable, efficient, and profitable way. Pharmaceutical manufacturers now face the need to confront these challenges head-on and embrace connectivity across the value chain, starting with laying the digital foundation for innovation in the form of Digital Knowledge Management and Pharma 4.0.
The pharma industry’s product development processes is complex and lengthy, but digital technologies can help. Here are the top AI use cases.
While the recent economic shutdown likely caught many auto industry manufacturers off guard, it’s time to prepare for what is next. Here are some ways to minimize near-term risk and some tips for how to prepare now for a post-crisis world.
Smart factories, enabled by digital technologies and concepts, may not be as futuristic as you think. Need inspiration to get started? Here's our UPDATED vision of the factory of the future, and the people and processes that will be impacted.
Discrete manufacturers and R&D professionals have long viewed product lifecycle management (PLM) as a means to enhance manufacturing and design process management, data integrity and digital mockup. While these capabilities serve as a baseline to address operational challenges, current out-of-the-box solutions lack the maturity to maximize the value of product data and quickly tie it to business decisions.
Smart factories, enabled by augmented reality, predictive analytics, and the digital twin, may not be as futuristic as you think. Need inspiration to get started? Here's our vision of the factory of the future, and the people and processes that will be impacted.
