We only need to look toward prominent Industry 4.0 models to see how artificial intelligence (AI) is impacting the future of manufacturing. It's baked into the roadmap and is arguably a vital part of the end state. Artificial intelligence can ingest a combination of data from sensors, machines, and people and then apply it to algorithms designed to optimize operations or achieve lights out manufacturing. Back in reality, we have some time before leading organizations achieve this pinnacle state of manufacturing, let alone the industry as a whole. Only about 9% of manufacturing organizations are leveraging Artificial Intelligence today.

In this special guest feature, Stuart Gillen, Senior Manager at Kalypso, offers a few ways manufacturing organizations can leverage predictive maintenance to identify potential issues, reduce the occurrence and length of unplanned downtime, and get the most value from assets and budgets. Stuart is a proven leader passionate about AI and able to successfully work through the hype to provide clients actual implementation in IoT and Machine Learning projects which provide true business value and positive ROI. His areas of specialty include IoT architectures, platforms, and technologies. With testimonial success applying leading innovation capabilities, Stuart has a unique perspective on how clients can enhance their creative aptitude and maximize their return on innovation investments.. As manufacturers become increasingly connected, their systems, machines, sensors and other devices are generating a wealth of new data, and given the sheer volume of data generated, that isn't easily analyzed.

Before getting into the details of deep learning for manufacturing, it's good to step back and view a brief history. Concepts, original thinking, and physical inventions have been shaping the world economy and manufacturing industry since the beginning of the modern era, i.e. early 18th century. Ideas of economies-of-scale by the likes of Adam Smith and John Stuart Mill, the first industrial revolution and steam-powered machines, electrification of factories and the second industrial revolution, and the introduction of the assembly line method by Henry Ford are just some of the prime examples of how the search for high efficiency and enhanced productivity have always been at the heart of manufacturing. However, almost all of these inventions centered around extracting the maximum efficiency from men and machines by carefully manipulating the laws of mechanics and thermodynamics. For the past few decades, however, the greatest new gains in manufacturing have come from adding the concept of information or data into the existing mix.

There have been countless changes in technology over the past couple of decades: Machine Learning, Cloud Computing, Internet of Things, Artificial intelligence, and Augmented Reality (to name a few). But with all of these advances in technology, the 350 million workers in manufacturing are being asked to perform increasingly complex jobs using technology that has remained relatively unchanged for 20 years. Whether this is because enterprise software solutions are expensive, technically complex, difficult to implement, or lack continuous improvement opportunities, these users and processes have been underserved. Although there has been a recent trend towards a digital transformation that looks at applying new technologies to improve operational processes, the workers who actually perform these processes are not being considered. Because of this, the frontline worker is largely disconnected from the digital thread of the business and improvement in productivity seems stagnant.

The era of digital transformation is upon us – from exciting new technologies in digital manufacturing to powerful new opportunities to create meaningful connections with customers through the Internet of Things (IoT), digital transformation is changing all aspects of the manufacturing business. And, it has the potential to disrupt every part of the enterprise. But let's take a moment to pause. How do you describe the digital transformation in a manufacturing organization? At its core, digital transformation refers to the use of technology to improve business results.

The era of digital transformation is upon us – from exciting new technologies in digital manufacturing to powerful new opportunities to create meaningful connections with customers through the Internet of Things (IoT), digital transformation is changing all aspects of the manufacturing business. And, it has the potential to disrupt every part of the enterprise. But let's take a moment to pause. How do you describe the digital transformation in a manufacturing organization? At its core, digital transformation refers to the use of technology to improve business results.

Information contained on this page is provided by an independent third-party content provider. If you are affiliated with this page and would like it removed please contact pressreleases@franklyinc.com BellHawk Systems Corporation announces the availability of a new white paper "The Artificial Intelligence Revolution in Manufacturing Operations Management." This white paper is available for download from the front page News section of www.BellHawk.com. This white paper describes how real-time Artificial Intelligence (AI) techniques originally developed for the USAF and NASA are being applied to manufacturing organizations to enable managers to run their manufacturing plants with less stress and much smaller management teams. It gives examples of how even small manufacturing organizations are able to use these methods to automate their planning and scheduling and for managers to be alerted whenever problems arise.