AVEVA launched Vision AI Assistant 2021, its new image classification-based analytics tool.

Machine vision technology helps factory computers recognise objects with greater accuracy and reliability, and in many cases has replaced quality inspection performed by humans. But that's not the end of the story, because advanced automation technologies like machine vision can be further enhanced with the addition of machine learning, according to a report by technology market research firm ARC Advisory Group. Machine vision systems provide object recognition capabilities and have demonstrated their cost effectiveness in inspection, measurement, scanning and object detection in manufacturing by improving consistency, productivity and overall quality. However, an underlying limitation is that these systems are generally developed to handle a limited number of cases and they do not have the ability to train when an unexpected variation occurs, explained report author Anju Ajaykumar, analyst at ARC Advisory Group. Machine learning can help solve that problem and is already being used to build greater adaptability into machine vision systems, enabling them to understand and respond appropriately to manufacturing variations.

The influence of Artificial Intelligence (AI) in smart manufacturing is growing rapidly. Artificial Intelligence, according to the ARC Advisory Group, applies to any device that perceives its environment and takes actions that maximize its chance of success toward some goal. This includes a vast range of technologies, such as traditional logic and rules-based systems, that enable computers to solve problems in ways that at least superficially resemble thinking. According to a recent Accenture Artificial intelligence (AI) research report, corporate profits will increase by an average of 38% by 2035 in large part thanks to a more advanced deployment of Artificial Intelligence into financial, IT and manufacturing applications. But at this early stage of AI implementation, is it still not clear how it will be deployed across many possible use cases.

With more than 90 percent of industrial companies wanting a simplified edge infrastructure that can be remotely managed, Stratus Technologies, a global leader in continuous availability solutions for mission-critical applications, unveiled its edge computing product strategy and direction at IoT Tech Expo, in Santa Clara, California. This strategy includes the latest version of Stratus' flagship product, ftServer, along with a preview of a converged edge system, which offers enhanced remote management services in a rugged and easy-to-deploy form factor. Ideal for users in industrial automation (IA) or in distributed enterprises deploying Industrial Internet of Things (IIoT) applications, these products simplify the continuous availability and remote management of mission-critical edge applications, whether in the data center, on the plant floor or at the network edge, saving customers time and money. By delivering a series of highly available edge compute solutions, Stratus addresses the growing need for more intelligent systems at the edge, as demonstrated by a new worldwide market report by ARC Advisory Group. In that study, 91 percent of IA users surveyed stated having better systems and connectivity at the edge will enable improved real-time decision making. Yet, more than 90 percent also indicated that, as edge computing grows, organizations will need a simplified edge infrastructure that can be remotely managed.

In 2017, McKinsey conducted a study on productivity gains driven by technology transformations, such as the steam engine, early robotic technology and advances in information technology. McKinsey sees manufacturing on the brink of the next generation of industrial automation revolution with unprecedented annual productivity growth of between 0.8 – 1.4% in the decades ahead. Advances in robotics, artificial intelligence and machine learning will match or outperform humans in a range of work activities involving fast, precise, repetitive action and cognitive capabilities. To remain competitive, complex industries need to deploy industrial automation more than ever, as intense global competition drives process industries to increase efficiency through reduced operating costs, increased production, higher quality and lower inventories. The highest priority should be to eliminate production losses caused by unplanned downtime and address a $20 billion a year problem for the process industries.

Infosys announced the launch of Infosys Mana, a platform that brings machine learning together with the deep knowledge of an organization, to drive automation and innovation – enabling businesses to continuously reinvent their system landscapes. According to the press release, Mana, with the Infosys Aikido service offerings, dramatically lowers the cost of maintenance for both physical and digital assets; captures the knowledge and know-how of people, and fragmented and complex systems; simplifies the continuous renovation of core business processes; and enables businesses to bring new and delightful user experiences leveraging state of the art technology. Over the last 35 years, Infosys has maintained, operated and managed systems with global clients across every industry. Building on this deep experience, Infosys has recognized the need to bring artificial intelligence to the enterprise in a meaningful and purposeful way; in a way that leverages the power of automation for repetitive tasks and frees people to focus on the higher value work, and on breakthrough innovation. Today's AI technologies address part of this with learning and information.