The truly connected factory: Supply Chain & Logistics

Over the past decade, new technologies increasingly have permeated the factory floor. Automation, always a part of manufacturing, has escalated quickly thanks to steadily greater computer processing power and data storage. At the same time, technologies like artificial intelligence, the Internet of Things connectivity, cloud computing, big data analytics, 3D printing and many others — previously complex to install and configure — have become affordable and scalable. They have found their way into industrial applications.

This rapid acceleration of digital transformation has been termed Industry 4.0: the Fourth Industrial Revolution. A major outcome of this period has been that the truly connected factory, or smart factory, is a reality. As more machines begin to communicate with each other, productivity increases. Efficiency gains and analytical tools that can predict maintenance needs improve productivity even more. But the real benefits of a smart factory reach far beyond mere productivity. They provide the ability to predict and adjust to changes, both internal and external, to offer unprecedented agility and create real competitive advantages.

While it’s easy to see how automation increases productivity by speeding up processes, streamlining product movement between machines and reducing errors, the true benefits of a smart factory come from a far broader concept.

Smart factories offer complete transparency by integrating machines, processes and people into a single, digitally connected system. Sensors constantly feed data from every element of the manufacturing process, ensuring that information reflects current conditions. It’s then integrated with supplier and customer data to create a holistic view of upstream and downstream supply chain processes.

This means that any change can be instantly recognized and addressed, whether it’s a difference in the availability of raw materials, a bottleneck in production, a shift in market demand or some other variable. And of course any necessary changes can be performed either by human intervention or autonomous decision making.

An AIMS server manages data flows and machine programs, displays real-time machine activity and continuously gathers production data. Image courtesy of ANCA

The ability of a smart factory to predict outcomes based on historical and real-time data offers endless benefits, from anticipating inventory issues to predicting quality problems and monitoring safety concerns.

One significant opportunity provided by smart factories is predictive maintenance. Until now, organizations had to choose between maximizing the life of a part, which risks its failure and subsequent machine downtime, or incurring the cost of replacing parts early, perhaps unnecessarily.
Predictive maintenance means that data gathered from connected, smart machines enables accurate prediction of when and where failures could occur, maximizing the life of parts and minimizing unnecessary downtime.