Posted by Ashwin Patil on June 22, 2017
Things are just starting to pop in the world of manufacturing, aren’t they? Digitization and connectivity are forging the way ahead. Advanced manufacturing techniques combined with the Internet of Things are creating a digital manufacturing enterprise that communicates, analyzes and uses information to drive intelligent action back in the physical world. Supply chains are shifting from linear, sequential operations to an always-on, interconnected, open system of supply operations called a digital supply network (DSN), and traditional silos are breaking down. The changes are driven in part by three key developments: lower computing costs, cheaper storage, and less costly bandwidth. These cost declines over the last few decades have made it possible for companies to invest less and still realize the benefits of digital technologies on a wider scale. We’re now at a time where manufacturers shouldn’t ignore the trend or they may risk falling behind as the industry begins widespread adoption.
Applying innovative capabilities to digitize supply networks involves a continuous flow of information, between physical and digital worlds. The lowered cost of computing, storage and advances in high speed connectivity have enabled disruptive technologies, including big data processing, sensors and artificial intelligence (AI), to capture a wider variety of digital signals and data from the physical world than ever before. These digital records are made available along with the entire production system and are used with predictive algorithms that are able to produce real-time insights with amazing accuracy and speed. And that window of insight can be acted upon immediately within the physical world as people along the supply chain make better decisions and take a variety of actions that showcase stronger results. It’s a constantly evolving loop. Here’s an example of how it can work.
Data, decisions, more data, all digitizing supply networks
Through the use of cognitive and concurrent planning, managers can forecast, plan and instantly react to changes across the DSN. It starts with outfitting the factory floor, engineering components and finished goods with sensors projecting information on supply chain positions across the production and logistics processes. Data can be shared with suppliers so they see the latest production schedules and engineering changes. As engineers adjust the components’ specifications, new work instructions automatically update the production line, and the end product is ready for shipment. Unlike a traditional supply chain model, digital supply networks are dynamic, integrated and have a high-velocity, continuous flow of information and analytics. The data impacts decisions. The decisions impact what’s happening on factory floors. New data is created and the cycle repeats, often getting smarter along the way with machine learning capabilities at the helm.
Technologies forging the revolution
The flows of information and movement between the digital and physical worlds are made possible by employing several integrated DSN technologies, such as:
- Sensors. Because sensors are generally becoming less expensive, smarter, and smaller, they can be a viable solution for businesses seeking a wide range of data at lower costs. For example, managers can watch in real time as customer usage data is electronically transformed into information useful for decision-making.
- Wi-Fi. Without Wi-Fi, this revolution would likely be at a standstill. Connected devices communicate with a centralized computer over the Wi-Fi network, so they can share the necessary information to improve operations.
- Signals. Signals are packets of information produced by the network. These massive data sets are used to predict outcomes. They are found in a variety of sources, including the streams of data produced by sensors; an organization’s operational, factory, manufacturing, financial and transactional systems; as well as in external partner and supplier data sources; and unstructured sources such as social media and websites. The ability to detect and harvest signals hidden in data flows—and to act on that information—can produce answers, actions, and competitive advantages.
- Edge computing analytics. Algorithmic and visualization routines are used at the edge, close to the source of signals, to identify root errors and drive process improvements in near real time.
- Big data and cloud computing. Big data applications such as Hadoop distributions combined with cloud computing helps make this revolution more economical. Hadoop and derivative technologies help make massive parallel processing and data storage more affordable. While cloud vendors invest in and maintain the cloud infrastructure supporting the big data technologies; a user only pays for the resources and applications he or she uses.
- Intelligent workflow automation. AI and machine learning work together to help organizations address their most vexing challenges by continuously learning from available data streams, then integrating answers into decision-making processes and real-time workflows. Intelligent automation systems sense and synthesize vast amounts of information and automate entire processes or workflows, learning and adapting as they go. The advances in cognitive computing are making automation possible in ways not dreamed of even a few years ago.
The future of business is here
More agile, intuitive and responsive information technology can help meet business needs today while laying the foundation for tomorrow. No longer does it have to be prohibitively expensive or time-intensive to gain insight into each operation’s step, or to deeply understand customer or supplier demand patterns. Companies with leading supply chain capabilities are using advanced analytics at every point of their supply chain to help improve forecasts, demand planning, sourcing, production and distribution. In its simplest form, a DSN tracks objects in the real world to feed a digital world of algorithms in mass so that humans can affect again what’s happening in the real world for the better, both in real time as well as offline for truly transformative change. Physical to digital. Digital back to physical. The collaborative relationship between machines and humans creates a continuous and bidirectional loop of learning, and just like that, a revolution is born that will impact the shape of manufacturing and supply chains forever. Don’t be left behind!