Manufacturing business models are being disrupted by digitalization, according to a new report from Frost & Sullivan. Aided by the latest industrial networks and automation, data from factories can be acquired, stored, and assessed to gain greater operational insight.
Automation of the shop floor is on the front lines of this transition. A reimagining of all facets of automation is ongoing, from design to engineering and from deployment to operations. Trends such as the artificial intelligence (AI), edge computing and augmented reality (AR) were identified by Frost & Sullivan as factors that strongly influence automation:
- AI has the potential to transform human-centered engineering models into automated systems, facilitating continuous operational learning and productivity gains that exceed existing approaches
- Edge computing expands PLC functionality by providing additional computing resources, power and personalized operational needs
- AR will become the HMI of the future, offering superior insight into controllers, machines and processes.
AI opens the door to machines that can sense, process and act in some ways like humans. It encompasses natural language processing, image/object/sound recognition and problem-solving. Machine learning is a subset of AI. It conveys the ability of a system (or a machine) to learn without being programmed explicitly. This is achieved via training algorithms to learn about context that can then assist AI in sifting through massive amounts of data with speed and accuracy.
A PLC or an industrial PC armed with AI, then, would be capable of learning from production data sets and devising operational programs that are both robust and flexible. Such technology helps to make sense of the huge troves of data that are being made available by ongoing digitalization initiatives. By taking what used to be isolated siloes of information and making it broadly available to other systems, AI has become a vital ingredient in gleaning insight and competitive advantage from organizational information.
Industrial IoT is transforming how data is generated, gathered and analyzed. The old model of transmitting everything to a central repository or sending data through a business intelligence is becoming increasingly difficult as there is simply too much information around. Efforts to shunt everything to one location is clogging networks and slowing operations. The solution is an emerging infrastructure of edge devices including next-gen controllers such as PLC and DCS.
What is meant by “edge” is that sufficient compute power and controller functionality exist exactly where they are needed – where the information is generated at the edge of the network. For example, a remote switch can be provided with enough intelligence and compute power to process routine functions locally rather than transmitting everything over WiFi or Ethernet to a decision-making system at head office. This frees up centralized resources to work on AI-related analytics and other functions.
Thus, it has become increasingly necessary to gather, store and process data at the source of data generation, while also controlling related manufacturing processes that may be taking place in the vicinity. By distributing some business processes such as analysis, control and decision-making to the network edge, the enterprise as a whole can become far more efficient.
Of course, some data will continue to be transmitted to central systems. But this might only be summarized data or key parameters. The combination of edge and centralized computing will play an important role in achieving the dream of manufacturing automation and real-time analysis of data. Supplementary benefits include reduced latency and greater security.
AR brings together the digital and the real world. By augmenting the real world with insights from the virtual world, those on the shop floor and engaged in monitoring processes or maintaining systems can be aided in seeing more than what is obvious and improve decision-making. This will add enormous value to factory and process automation.
How does it work? AR, facilitated by digitalization, superimposes digital information on top of physical assets in the real world via goggles, visors, glasses and other mechanisms. The benefits include:
- AR can help manufacturers to automatically assess the quality of manufactured goods by comparing them against standard instructions
- Operators and factory personnel can access work instructions in real time and visualize process outcomes
- Industrial users can act on data and insights delivered by analytics in real time.
- Maintenance personnel can be guided in their tasks, either via step-by-step instructions, or by being able to see clearly which valve, actuator or controller component requires service or replacement.
- AR-based HMI systems can help operators see the outcome of a specific response, aiding in measuring and improving real-time decision making on the ground.
- AR can facilitate a remote operations approach whereby domain experts provide expertise remotely to less-trained shop floor personnel who carry out the actual work.
With the convergence of advanced technologies such as AI, AR and edge computing, industrial automation is expected to go through a phase of explosive growth in the coming years. To read the entire paper, The Future of Automation: A Primer, please click here.Have an Inquiry for Siemens about this article? Click Here >>