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Designing the Rise of the Smart Machines

National Instruments : 12 June, 2013  (Technical Article)
Smart machines are systems that not only perform repetitive tasks at soaring speeds and high accuracy rates, but also adapt to changing conditions and operate more autonomously than ever before. The subject of debate ranges from the fear of humans losing low and middle-skilled jobs to smart machines, all the way to the hope that intelligent factories will spark the resurgence of manufacturing in advanced countries. Christian Fritz, Embedded Systems Senior Product Marketing Manager of National Instruments explains.
Designing the Rise of the Smart Machines

Like generations of technologies before, smart machines will impact almost every domain of life. They will alter how we produce goods, how doctors perform surgeries, how logistics companies organize storage, and even how we educate future generations.

While research institutes, economists, and the media question the impact of machines infused with IT technology, engineers and scientists must provide manufacturing systems that offer a dramatically increased level of flexibility. Super versatile machines make it possible for the manufacturing industry to satisfy society’s hunger for product variety and deal with the ever-decreasing lifecycles of consumer goods.

Characteristics of a Smart Machine

Machine and device builders have switched from designing single-purpose machines to creating multipurpose machines that address today’s manufacturing needs: smaller lot sizes, customer-specific variations of products, and the trend toward highly integrated products, which combine a lot of different functionality in one device.

Capable of operating more autonomously than ever before, modern machines can prevent and correct processing errors that are caused by disturbances like changing conditions in the raw material, the drift of the thermal working point, or the wear and tear of mechanical components. An extensive network of sensors provides smart machines with information about the process, the machine condition, and their environment, so the machines can work side by side with humans, which improves uptime and provides an increased level of quality. Additionally, these systems have the capability to improve their performance over time and learn new skills through mining data, leveraging simulation models, or applying application-specific learning algorithms.  

Last but not least, machines exchange information with other automation systems and provide status updates to a higher level control system. This collaboration between machines creates a smarter, intelligent factory, making it possible for an entire automation line to adjust for changing conditions, balance the workload between machines, and inform service personnel of errors  before a machine fails.

A Smart Approach to Machine Design

To make your next machine smarter and address manufacturing requirements, you need to design highly modular systems that you can extend to satisfy customer-specific requests. Modular systems feature machines that you can adapt on-site for different manufacturing processes and product variations—sometimes even without the need of operator interaction. While you can use this approach to develop reusable components that you implement across a variety of machines to simplify the integration of off-the-shelf subcomponents, it significantly changes the way OEMs conduct system design.

The modularity needs to be reflected in the control system architecture. Rather than leveraging a traditional monolithic system, modern machines are based on a network of control systems that rely on a seamless communication infrastructure. This infrastructure can handle time-critical as well as lower priority data and deliver status information to a supervisory system. To handle the increased complexity of distributed embedded systems, machine builders adapt a software-centric system design approach.

Today, NI LabVIEW graphical programming helps leading machine builders master increasing system complexity. With add-on modules for motion control, machine vision, and control design and simulation; features for machine prognostics and condition monitoring; and extensive support for I/O hardware and communication protocols, LabVIEW helps you consolidate your development toolchain and further streamline the design process.

Selecting hardware for machine control systems can be a daunting task. Often a system engineering department needs to weigh the ease of use and low risk of black-box solutions with the performance and price benefits of a custom embedded system. By considering this, you can build differentiated features that determine whether your machine succeeds or fails in the marketplace. Since custom solutions usually drive design teams out of their comfort zones, the teams lean toward traditional solutions knowing this might limit their capability to add differentiating smarts to their machines.

The LabVIEW reconfigurable I/O (RIO) architecture offers a hybrid approach: a fully customisable off-the-shelf platform, utilising programmable FPGAs that provide access to a range of existing I/O modules from National Instruments and third-party vendors. Using the features and IP of the LabVIEW FPGA Module, machine builders can focus on the design and optimization of their custom algorithms rather than spending weeks or months on hardware design or having to rely on a third-party company to design yet another more application-specific black-box embedded solution. Custom I/O frontends and board-only versions based on the same architecture offer an additional level of flexibility.

To give machine builders a head start, NI offers a design guide covering a variety of smart machine topics. From common architectures for distributed machine control systems to motion vision integration, to advanced control strategies, the guide comprises best practices, technology overviews, and customer examples to help you design smarter systems for the intelligent factory and get ahead of the competition.

Further Reading

The Control Design Guide for Smart Machines

The Smart Machine Webcast Series

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