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Smart Manufacturing is a broad category of idealized manufacturing optimized for agile and efficient concept generation, production, and product transaction. While manufacturing can be defined as the multiphase process of creating a product out of raw materials, smart manufacturing is a subset that employs computer control and high levels of adaptability. The goal is to generate new products, as well as optimize and reshape them, in a rapidly changing market. Smart manufacturing takes advantage of advanced information and manufacturing technologies to enable flexibility in physical processes to address a dynamic and global market. Necessarily, the workforce involved needs to be trained for such flexibility and use of the technology rather than specific tasks as is customary in traditional manufacturing.[3]

Current Technology

The broad definition of smart manufacturing covers many different technologies.  Some of the most influential technologies in the  smart manufacturing movement include big data processing capabilities, industrial connectivity devices and services, and advanced robotics.

Big Data Processing

Smart manufacturing utilizes big data analytics, to refine complicated processes and manage supply chains.[1][1] Big data analytics refers to a method for gathering and understanding large data sets in terms of what are known as the three V's, velocity, variety and volume. Velocity informs the frequency of data acquisition, which can be concurrent with the application of previous data. Variety describes the different types of data that may be handled. Volume represents the amount of data.[2] Big data analytics allows an enterprise to use smart manufacturing to shift from reactionary practices to predictive ones, a change that serves to improve efficiency of the process and performance of the product.

Advanced robotics used in automotive production

Advanced Robotics

Advanced robots, also known as smart machines operate autonomously and can communicate directly with manufacturing systems. By evaluating sensory input and distinguishing between different product configurations, these machines are able to solve problems and make decisions independent of people. These robots are able to complete work beyond what they were initially programmed to do and have artificial intelligence that allows them to learn from experience.

Industrial Connectivity Devices and Services

Leveraging the capabilities of the internet, manufacturers are able to improve integration and data storage. Employing cloud software allows companies access to highly configurable computing resources. This allows for servers, networks and other storage applications to be created and released at a rapid pace. Enterprise integration platforms allow the manufacturer to collect data broadcast from its machines, which can track metrics such as work flow and machine history. Open communication between manufacturing devices and networks can also be achieved through internet connectivity. This encompasses everything from tablets to machine automation sensors and allows for machines to adjust their processes based on input from external devices.

Benefits and Aims

Smart Manufacturing can be seen as an idealized practice in manufacturing. It involves the integration in all steps of the product fabrication process. The aim being a more harmonious development process utilizing data and innovative, intelligent technology to expedite new higher quality goods. This business practice hopes to brings a more flexible, adaptive, and reactive approach to participating in competitive markets. The idea being companies will be forced to adapt or adopt the practice to compete, stirring up the market. The expectation is that innovation and networking will be more prevalent in the process.

Smart Manufacturing can also be attributed to surveying workplace inefficiencies, assisting worker safety, and addressing environmental concerns.  An intelligent, interconnected “smart” system can be established to set a performance target, determine if the target is obtainable, and identify inefficiencies through failed or delayed performance targets. Worker safety can be augmented by safe design and leading technology already implemented by robotics and automation.