One of the most widely used definitions of advanced manufacturing involves the use of technology to improve products and/or processes, with the relevant technology being described as "advanced," "innovative," or "cutting edge.”
For example, one organization defines advanced manufacturing as industries that "increasingly integrate new innovative technologies in both products and processes. The rate of technology adoption and the ability to use that technology to remain competitive and add value to define the advanced manufacturing sector."
Another author defined World Class Foundry (read manufacturing) as: "A World Class Manufacturing (WCM) is one which integrates the latest-gen machinery with (process/ work) systems to facilitate 'manufacturing'- based business development governed around manufactured products only, duly based over a high accent on Product Substitution or New Product Development."
"Advanced manufacturing centers upon improving the performance of US industry through the innovative application of technologies, processes and methods to product design and production."[3] Finally, a recent survey of advanced manufacturing definitions by the White House and states: "A concise definition of advanced manufacturing offered by some is manufacturing that entails the rapid transfer of science and technology (S&T) into manufacturing products and processes." (PCAST, April 2010.) Advanced manufacturing makes things that make life easier.
The term industrial internet of things is often encountered in the manufacturing industries, referring to the industrial subset of the IoT. The industrial internet of things will enable the creation of new business models by improving productivity, exploiting analytics for innovation, and transforming the workforce. The potential of growth by implementing IIoT is predicted to generate $15 trillion of global GDP by 2030.
While connectivity and data acquisition are imperative for IIoT, they are not the end goals, but rather the foundation and path to something bigger. Of all the technologies, predictive maintenance is an "easier” application, as it is applicable to existing assets and management systems. Intelligent maintenance systems can reduce unexpected downtime and increase productivity, which is projected to save up to 12% over scheduled repairs, reduce overall maintenance costs up to 30%, and eliminate breakdowns up to 70%, according to some studies.[28] Industrial big data analytics plays a vital role in manufacturing asset predictive maintenance, although that is not the only capability of industrial big data. Cyber-physical systems (CPS) are the core technology of industrial big data and they will be an interface between human and the cyber world. Cyber-physical systems can be designed by following the 5C (connection, conversion, cyber, cognition, configuration) architecture, and they transform the collected data into actionable information, and eventually interact with the physical assets to optimize processes.
An IoT-enabled intelligent system of such capability has been demonstrated by the NSF Industry/University Collaborative Research Center for Intelligent Maintenance Systems (IMS) at University of Cincinnati on a band saw machine in IMTS 2014 in Chicago. Band saw machines are not necessarily expensive, but band saw belt expenses are enormous since they degrade much faster. However, without sensing and intelligent analytics, it can only be determined by experience when the band saw belt will actually break. The developed prognostics system is able to recognize and monitor the degradation of band saw belts even if the condition is changing, so that users can know in near real-time the optimal time to replace the belt. The developed analytical algorithms were realized on a cloud server, and were made accessible via the Internet and on mobile devices.
Integration of sensing and actuation systems connected to the Internet can optimize energy consumption as a whole. It is expected that IoT devices will be integrated into all forms of energy consuming devices (switches, power outlets, bulbs, televisions, etc.) and be able to communicate with the utility supply company in order to effectively balance power generation and energy usage. Besides home based energy management, the IIoT is especially relevant to the Smart Grid since it provides systems to gather and act on energy and power-related information in an automated fashion with the goal to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity. Using advanced metering infrastructure (AMI) devices connected to the Internet backbone, electric utilities can not only collect data from end-user connections, but also manage other distribution automation devices like transformers and reclosers.
As of 2016, other real-world applications include incorporating smart LEDs to direct shoppers to empty parking spaces or highlight shifting traffic patterns, using of sensors on water purifiers to alert managers via computer or smartphone when to replace parts, attaching RFID tags to safety gear to track personnel and ensure their safety, embedding computers into power tools to record and track the torque level of individual tightenings, and collecting data from multiple systems to enable the simulation of new processes.
References: Most of this content has been derived from Wikipedia.