A distributed control system (DCS) is a computerised control system for a process or plant usually with many control loops, in which autonomous controllers are distributed throughout the system, but there is no central operator supervisory control. This is in contrast to systems that use centralized controllers; either discrete controllers located at a central control room or within a central computer. The DCS concept increases reliability and reduces installation costs by localising control functions near the process plant, with remote monitoring and supervision.
Machine to machine (M2M) is direct communication between devices using any communications channel, including wired and wireless. Machine to machine communication can include industrial instrumentation, enabling a sensor or meter to communicate the information it records to application software that can use it. Such communication was originally accomplished by having a remote network of machines relay information back to a central hub for analysis, which would then be rerouted into a system like a personal computer.
Shimon Y. Nof is a professor of Industrial Engineering at Purdue University in West Lafayette, Indiana. He has held visiting positions at the Massachusetts Institute of Technology and at universities in Chile, the European Union, Hong Kong, Israel, Japan, Mexico, Philippines, Taiwan, and UK. He is the Director of the Production, Robotics and Integration Software for the Manufacturing & Management (PRISM) Center at Purdue.
The following outline is provided as an overview of and topical guide to manufacturing:
A unidirectional network is a network appliance or device that allows data to travel in only one direction. Data diodes can be found most commonly in high security environments, such as defense, where they serve as connections between two or more networks of differing security classifications. Given the rise of industrial IoT and digitization, this technology can now be found at the industrial control level for such facilities as nuclear power plants, power generation and safety critical systems like railway networks.
The Internet of things (IoT) describes devices with sensors, processing ability, software and other technologies that connect and exchange data with other devices and systems over the Internet or other communications networks. The Internet of things encompasses electronics, communication and computer science engineering. Internet of things has been considered a misnomer because devices do not need to be connected to the public internet, they only need to be connected to a network, and be individually addressable.
The Advanced Learning and Research Institute (ALaRI), a faculty of informatics, was established in 1999 at the University of Lugano to promote research and education in embedded systems. The Faculty of Informatics within very few years has become one of the Switzerland major destinations for teaching and research, ranking third after the two Federal Institutes of Technology, Zurich and Lausanne.
A smart object is an object that enhances the interaction with not only people but also with other smart objects. Also known as smart connected products or smart connected things (SCoT), they are products, assets and other things embedded with processors, sensors, software and connectivity that allow data to be exchanged between the product and its environment, manufacturer, operator/user, and other products and systems. Connectivity also enables some capabilities of the product to exist outside the physical device, in what is known as the product cloud. The data collected from these products can be then analyzed to inform decision-making, enable operational efficiencies and continuously improve the performance of the product.
EMS Technologies was an Atlanta-based company with approximately $290 million in annual sales revenue before its 2011 purchase by Honeywell International. EMS-T specialized in wireless, defense, and space communications systems.
A cyber-physicalsystem (CPS) or intelligent system is a computer system in which a mechanism is controlled or monitored by computer-based algorithms. In cyber-physical systems, physical and software components are deeply intertwined, able to operate on different spatial and temporal scales, exhibit multiple and distinct behavioral modalities, and interact with each other in ways that change with context. CPS involves transdisciplinary approaches, merging theory of cybernetics, mechatronics, design and process science. The process control is often referred to as embedded systems. In embedded systems, the emphasis tends to be more on the computational elements, and less on an intense link between the computational and physical elements. CPS is also similar to the Internet of Things (IoT), sharing the same basic architecture; nevertheless, CPS presents a higher combination and coordination between physical and computational elements.
MTConnect is a manufacturing technical standard to retrieve process information from numerically controlled machine tools. As explained by a member of the team that developed it, "This standard specifies the open-source, royalty-free communications protocol based on XML and HTTP Internet technology for real-time data sharing between shopfloor equipment such as machine tools and computer systems. MTConnect provides a common vocabulary with standardized definitions for the meaning of data that machine tools generate, making the data interpretable by software applications." A simple, real-world example of how this tool is used to improve shop management is given by the same author.
"Fourth Industrial Revolution", "4IR", or "Industry 4.0" is a buzzword neologism describing rapid technological advancement in the 21st century. The term was popularised in 2016 by Klaus Schwab, the World Economic Forum founder and executive chairman, who says that the changes show a significant shift in industrial capitalism.
An intelligent maintenance system (IMS) is a system that utilizes collected data from machinery in order to predict and prevent potential failures in them. The occurrence of failures in machinery can be costly and even catastrophic. In order to avoid failures, there needs to be a system which analyzes the behavior of the machine and provides alarms and instructions for preventive maintenance. Analyzing the behavior of the machines has become possible by means of advanced sensors, data collection systems, data storage/transfer capabilities and data analysis tools. These are the same set of tools developed for prognostics. The aggregation of data collection, storage, transformation, analysis and decision making for smart maintenance is called an intelligent maintenance system (IMS).
The Industrial Internet Consortium rebranded as the Industry IoT Consortium in August 2021. The Industry IoT Consortium is a program of the Object Management Group (OMG).
A digital twin is a digital model of an intended or actual real-world physical product, system, or process that serves as the effectively indistinguishable digital counterpart of it for practical purposes, such as simulation, integration, testing, monitoring, and maintenance. The digital twin has been intended from its initial introduction to be the underlying premise for Product Lifecycle Management and exists throughout the entire lifecycle of the physical entity it represents. Since information is granular, the digital twin representation is determined by the value-based use cases it is created to implement. The digital twin can and does often exist before there is a physical entity. The use of a digital twin in the creation phase allows the intended entity's entire lifecycle to be modeled and simulated. A digital twin of an existing entity may be used in real-time and regularly synchronized with the corresponding physical system.
Asif Jamal mansooriIndustrial big data refers to a large amount of diversified time series generated at a high speed by industrial equipment, known as the Internet of things. The term emerged in 2012 along with the concept of "Industry 4.0”, and refers to big data”, popular in information technology marketing, in that data created by industrial equipment might hold more potential business value. Industrial big data takes advantage of industrial Internet technology. It uses raw data to support management decision making, so to reduce costs in maintenance and improve customer service. Please see intelligent maintenance system for more reference.
Smart manufacturing is a broad category of manufacturing that employs computer-integrated manufacturing, high levels of adaptability and rapid design changes, digital information technology, and more flexible technical workforce training. Other goals sometimes include fast changes in production levels based on demand, optimization of the supply chain, efficient production and recyclability. In this concept, as smart factory has interoperable systems, multi-scale dynamic modelling and simulation, intelligent automation, strong cyber security, and networked sensors.
The industrial internet of things (IIoT) refers to interconnected sensors, instruments, and other devices networked together with computers' industrial applications, including manufacturing and energy management. This connectivity allows for data collection, exchange, and analysis, potentially facilitating improvements in productivity and efficiency as well as other economic benefits. The IIoT is an evolution of a distributed control system (DCS) that allows for a higher degree of automation by using cloud computing to refine and optimize the process controls.
MindSphere is an industrial IoT as a service solution developed by Siemens for applications in the context of the Internet of Things (IoT). MindSphere stores operational data and makes it accessible through digital applications to allow industrial customers to make decisions based on valuable factual information. The system is used in applications such as automated production and vehicle fleet management.
Digital thread, also known as digital chain, is defined as “the use of digital tools and representations for design, evaluation, and life cycle management.”. It is a data-driven architecture that links data gathered during a Product lifecycle from all involved and distributed manufacturing systems. This data can come from any part of product's lifecycle, its transportation, or its supply chain. Digital thread "enables the collection, transmission, and sharing of data and information between systems across the product lifecycle" to enable real-time decision making, gather data, and iterate on the product.
