95 Smart Manufacturing Terms You Need to Know Today

3D printing

A slang term for a sub-class of additive manufacturing printing. It allows one-off or small batch production, 3D printers can be leveraged into the manufacturing process of Smart Factories for flexible production equipment. The technology is advancing rapidly and both the speed of production is increasing and the types of materials that can be printed are being expanded to include metals and other materials. See Additive Manufacturing.

5th Generation

5th generation mobile networks or 5th generation wireless systems,are the proposed next telecommunications standards beyond the current systems. Will provide high bandwidth for all sorts of applications.

5S

It applies to workplace organization and uses a list of five Japanese words to organize the theory — seiri (sort), seiton (set in order), seiso (shine), seiketsu (standardize), and shitsuke (sustain). Basically, by creating an efficient organizational system where everything has a place, it will subsequently create an efficient working environment. Additionally, it builds a culture of standardization for how a company, a division, or even a process should operate.

Additive Manufacturing

Technology that manufactures objects from Computer-Aided Design (CAD) sketches by adding a layer of the material falls into Additive Manufacturing. This includes 3D Printing, layered manufacturing, additive fabrication, Rapid Prototyping (RP), and Direct Digital Manufacturing (DDM). Additive Manufacturing is used across all industries for very small production runs, notably in fully customized implants in the medical industry. ♦ Manufacture of a solid body by depositing successive thin layers of material, usually powder, until the desired shape and size is obtained (also called 3D Printing). It has extensive applications in the industrial world and represents a revolution in manufacturing processes and systems.

Advanced Manufacturing

Advanced Manufacturing in the U.S. refers mostly to CNC machine tool technology. Industry 4.0 leverages the latest available technology to carry out the most efficient production processes, maximizing productivity. This is called Advanced Manufacturing. ♦ A manufacturing ecosystem using innovative technologies and methodologies that improve output, product quality, and competitiveness in the manufacturing sector. ♦ It is the combination of automation in the industry, with advances in computing, connectivity, and IT. Advanced manufacturing enables production to become much faster, more flexible, and integrated. In addition, it can be managed remotely and in real-time. ♦ Advanced Manufacturing is the more general name used in the world than Industry 4.0, which is of German origin. In addition to the technologies involved in the digital transformation for Industry 4.0 (additive manufacturing, collaborative robotics, cyber-physical systems, augmented reality, cloud computing, big data, computer vision, artificial reality, and cybersecurity), the US definition also refers to the use of new avant-garde materials and emerging capabilities enabled by the biosciences and nanotechnology.

App Store

New capabilities on demand. Intelligent digital forms or complete applications, such as those familiar today from well-known app stores for smartphones, tablets, or computers, and which endow robots with new capabilities and functions on-demand at the click of a mouse. For example, programs that only require the entry of the desired parameters. With regard to Industrie 4.0, the immediate availability of new production capabilities will open up a whole new dimension of versatility for robots.

Application Architecture

Application integration architecture refers to the standards and policies created to define the means by which manufacturing and engineering applications are built, accessed, and integrated across the 4IR enterprise. It consists of a set of application guidelines and architectural components and may include messaging standards for accessing applications. This standardization is expected to enhance the organization’s ability to extract data from applications (and hence value), link disparate business and manufacturing processes, and ultimately eliminate redundancy between applications across the 4IR enterprise.

Application Programming Interface

One way for an application to present itself to other, typically remote, applications so that they can interact with it (for example, to read or write data to it). Often now used as another term for a Web Service.

Artificial Intelligence (AI)

Artificial Intelligence is what is exhibited by computers that have ‘learned’ based on processing large amounts of data, including historical facts and also information on their environment. In the Industry 4.0 context, environmental information is provided by sensors and pattern recognition applied to historical data by AI to make predictions and optimize scenarios to maximize results. ♦ The fusion of advanced technologies, exhibited through machines, to provide humanistic intelligence and decision making. ♦ The capability of a machine to perceive its environment and make rational decisions based upon its surroundings, displaying problem-solving capabilities similar to that of humans. Often used in consumer-facing businesses as an intelligent, voice-driven interface, in manufacturing, its further applications include machine learning algorithms; the ability of motion sensors and machine vision to spot and even predict defects, then adjust accordingly; and adaptive manufacturing where robots are able to learn new tasks rather than be reprogrammed. ♦ The term Artificial Intelligence refers to programs that map human intelligence by deploying cognitive technologies — for example, by speech control or machine learning. AI programs are independent and are based on the recognition of patterns which on the basis of the analysis of behavior and habits allow them to align themselves to the individual users. Artificial Intelligence or “virtual agents” are deployed in objects of daily use (for example, security mechanisms in the car to prevent microsleep). But they are also used in industry, for example, in robots used for process management or production. ♦ A technology that allows machines to learn from experience and perform tasks that normally require human intelligence (like visual perception, speech recognition, and decision-making). ♦ Artificial Intelligence is the development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages, and to take actions that maximize its chance of success at some goal.

Asset Administration shell

A popular rising Industry 4.0 term, an administrative shell describes the integration of assets into the world of information. Virtual digital and active representation of an I4.0 component in the I4.0 system.

Attack Surface and Vector

Elements and interactions of a system that are vulnerable to attack. Attack Vector Path or means (e.g. viruses, e-mail attachments, web pages, etc.) by which an attacker can gain access to an entity.

Automated Guided Vehicle (AGV)

A guided transportation system follows markers such as magnetic strips, bar codes, or pre-defined laser paths to help the uncrewed vehicles follow a specific route. Used in industrial applications for material movement

Augmented Reality (AR)

This new technology adds digital information to existing environmental information, displaying them together to provide a composite picture that is much more informative. Unlike Virtual Reality, Augmented Reality does not create a totally artificial environment but overlays the new information onto the real one. In the Smart Factory, Augmented Reality is used to assist in assembly and machine operation and training. ♦ A technology that superimposes a computer-generated image on to a user’s view of the real world in real-time via a headset, providing a composite view. This is ideal for prototyping and hand assembly. This is distinct from virtual reality in that in VR, the user only sees an artificial environment. ♦ The term relates to a computer-based extension of human perception. The respective real experience is enriched by additional virtual information or the opportunity for interaction. A key function in augmented reality is played by cameras which now can be integrated into a wide range of mobile devices to give the user a view of the real world and multimedia contents on a parallel basis. The user perceives augmented reality via an optical head-mounted display, a smartphone monitor, or also special data gloves. ♦ Augmented reality (AR) is an interactive experience of a real-world environment where the objects that reside in the real world are enhanced by computer-generated perceptual information, sometimes across multiple senses.

Availability

This is the actual time a machine is available to produce a product and is given as a percentage of the total planned production time. A manufacturing analytics platform can determine the availability of a machine by collecting and calculating downtime using alarms and signals from controls on the equipment and input from operators.

Batch Size 1 (Lot Size 1)

By including the Internet and CPS, Industry 4.0 will make the production more efficient and more flexible to allow a batch size 1 at affordable prices. In the same way, consumers can have their muesli mixed to their individual preference; the Internet enables machines’ individual production. ♦ Unique, one-off products for everyone. Industrie 4.0 is creating the basis for implementing the highest levels of customization — all the way down to batch size 1 — within industrial manufacturing. This means high-quality, single-piece production at the price of current, uniform, mass-produced goods. The networking of all systems involved in the production, and their extreme flexibility, will make the fulfillment of individual customer requirements a matter of routine in the smart factory. While the desire for customized products is already a megatrend today, it will develop to become one of the decisive competitive factors in the near future. This trend not only offers new market opportunities for products but also gives traditional industrial nations the chance to return previously outsourced production capacity to locations in high-wage countries.♦ Meeting every customer requirement. Individualized, or customized, production refers to the concept of an intelligent, highly automated production system that allows high variance and dynamism in the product range with production costs at the level of mass production. The goal is to resolve the conflict between the customer’s desire for individualization and the process efficiency of production in an industrial setting. A batch size of 1 is the highest level of customized production. Besides proprietary solutions in the automotive sector, Industrie 4.0 with its AMRC i4.0 Dictionary universally networked production environments represents the world’s most advanced approach for implementing customized production.

Big Data and Analytics

Industry 4.0 operation relies on digitally connected devices, with a large volume of high-quality data being recorded, processed, and stored at any point in time. Big Data Analytics has enabled the Smart Factory to examine these huge data sets to make associations and spot patterns and trends. These can be used for purposes such as production scheduling, planning predictive maintenance, and the prevention of bottlenecks. ♦ A collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis ♦ The collection and storage of massive amounts of structured, unstructured, and semi-structured data that has the capacity to be mined and analyzed. It enables organizations to have information about every part of their business and use it to predict and plan future production and supply possibilities. ♦ With technology progressing, more and more devices are being connected to the Internet. The resulting enormous volume of unstructured data sets is analyzed and assessed using data management platforms — traditional software for data processing cannot cope with the huge data volumes. With the appropriate analysis tools, big data can help companies to optimize their processes, determine trends, and address customers in a targeted fashion.

Blockchain

A blockchain is a continuously growing list of decentralized, digitized public records, called blocks, of all cryptocurrency transactions, which are linked and secured using cryptography.♦ The blockchain principle takes up the growing trend of decentralized data administration and processing. As solar modules on house roofs provide the centralized provision of power, the blockchain also operates with a central administrative unit. Literally, it is a chain of data blocks in which transactions are linked and examined. On the basis of smart contracts, more complex transactions can also be mapped on the blockchain. For example, smart contracts can facilitate loan agreements without the previously necessary administrative work. ♦ Originally, a blockchain is a growing list of records, called blocks, which are linked using cryptography. Each block contains a cryptographic hash of the previous block, a timestamp, and transaction data. By design, a blockchain is resistant to data modification. It is an open, distributed ledger that can record transactions between two parties efficiently, and in a verifiable and permanent way. ♦ Blockchain technology is being internationally recognized as one of the most disruptive innovations of the 21st century. Technology which, in spite of being complicated to understand, represents a transformation in the way we currently conduct transactions. The first application of this technology was with the appearance of the famous “Bitcoin” cryptocurrency, but it has both financial and non-financial applications. Blockchain technology allows virtually everything of value that can be expressed digitally to be recorded: birth certificates, title deeds, votes, financial accounts, product data, formulas, contracts, etc. All this is performed more quickly, securely, and transparently than with traditional alternatives”.

Bluetooth Low Energy

BLE (Bluetooth 4.0) is a lower-energy-consumption version of the Bluetooth wireless communications standard, which runs constantly, announcing a device’s presence to local sensors and optimizing battery life for the device in question. In the IoT, BLE allows for precise location and feature tracking without reduced battery life.

Build to Order (Made to Order)

A production process where products are not built until a confirmed order is received. It is established to eliminated wasted inventory and resources and align with lean manufacturing best practices.

Business intelligence

A set of methodologies and tools that analyze, report, manage and deliver information that is relevant to the business, and that includes dashboards and query/ reporting tools similar to those found in analytics. One key difference between analytics and BI is that analytics uses statistical and mathematical data analysis that predicts future outcomes for situations. In contrast, BI analyses historical data to provide insights and trends information.

Cell

The term cell is used in the larger concept of cellular manufacturing which is when equipment is arranged in small increments, or a cell, to promote continuous flow production. Most often in a u-shape, the cell is designed to facilitate shorter production times and increased efficiencies between each step.

Cloud Computing

Cloud Computing has enabled the Industry 4.0 environment to be fully connected, using the internet, data security, and large storage facilities. This remote centralization of business information provides the ideal platform for Digital Manufacturing. ♦ Using a network of remote servers to host your data on the internet, not on your PC or local server. This allows almost infinite space to store data, plus negates the potential for data loss and reduces investment in hardware. It also enables collaboration irrespective of geographical location and offers always-on availability. ♦ In principle, cloud computing covers all activities taking place via an online service, e.g. sending e-mails, processing documents via an online platform, and saving them there, playing videos, or analyzing data. What is meant is an IT infrastructure that makes it possible for data to be saved on decentralized computer systems via the internet and in principle to be available at any time at any place as long as there is an internet connection. Thus a cloud provider offers a complete working place in virtual form — computer, memory, platforms, and software applications — creating a high degree of flexibility for each user. ♦ The cloud is a shared platform of computing resources such as servers, storage and applications, which can be used as required and which can be accessed from any fixed or mobile device with Internet access. Industry environments and processes can take advantage of this infrastructure.

Customer Journey Tracking

The term Customer Journey Tracking designates the data-based analysis of buying decision processes. If the customer buys online, it is possible to reconstruct the decision-making path of the client using special tracking tools. For example, when using the tool it is possible to find out how many advertising contacts were necessary to activate the purchase of a specific product.

Cloud Robotics

Communication between the physical and digital worlds is controlled in the cloud and extended to robots used in mobile applications. ♦ Cloud Robotics Shared intelligence. Nowadays smartphones, tablets, and computers utilize data and processing power from the cloud as a matter of course. In the context of Industrie 4.0, robots too will be able to access decentralized data in networks or in the cloud, thereby significantly boosting their performance and flexibility. The robot itself will only require a small chip to control functionality, motion, and mobility. For the task at hand, specific services will be retrieved from the cloud or individual robots networked on an ad hoc basis to form temporary production teams. In this way, specialists will become universalists that can be used for a wide range of different manufacturing processes. Cloud robotics enables the implementation of a broad spectrum of different industry-specific applications via “Robotics as a Service®”. Another effect of the cloud: robots learn from one another. If one robot encounters an obstacle, for example, it posts this information to the connected systems, which can use it to respond intelligently to the obstacle.

Cobots (Collaborative Robotics)

A cobot, or collaborative robot, is a robot intended to physically interact with humans in a shared workspace, as opposed to ones that are designed to operate autonomously or with limited guidance. Cobots that can work safely alongside humans are already being used in some manufacturing plants in Britain, improving the efficiency of the manufacturing process. A key difference is that cobots are adaptive — able to learn new tasks rather than having to be reprogrammed. ♦ Industrial robots are no longer in closed work environments and isolated from each other, but will operate next to workers, share their space, and collaborate with them. A new generation of manageable lightweight robots will form the so-called “smart factory”. ♦ The best of two worlds. Until now, industrial robots always worked separately from humans in specially safeguarded protected spaces. Robotics have broken down this barrier with a new generation of collaborative industrial robots. With human-robot collaboration (HRC), combine the skills of humans with their superior creativity and cognitive abilities and the robot with its greater repeatability, strength, and precision. In this way, the robot becomes the third arm of the human operator. This new form of collaboration opens up previously inconceivable possibilities for the smart factory of the future.

Computer Numerical Controller

Computer numerical control is the automation of machine tools by means of computers executing pre-programmed sequences of machine control commands. This is in contrast to machines that are manually controlled by hand wheels or levers, or mechanically automated by cams alone.

Cyber-Physical Systems (CPS)

CPS are objects which have embedded software and electronics connected to each other in a system, for example, robots, drones, and other movable machines. This way physical and mechanical objects and processes are connected with software-controlled objects and processes — with the real and virtual worlds converging. CPS can be used for traffic control or for managing intelligent electricity networks. ♦ System which links real (physical) objects and processes with information-processing (virtual) objects and processes via open, in some cases global, and constantly interconnected information networks. Note: A CPS optionally uses services available locally or remotely, has human-machine interfaces, and offers the possibility of dynamic adaptation of the system at runtime.

Cyber-Physical Production Systems (CPPS)

This is the name for the connected machines in a Smart Factory, where they are centrally controlled and where one piece of equipment’s status and actions affect the others. Sensors are used for the data collection on each machine analyzed and used to provide information on the performance and condition of the overall production system. ♦ Physical and digital items are connected, monitored, and managed with computer programming and algorithms. ♦ If Cyber-Physical Systems (CPS) are used in production, then the designation is CPPS. In intelligent production, the CPPS unit controls itself. It can make decisions on the basis of individual parameters — does the relevant function/capacity exist for the requested version of the product? Accordingly, the implementing system is controlled by the CPPS, which at the same time monitors production. An example of deployment is avoiding measurement errors, securing a uniform quality, and streamlining the entire process

Cyber Security

In a digitized environment, the protection of any important company information, or cybersecurity, becomes increasingly important. Cybersecurity means all the technologies and services that protect the company from any attack or loss of data.

Cycle Time

No acronym here, but cycle time is a very common phrase used in manufacturing. It is an essential manufacturing key performance indicator for a number of systems and other calculations. For example, it is used by ERP and MES systems for scheduling, purchasing, and production cost, but is also a key component of calculating OEE. Check out the Cycle Time Formula resource for a deeper dive.

Dashboard

Displays information about the IoT ecosystem to users and enables them to control their IoT ecosystem.

Data Analyst

A person responsible for working with end business users to define the types of analytics reports needed in the business, and then capturing, modeling, preparing, and cleaning the required data for the purpose of developing analytics reports on this data that business users can act on.

Data Architecture

The data management architecture refers to the data models created within the 4IR enterprise in order to facilitate the creation of a common view of the data resources within the organization, and common methods for assessing and integrating data including augmented intelligence. This standardization allows all users better access to business data, integrated business views dependent upon integrated data, and data-facilitated (analytics) real-time response to market opportunities.

Data Value

Value is the most important ‘V’. It is all well and good having access to big data but unless we can turn it into value, it is useless.

Data Variety

Refers to the different types of data we can now use. 80% of the world’s data is now unstructured, and therefore can’t easily be put into tables. With big data technology, we can now harness different types of data (structured and unstructured) including messages, photos, sensor data, video, or voice recordings, and bring them together with more traditional, structured data.

Data Velocity

Refers to the speed at which new data is generated and the speed at which data moves around. Big data technology allows us now to analyze the data while it is being generated, without ever putting it into databases.

Data Veracity

Refers to the messiness or trustworthiness of the data. With many forms of big data, quality, and accuracy are less controllable. Volume often makes up for the lack of quality or accuracy

Data Volume

Refers to the vast amounts of data generated every second. This increasingly makes data sets too large to store and analyze using traditional database technology. With big data technology, we can now store and use these data sets with the help of distributed systems, where parts of the data is stored in different locations and brought together by software.

Deep Learning

Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised, or unsupervised.

Department of Defence Architecture Framework (DoDAF)

The standard for defense architectures especially in the United States.

Descriptive Analytics

An initial stage of data processing that involves creating a summary of historical data with the goal of producing useful information or, answering the question, “What happened?”

Digital Enterprise

Industry 4.0 that it reached outside the factory walls. A connected supply and value chain means greater visibility of locations and activities across the whole enterprise, rather than just the internal position.

Digital Shadow

The virtual image of real things. The digital shadow is a digital image of a real object. These data contain both the current status and the desired status of the object, the possible ways and processes for achieving the desired status, and the history of what the object has already gone through. It is only the combination of a digital shadow and a physical object that results in a smart thing. Every physical product can be manufactured more efficiently and with higher quality, in the digitized production facility if a digital shadow has been created for it and it bears its own specific DNA.

Digital Supply Chain

An environment where processes are web-based. If organizations want to successfully implement Industry 4.0 concepts, they will need to integrate a digital supply chain into their processes. Greater connectivity allows greater sharing of manufacturing processes, production control, and scheduling. ♦ An environment where processes are web-based. If organizations want to successfully implement Industry 4.0 concepts, they will need to integrate a digital supply chain into their processes. Greater connectivity allows greater sharing of manufacturing processes, production control, and scheduling. ♦ The digital supply chain merges the major business processes of all parties involved — from the suppliers to the manufacturer and the end customer. The potential of a digitized value creation chain lies primarily in the acceleration of the production and logistics processes, the reduction of effort for data acquisition, and the optimization of data security and consistency. With integrated networking, the digital value creation chain is able to overcome current media discontinuity. One example from the field of procurement: where a steel-processing company previously had to activate a complicated process via different media for purchasing and replenishment, in the future purchasing will be automated on the basis of predefined parameters. Companies today are already making use of digital value creation chains to optimize individual production islands and processes within their organization. In the factory of tomorrow, the digital supply chain will also encompass global procedures across company boundaries, controlling them largely autonomously. As the most flexible machine ever conceived by man, the robot plays a central role in the digital supply chain. In its function as the core component of intelligent automation solutions, it increases the entrepreneurial freedom of action, secures competitive advantages, speeds up production processes, and assures quality in the long term.

Digital Twin

A digital twin is a digital replica of a physical machine or system. It uses data from sensors installed on physical objects to represent their near real-time status, working condition, or position. The delivery of this data can be through simple dashboards or through the use of a 3D geometrical model of the machine or system allowing contextualized location of data sources. If a snapshot of the real-time status is taken, and then fed into a predictive simulation model, this model is no longer a twin, but instead can be considered to be a Digital Master, especially if the physical world is then adjusted based on this master.

Digitization

The move to Digitization has allowed Industry 4.0 and the connected factory to develop, facilitating a fully integrated supply chain from a product’s development right through to its final distribution. With all information being in a format that can be understood by a computer, systems and machines can interact to provide highly efficient operation. ♦ Potential of the digital transformation. Converting real products and analog sequences into digital data and processes is referred to as digitization. In Industrie 4.0, people, machines, and industrial processes are networked on the basis of cyber-physical systems incorporating state-of-the-art information and communications technology. In this context, the intelligent exchange and interpretation of data determine the entire life cycle of a product: from the idea to development, manufacturing, use, and maintenance through to recycling. Production and logistics processes will be globally networked beyond the factory gates in the future for the purpose of optimizing the flow of materials, detecting non-conforming parameters at an early stage, and enabling a highly flexible reaction to changing customer requirements and market conditions.

Edge Computing and Gateways

An edge gateway serves as a network entry point for devices typically talking to cloud services. They also often provide network translation between networks that use different protocols. ♦ Edge computing is where processing takes place at (or near) the physical location of the user or data source. With the closest processing, users benefit from faster and more reliable services, while enterprises take advantage of the flexibility of hybrid cloud computing. Edge computing is one way a company can use and distribute a pool of resources across a large number of locations.

Enterprise Resource Planning (ERP Software)

Enterprise resource planning (ERP) refers to business-management software, usually comprising a suite of integrated applications, that an organization uses to collect, store, manage and interpret data from its many business activities, including inventory management, cash flow, raw materials, CRM (customer relationship management), production capacity and the status of orders, purchase orders and payroll. Often for the first time in a business, it allows individuals to access data from other departments, therefore, using the same information to base their decisions on. ♦ An ERP system refers to software solutions with which business processes such as procurement, production, controlling and sales can be managed on a centralized basis. This enables a rapid overview of all company units. For example, it makes it simple to determine when which parts need to be ordered for manufacturing processes. Alongside the overall management, the ERP system contains important data for reporting, as the system contains meaningful data to assess the corporate situation. ♦ Enterprise resource planning is a business process management software that allows an organization to use a system of integrated applications to manage the business and automate many back-office functions related to technology, services, and human resources.

Extensible Mark-up Language

In computing, Extensible Mark-up Language is a markup language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable.

Flexible Manufacturing

An infrastructure-free system of technologies and processes that enable operations to be reconfigurable and scalable. ♦ Flexibility in all dimensions. Flexibility is the ability to react quickly to changing influences. In the smart factory, utmost flexibility results primarily from the combination of IT technologies, such as the Cloud and Big Data, with intelligent, generic production units incorporating robots and autonomously controlled mobile units. The factory of the future will not have any predefined routes or rigid processes. Mobile units will equip robots “on the fly” with other tools, enabling them quickly to carry out new tasks or process other workpieces. The smart factory is therefore able to manufacture different products or product versions without any significant retooling times. It thus completely redefines the concept of flexibility in production.

Fog Computing

Extending cloud computing to the edge of an enterprise’s network, reducing the amount of data transferred to the cloud for processing and analysis, improving security. This creates efficiencies and has opportunities for companies concerned with compliance issues. ♦ This term refers to extending cloud computing to the edge of an enterprise’s network. It brings the advantages and power of cloud computing closer to where the data is being generated and acted upon. It can reduce the amount of data that is transferred to the cloud for processing and analysis, while also improving security. ♦ An architecture approach that uses a collaborative multitude of end-user clients or near-user edge devices to carry out a substantial amount of temporary storage, communication, control, configuration, measurement, and management.

Hadoop

Administered by the Apache Software Foundation, Hadoop is a batch processing software framework that enables the distributed processing of large data sets across clusters of computers.

HANA (see ERP)

An ERP software/hardware in-memory computing platform from SAP designed to process high-volume transactions and real-time analytics.

Horizontal Integration

This term denotes the networking of companies operating at approximately the same level (for example, manufacturing similar products). Horizontal integration also occurs within one and the same organization. There it relates to hierarchy levels and departments which carry out similar tasks. One of its functions is to achieve optimized material and information flows.

Human-Machine Interface (HMI)

Allowing a person to interact with a machine, the HMI consists of hardware and software for control and communication. Extensive use is made of this interface in the Smart Factory, where there is increased demand for discrete HMI applications across many industries. ♦ HMI is the space where interactions between humans and machines take place. Applications within Industry 4.0 center around machine control achieving new levels of safety and efficiency. For example, machine operators using wearables or AR glasses receive physical feedback from haptic technologies; maintenance professionals are able to visualize machine status in real-time, allowing them to prioritize workload and anticipate tooling and material requirements; remote collaboration allows off-site specialists to consult or guide local technicians through tasks that would otherwise require travel; managers are able to survey the status of all operations inside a facility. ♦ The user interfaces in a manufacturing or process control system. It provides a graphics-based visualization of industrial control and monitoring system. Previously called an “MMI” (man-machine interface), an HMI typically resides in an office-based Windows computer that communicates with a specialized computer in the plant such as a programmable automation controller (PAC), a programmable logic controller (PLC), or a distributed control system (DCS). ♦ A user-interface consisting of hardware and software that lets a person send requests/commands to a machine. Typically HMI’s are meant to make it as easy as possible for a person to control a machine with little difficulty. A great example here would be a smartphone. With a smartphone, a user would perform various actions in order to navigate to the phone-call application and place a call.

Industrial Internet Consortium

The Industrial Internet Consortium will enable and accelerate the adoption of the Industrial Internet which is essential to growth and competitiveness in key industry sectors, including manufacturing, transportation, energy, healthcare, buildings, utility infrastructure, defense, and emergency response.

Industrial Internet of Things

A system that connects and integrates industrial control systems with enterprise systems, business processes, and analytics. Note 1: industrial control systems contain sensors and actuators. Note 2: typically, these are the large and complicated system.

Industrial Internet Reference Architecture

A standards-based architectural template and methodology enable Industrial Internet of Things (IIoT) system architects to design their own systems based on a common framework and concepts.

Industry 4.0

Industry 4.0 is the common name used to describe the current trend towards a fully connected and automated manufacturing system, or Smart Factory. Conceived in Germany, also written as Industrie 4.0, it is internationally hailed as the latest, or Fourth, Industrial Revolution. All production decisions are optimized based on real-time information from a fully integrated and linked set of equipment and people. Industry 4.0 is considered the fourth industrial revolution: After mechanization followed electrification (introduction of the assembly lines) and computers’ introduction. Now, within the scope of Industry 4.0, the Internet enters factories. Industry 4.0 deals with cyber-physical systems (CPS), physical systems, mechanical and electro-mechanical equipment, or anything else that can gain new potential by using the Internet. ♦ Industry 4.0 is a name for the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things, cloud computing, and cognitive computing. ♦ The current trend in the manufacturing industry uses a combination of IoT, big data, and cloud computing in order to develop factories that can make decisions based on large amounts of data. A couple of benefits that Industry 4.0 offers is the ability to detect bottlenecks and deficiencies using big data, high-level customization, and automation of production.

Internet of Things (IoT)

This term encompasses the connection of smart devices that can communicate and exchange information. Applied in the manufacturing context, this intelligent connectivity is used to collect data and optimize the production line in quality, cost, and throughput. ♦ The connection of all devices to the internet and each other. The phenomenon is built on cloud computing and networks to take in data and make real-time actions based on that data. ♦ A network of physical devices, vehicles, home appliances, and products embedded with electronics, software, sensors, actuators, and connectivity enabling connection via wireless technology. ♦ The IoT consists of physical objects which can communicate with each other via the internet. The connection is made via integrated microchips which allow a unique identifier of the device in the network. An example: Appropriately equipped printers can order printer cartridges automatically once the ink level reaches a critical value. This communication can be understood using the example of the “smart home” where several or all household devices are interconnected, the fridge independently reports used food via the smartphone or the user can switch on the heating using the tablet before he comes home. ♦ Defines the connectivity of objects through a communication protocol. Everything from a watch to the condition of a shipping container in the middle of the ocean can be tracked, monitored, and configured via the internet. It delivers real-time knowledge of an environment the user wants to control. The development of sensors and communicating technologies such as 5G networks provide low-cost opportunities.

Interoperability

The connection of cyber-physical systems, humans, and smart factories communicating with each other through the IoT. In doing so, manufacturing partners can effectively share information, error-free.

Key Performance Indicators (KPI)

Quantifiable measurements to evaluate the performance of industrial solutions and processes within an operation. KPIs can be benchmarked and compared across multiple facilities and include inputs spanning the number of deliveries made, average downtime, cost per labor per shift, etc. ♦ A Key Performance Indicator is a measurable value that demonstrates how effectively a company is achieving key business objectives. Organizations use KPIs to evaluate their success at reaching targets.

Lean Manufacturing

Relies on an efficient flow of materials, components, and finished product. Toyota coined the concept to ensure manufacturing operations ran as efficiently as possible. Along with the definition of lean manufacturing, mudas (or wastes) were also established as key practices to avoid in manufacturing.

Machine 2 Machine Communication (M2M)

Also called Interoperability, this labels the ability of digital equipment to communicate with each other without requiring any manual assistance from humans. This is particularly useful in applications of remote monitoring and forms the basis for the IoT. Historically first used in telemetry, M2M is reliant upon sensors and software and a communication network and identification protocol and is now finding application in everyday household products and appliances. Equipment like this, with M2M capability, is referred to as “Smart.” ♦ Machine-to-machine communication: when networked devices can exchange information and perform actions without the manual intervention of humans. The technology that underpins the Internet of Things.

Machine Learning

The process by which intelligent devices gain their ‘knowledge’ is known as Machine Learning. Large amounts of data are processed to recognize patterns, identify correlations, and apply rules. They can then detect anomalies and react accordingly. The learning process may occur within an individual device or connected to an intelligent network. In Industry 4.0, Machine Learning is effective in optimizing production processes according to real-time information, within rules or constraints. ♦ Machine learning is a field in which machines can ‘learn’ without explicit programming. Evolved from the study of pattern recognition and computational learning theory in artificial intelligence, machine learning explores the study and construction of algorithms that can learn from and make predictions on data — such algorithms overcome following strictly static program instructions by making data-driven predictions or decisions, through building a model from sample inputs.

Machine-to-Machine Communication (M2M)

Machine-to-machine communication: when networked devices can exchange information and perform actions without the manual intervention of humans. The technology that underpins the Internet of Things. ♦ M2M denotes the largely automated communication between devices, such as machines, automatic machines, vehicles, and measuring units. The exchange takes place via the internet or mobile phone and is used in medical engineering, facility management, or automated production. M2M is used for remote maintenance and monitoring of machines, the use of automatic machines such as mobile pay terminals, or mobile transfer of consumer data. M2M brings together information and communication technology. ♦ M2M relates specifically to the interconnection of devices, usually wirelessly — such as devices that track a car’s location or monitor its engine’s performance. ♦ Machine to machine communication is one of the breakthrough benefits of having smart connected machines. Smart machines can make decisions based on machine learning, artificial intelligence, and historical data. A single machine’s decisions may influence other machines in the process chain through the communication of its own decision.

Manufacturing Execution System (MES)

MES are production systems that allow production management and control in real-time. These systems record and link operating, machine, and personnel deployment data and are generally connected to all additional systems of process automation within a corporation. MES operates as a system at the operating management level and establishes the link between the corporate management level and the operating level. ♦ A production system that allows real-time management. The system records and links operational data (from machines and personal deployment), and is usually connected to the organization’s additional automation systems. MES operates at the operational management level and creates a link between the corporate and operational management levels. ♦ Manufacturing execution systems are computerized systems used in manufacturing, to track and document the transformation of raw materials to finished goods. MES provides information that helps manufacturing decision-makers understand how current conditions on the plant floor can be optimized to improve production output. MES works in real-time to enable the control of multiple elements of the production process (e.g. inputs, personnel, machines, and support services).

Mass Customisation (see Batch Size 1)

One of the goals of the digital enterprise is to be able to create one-off, consumer-defined, products in a cost-effective way using flexible manufacturing processes and configurations.

Mixed-Model Production

Mixed-Model Production occurs in the Smart Factory environment when several distinct product models are manufactured on the same production line without changeovers. This is carried out to provide the optimal input to later workstations for improved overall productivity or smooth demand on suppliers and reduce inventory.

OSI Model (Open Systems Interconnection Model)

OSI is a standardized model that describes how different network components communicate with each other. The model divides this communication into seven layers, also called stations. For example, between sender and recipient, an e-mail goes through all these standard stations and arrives only if each layer/station fulfills its task. All steps from the sender to the recipient are recorded in a protocol so that the respective layer receives the necessary information on the object (sender/recipient, file properties) and carries out its function accordingly. All links within a process must know the procedure. This is the way the layer model works, irrespective of whether sender and recipient are using different components and software. ♦ This is a model that describes how different components in a network communicate with each other. OSI divides communication into 7 layers, called stations. All stations are recorded in a protocol so that they can receive the necessary information from the inner layer and thus function effectively.

OPC UA

OPC UA, or OPC Unified Architecture, was developed by the OPC Foundation, an industry consortium focused on automation. OPC UA refers to machine the standards set for automation and communication between machines

Operational Technology

Hardware and software that detects or causes a change through the direct monitoring and/or control of physical devices, processes, and events in the enterprise.

OT/IT Convergence

The process or aspiration of bringing together Information Technologies and Operation Technologies (which provide operational control of assets in a network in real-time). Higher efficiency and reliability may be attained with such a smart grid platform combining the physical infrastructure and human interface.

Overall Equipment Effectiveness (OEE)

The evaluation of how effectively equipment is working in a manufacturing environment. ♦ OEE is the gold standard for improving manufacturing productivity. Understand, measure, and improve OEE, Availability, Performance, and Quality.

Predictive Analytics

Predictive Analytics goes one step beyond normal data analysis and uses the results and the knowledge gained from the analysis to make statements about possible events in the future. An example is the Smart Grid (intelligent power grid) which calculates future power requirements and then provides them. ♦ The practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends. Using predictive analytics, we can predict future events like when a machine might AMRC i4.0 Dictionary fail. It does not however change a machine’s operating conditions to extend the remaining useful life. That would be the domain of prescriptive analytics.

Predictive Maintenance

With connected machines in the Digital Manufacturing environment providing real-time status information, Machine Learning can be applied to the data to spot trends and patterns in timing specifically for maintenance requirements. This results in the avoidance of unscheduled downtime and maximizes overall machine availability. Predictive Maintenance is also being extended into the field after product delivery to facilitate Servitization.♦ The capacity to predict the productivity and maintenance needs of machines within a smart factory. Where predictive maintenance also has potential is for machine manufacturers to have data coming back to them after their products are installed in the customer’s factories. By better understanding of how a product is used and being able to detect defects (and ideally, remote maintenance) leads to better future design and improved customer relationships.♦ Predictive Maintenance operates in a similar fashion: Using sensors machines and vehicles can transfer operating data and thus allow predictive maintenance. ♦ The capacity to predict the productivity and maintenance needs of machines within a smart factory. Where predictive maintenance also has potential is for machine manufacturers to have data coming back to them after their products are installed in the customer’s factories. By better understanding of how a product is used and being able to detect defects (and ideally, remote maintenance) leads to better future design and improved customer relationships. ♦ Predictive maintenance allows machines to prevent machine downtime. Machines and systems continuously analyze their status themselves and potential problems are reported in real-time. Scheduled maintenance ensures that the machine remains operational.

Production analytics (software)

A production analysis software is a platform that helps you to visualize in real-time the data of your machines, lines, and factories. In addition, to live tracking, you can also analyze historical data and make predictions based on inputs collected from sensors.

Programmable Logic Controller (PLC)

Electronic devices for control of the logical sequence of events commonly found in discrete manufacturing processes.

Radio Frequency Identification (RFID) (automatic object identification)

RFID devices are chips that communicate with a reading device using an electromagnet field. Like a barcode or a magnetic stripe, the chips contain information that can be obtained using a scanner. This information can also be recorded over large distances. Chips are often used in storage as objects marked in such a way can be localized at any time. ♦ The use of electromagnetic or inductive coupling in the radio frequency portion of the spectrum to communicate to or from a tag through a variety of modulation and encoding schemes uniquely to read the identity of an RFQ Tag. A method to identify objects (including humans) through electromagnetic waves without actual physical contact. This way, data can be gathered more easily. An object or creature is equipped with a transponder that transmits data to an electronic reader. Other than, for example, barcodes, the information can be read without a line of sight, and in some cases, operating distance can be over a kilometer.

RAMI 4.0 (Reference Architecture Model Industry 4.0)

RAMI 4.0 is a three-dimensional structural model that presents all levels and participants of Industry 4.0 in a comprehensible manner. In this architecture, processes are divided into smaller packages. There is an axis for the grid-like hierarchy structure within a modern factory, an axis for the architecture structure (functions, processes, data), and a third axis that describes the product life cycle. It is intended that RAMI 4.0 functions on a global basis, identifying and bringing together all developments in the manufacturing industry, securing a standardized exchange of information. ♦ RAMI 4.0 combines all elements and IT components in a layer and life cycle model. RAMI 4.0 breaks down complex processes into easy-to-grasp packages, including data privacy and IT security.

Re-Shoring

Whereas in the past purchase decisions were often primarily made on the basis of the lowest cost production, in the future it will be the product that is available most quickly and with a high level of customization that will be at the top of consumers’ shopping lists. This necessitates new manufacturing and marketing methods and structures that will only become possible as a result of networked production in smart factories. Short distances will be an important factor in achieving fast availability. Due to the high degree of automation, production steps that are currently outsourced to low-wage countries can be repatriated to high-wage countries in a process known as “reshoring”. Irrespective of wage structures, intelligent automation allows cost-efficient and high-quality production in the vicinity of the consumers.

Risk-based Planning & Scheduling (RPS)

Risk-based Planning and Scheduling extends traditional planning and scheduling techniques to fully account for the variation present in nearly any production system. Using a simulation model, RPS generates a detailed resource-constrained deterministic schedule and a probability-based risk analysis of that schedule to account for variation in the system. In this way, RPS is used to generate schedules that minimize risks and reduce costs in the presence of uncertainty.

Remote Maintenance

Risk-based Planning and Scheduling extends traditional planning and scheduling techniques to fully account for the variation present in nearly any production system. Using a simulation model, RPS generates a detailed resource-constrained deterministic schedule and a probability-based risk analysis of that schedule to account for variation in the system. In this way, RPS is used to generate schedules that minimize risks and reduce costs in the presence of uncertainty. A very classical application area of Industry 4.0 is remote maintenance that permits maintaining a huge printing machine in Australia from Germany. When combined with augmented reality, this becomes even more possible. For this, the installer in the field would put on special glasses (for instance, Google Glass) to mark the exact screws that need to be removed in the correct sequence to repair the machine, all via visual displays on the glasses.

SCADA (Supervisory Control and Data Acquisition)

A control system in which peripheral devices are used to the interface, in addition to computers and other networks.

SMAC

SMAC is an acronym for “Social, Mobile, Analytics, Cloud” and is sometimes referred to as ‘Third Platform.’ Working together, these technologies combine in a way to make a potentially very intelligent, successful system. These factors link products to their end-users in the manufacturing context, providing instant feedback into market trends and preferences, which drives innovation and growth.

Smart Device

A smart device is a device, generally connected to other devices or networks via different protocols such as Bluetooth, NFC, Wi-Fi, 3G, etc., that can operate to some extent interactively and autonomously.

Smart Factory

A Smart Factory is the implementation of Industry 4.0 technology. At a very detailed level, large volumes of data can be analyzed and modeled to produce plans and schedules that provide an immense competitive advantage. ♦ The connected factory is used in parallel with the term “smart factory.” It is an industrial environment that uses Industry 4.0 technologies such as cloud computing and networked activity to offer task completion through autonomous capability. Information about all activity within the plant is received through real-time data reporting, which can be used to adjust issues before they arise. ♦ The seamless connection of individual production steps, from planning stages to actuators in the field. Soon, machinery and equipment will improve processes through self-optimization; systems will autonomously adapt to the traffic profile and network environment. ♦ Factories that are monitored by artificially intelligent machines that oversee the manufacturing process, reducing the manpower traditionally required on the factory floor. The data provided by the connected elements brings huge opportunities for businesses to better understand their process, potential flaws, and, ultimately, to implement considerable efficiencies. ♦ Factories that are monitored by artificially intelligent machines that oversee the manufacturing process, reducing the manpower traditionally required on the factory floor. The data provided by the connected elements brings huge opportunities for businesses to better understand their process, potential flaws, and, ultimately, to implement considerable efficiencies. ♦ Factory whose degree of integration has reached a level that makes self-organizing functions possible in production and in all business processes relating to production. Note: The virtual representation of the factory makes intelligent decisions possible. The aim is to increase efficiency, effectiveness, flexibility, and/or adaptability.

Smart manufacturing

An environment where computers control decision-making in which the physical and digital are connected and communicate with one another to improve production.

Software as a Service (SaaS)

Software as a service (SaaS) is a form of software distribution and marketing. In the SaaS model, the software supplier is responsible for all the necessary structures to make the system available (servers, connectivity, information security care), and the client uses the software via Internet, paying a fee for the service. The SaaS model offers software as a service with specific purposes that are available to users on the Internet. Software systems are accessible from multiple devices, through a client interface, on a client-server model network such as a Web browser. In SaaS, the user does not manage the individual features of the application, except for specific configurations. Therefore, developers focus on updating rather than infrastructure, leading to the rapid development of software systems. ♦ Software is delivered to the user and updated via the internet. Typically enabled by a cloud service that hosts the software. Often there is no software installed on the user’s device but it is accessed via a web browser. Although this is not a requirement of SaaS, for example, Adobe and Microsoft both deliver applications that are installed on the user’s device through a SaaS model.

Traceability

Traceability here refers to the ability to fully trace all raw materials, producers, upstream suppliers, individual parts or assemblies as well as the complete product and its consumers in the digital value creation chain. It is possible at all times to determine when, where and by whom the goods were produced, processed, stored, transported, used, or disposed of. Irrespective of whether an individual part or a finished product is concerned, a distinction is made between two directions of traceability: from the manufacturer to the consumer and from the consumer to the manufacturer.

Unstructured Data

Information that either does not have a pre-defined data model or is not organized in a pre-defined manner. It is thus not stored in a database in structured fields. Examples include text, images, audio, video.

User experience (UX)

User experience (UX) is the set of elements and factors related to user interaction with a given product, system, or service whose result generates a positive or negative perception. An important concept in UX design is the process by which users form experiences. When the user encounters a product, it forms a momentary impression, which evolves over time.

Vertical Integration

Vertical integration describes the networking of inter-company departments of the procurement chain (c.f. horizontal integration). It allows the simple exchange of information, contributes to greater efficiency in production flows, for example in optimizing the value-added and supply chains of the company, and operates as a control instance.

Virtual Reality

A computer-generated simulation of a three-dimensional image that can be interacted with in a seemingly real or physical way by a person using special electronic equipment. In the manufacturing environment, it can allow for rapid visualization, prototyping, and simulation. ♦ A Smart Factory is a production facility in which the production processes are optimized automatically and managed via network machines. Individual tools contain — for example using RFID chips — information that can be read by other machines. One of the advantages of Smart Factories is that they can manufacture small lot sizes efficiently or even on a specially customized basis. ♦ A computer-generated simulation of a three-dimensional image that can be interacted with in a seemingly real or physical way by a person using special electronic equipment. In the manufacturing environment, it can allow for rapid visualization, prototyping, and simulation.

Wi-Fi

Wireless Fidelity is a technology for wireless local area networking with devices based on the IEEE 802.11 standards. Wi-Fi is a trademark of the Wi-Fi Alliance, which restricts the use of the term Wi-Fi Certified to products that successfully complete interoperability certification testing.

ZigBee

Low-power radio protocol for small amounts of data, based on the IEEE 802.15.4 standard. It has low power consumption, a range of about 100 meters, and a bandwidth of 250 kbps. IoT devices like the Nest thermostat and Hue light bulb both use ZigBee chips.