Simple & Concise: A Brief Explanation of the Pillars of Industry 4.0
Systems Integration: A more cohesive cross company collaboration, enabling horizontal and vertical data integration networks providing truly automated value chains.
With greater systems integration,companies, departments, functions, and capabilities will become much more cohesive, as cross-company, universal data-integration networks evolve and enable truly automated value chains.
Can be divided into:
Horizontal Integration: Horizontal integration of a company’s processes means optimizing the interrelation between all process stages within the value chain. IT and IT infrastructures play a key role here, as they enable communication between the individual stages and provide a targeted means of managing them.
Vertical Integration: This is a vertical view of the interaction between various processes according to their respective logical levels. This ranges from the production level to company level and allows for greater monitoring and resource allocation company wide.
Simulation: amalgamation of physical and virtual entities to model, design, simulate, monitor and safeguard physical processes in a virtual environment.
Simulation is thecreation of cyber-physical systems where physical and virtual representations of entities are amalgamated into self-optimising smart entities
Smart Factories where computerised systems can be used to design, simulate, monitor and safeguard physical processes, creating a virtual map of the physical world and optimising decision-making.
3D Scan, the most accurate field survey of an existing environment to perfectly secure supply fits; Energy Simulation to assess or forecast consumption and emissions; and Virtual Reality Simulation to visualise new installations with immersive 360° models.
The use ofModeling & Simulation (M&S)andVirtual Reality (VR)allows to create 3D Prototypes of Plants, Skids, Machines, Equipment, Products and Processes and to test Virtually New Solutions.
This Virtual Simulation supports Engineering, Training & Management on the Virtual Worlds and enables developments ofapplications to improve Safety, Effectiveness and Efficiency.
Augmented Reality: Superimposing computer-generated images combined with object recognition to a user's view of the real world, giving an interactive hybrid view.
A technology that superimposes a computer-generated image on a user's view of the real world, thus providing a composite view. It augments and enriches reality, adding layers of information on top of the things that surround us.
With the help of advanced AR technology (e.g. addingcomputer visionandobject recognition) the information about the surrounding real world of the user becomesinteractiveand digitally manipulable.
This information can be virtualor real, e.g. seeing other real sensed or measured information such as electromagnetic radio waves overlaid in exact alignment with where they actually are in space.
Additive Manufacturing:refers to processes used to create athree-dimensionalobjectin which layers of material are formed undercomputer controlto create an object.
In additive manufacturingdigital design data is used to create athree-dimensionalobjectin which layers of material are formed undercomputer control.
The term3D printingstill referred only to the polymer technologies in most minds, and the termAMwas likelier to be used in metalworking.
An additive manufacturing process refers to a process by which digital 3D design data is used to build up a component in layers by depositing material.
Additive manufacturing is a far more effective way of working, requiring less intervention from machinists, delivering far greater degrees of precisionmass customisation, reduced environmental impact and enhanced design freedoms, being printed digitally directly from a CAD model rather than subject to interpretation.
The design is first created using CAD software on computer; this is what the final design will be created from, a digital blueprint, so every detail needs to be right. This software can help engineers predict how the final structure will behave and how strong it will be so it’s a vital part of the design process.
Big data:Large data sets that may be analysed computationally to reveal inconsistent process performance or availability and visualise results.
A term fordata setsthat are so large or complex that traditionaldata processing application softwareis inadequate to deal with them.
Predictive manufacturing as an applicable approach toward near-zero downtime and transparency requires vast amount of data and advanced prediction tools for a systematic process of data into useful information.
The importance of big data doesn’t revolve around how much data you have, but what you do with it. You can take data from any source and analyze it to find answers that enable
1) cost reductions.
2) time reductions.
3) new product development and optimized offerings.
4) smart decision making.
When you combine big data with high-powered analytics, you can accomplish business-related tasks such as determining root causes of failures, issues and defects in near-real time.Simply put, because of big data, managers can measure, and hence know, radically more about their businesses, and directly translate that knowledge into improved decision making and performance.
Cloud Computing: Remote server software and hardware services used to store, manage, process and visualise data, rather than a local server.
Cloud Computing isthe practice of using a network of remote servers hosted on the Internet to store, manage, and process data, rather than a local server or a personal computer. Or more simply, Cloud computing is the delivery of computing services over the Internet (the cloud).
Cloud computing allows users, and enterprises, with various computing capabilities to store and process data in either a privately-owned cloud, or on a third-party server located in adata centerin order to make data accessing mechanisms more efficient and reliable.
Software as a service: run on distant computers “in the cloud” that are owned and operated by others and that connect to users’ computers via the internet and, usually, a web browser.
Platform as a service: provides a cloud-based environment with everything required to support the complete lifecycle of building and delivering web-based (cloud) applications—without the cost and complexity of buying and managing the underlying hardware, software, provisioning, and hosting.
Infrastructure as a service provides companies with computing resources including servers, networking, storage, and data center space on a pay-per-use basis.
Public clouds are owned and operated by companies that offer rapid access over a public network to affordable computing resources. With public cloud services, users don’t need to purchase hardware, software, or supporting infrastructure, which is owned and managed by providers.
A private cloud is infrastructure operated solely for a single organization, whether managed internally or by a third party, and hosted either internally or externally. Private clouds can take advantage of cloud’s efficiencies, while providing more control of resources and steering clear of multi-tenancy.
A hybrid cloud uses a private cloud foundation combined with the strategic integration and use of public cloud services. The reality is a private cloud can’t exist in isolation from the rest of a company’s IT resources and the public cloud. Most companies with private clouds will evolve to manage workloads across data centers, private clouds, and public clouds—thereby creating hybrid clouds.
Autonomous system: An object/process which can gain information about it’s environment, adapt and make decisions without the need for human intervention.
A fully autonomous system can:
- Gain information about the environment.
- Work for an extended period without human intervention.
- Avoid situations that are harmful to people, property, or itself unless those are part of its design specifications.
- Move either all or part of itself throughout its operating environment without human assistance (more commonly associated with robots and may not be applicable to some systems).
Acobotorco-robot (fromcollaborative robot) is arobotintended to physically interact with humans in a sharedworkspace. This is in contrast with other robots, designed to operate autonomously or with limited guidance.
Cyber Security: Protection of computer systems from theft or damage to hardware, software or information and from disruption of the services provided.
Cyber security consists of technologies, processes and measures that are designed to protect systems, networks and data from cybercrimes.
Effective cyber security reduces the risk of a cyber-attack and protects entities, organisations and individuals from the deliberate exploitation of systems, networks and technologies.
- Threat landscape: terminology, cyber security threats, keeping up to date
- Authentication: access control, passwords, two-factor authentication
- Malware: types of malware, attack vectors, preventing infection
- Networking and communications: fundamentals, security challenges, standards
- Cryptography: symmetric and asymmetric cryptography, applications
- Network security: firewalls, virtual private networks, intrusion detection/prevention
The Internet of Things: The networking and connectivity of smart devices to enable data collection and exchange.
The Internet of Things (IoT) is the inter-networking of physical devices, vehicles (also referred to as "connected devices" and "smart devices"), buildings, and other items embedded with electronics, software, sensors, actuators, and network connectivity which enable these objects to collect and exchange data.
The IoT allows objects to be sensed or controlled remotely across existing network infrastructure,creating opportunities for more direct integration of the physical world into computer-based systems, and resulting in improved efficiency, accuracy and economic benefit in addition to reduced human intervention. Each thing is uniquely identifiable through its embedded computing system but is able to interoperate within the existing Internet infrastructure.
IIoT – Industrial Internet of Things the use of technologies in manufacturing. The Industrial Internet of Things (IIoT), also known as the Industrial Internet, brings together brilliant machines, advanced analytics, and people at work. It’s the network of a multitude of devices connected by communications technologies that results in systems that can monitor, collect, exchange, analyse, and deliver valuable new insights like never before. These insights can then help drive smarter, faster business decisions for industrial companies.
The IIoT is transforming industry—changing the way industries work. Whether it’s enabling predictive analytics to detect corrosion inside a refinery pipe, or providing real-time production data to uncover additional capacity in a plant, or driving visibility and control over your industrial control systems environment to prevent cyber-attacks, the IIoT—and the software solutions powered by it—are driving powerful business outcomes.
By combining machine-to-machine (M2M) communication, industrial big data analytics, technology, cyber security, and HMI and SCADA, the IIoT is driving unprecedented levels of efficiency, productivity, and performance. And as a result, industrial companies in power and energy, oil and gas, manufacturing, healthcare, aviation, and many other industries are experiencing transformative operational and financial benefits.