Fourth Industrial Revolution: Difference between revisions

Industry 4.0 creates what has been called a "smart factory". Within the modular structured smart factories, cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralized decisions. Over the Internet of Things, cyber-physical systems communicate and cooperate with each other and with humans in real time, and via the Internet of Services, both internal and cross-organizational services are offered and used by participants of the value chain.^[1]

Name

The term "Industrie 4.0" originates from a project in the high-tech strategy of the

Some have compared Industrie 4.0 with the Fourth Industrial Revolution. However, the latter refers to a systemic transformation that includes impact on civil society, governance structures, and human identity in addition to solely economic/manufacturing ramifications. The first

Industry 4.0 Workgroups [11]

Co-Chair Henning Kagermann and Siegfried Dais
WG 1 – The Smart Factory: Manfred Wittenstein
WG 2 – The Real Environment: Siegfried Russwurm
WG 3 – The Economic Environment: Stephan Fische
WG 4 – Human Beings and Work: Wolfgang Wahlster
WG 5 – The Technology Factor: Heinz Derenbach

Industry 4.0 Workgroup members
Reinhold Achatz, Heinrich Arnold, Klaus Träger, Johannes Helbig, Wolfram Jost, Peter Leibinger, Reinhard Floss, Volker Smid, Thomas Weber, Eberhard Veit, Christian Zeidler, Reiner Anderl, de:Thomas Bauernhansl, Michael Beigl, Manfred Brot, Werner Damm, Jürgen Gausemeier, Otthein Herzog, Fritz Klicke, Gunther Reinhart, Bernd Scholz-Reiter, Bernhard Diener, Rainer Platz, Gisela Lanza, Karsten Ortenberg,

On 8 April 2013 at the Hannover Fair, the final report of the Working Group Industry 4.0 was presented.^[12]

Design principles

There are 4 design principles in Industry 4.0. These principles support companies in identifying and implementing Industry 4.0 scenarios.^[1]

• Interoperability: The ability of machines, devices, sensors, and people to connect and communicate with each other via the Internet of Things (IoT) or the Internet of People (IoP).
• Information transparency: The ability of information systems to create a virtual copy of the physical world by enriching digital plant models with sensor data. This requires the aggregation of raw sensor data to higher-value context information.
• Technical assistance: First, the ability of assistance systems to support humans by aggregating and visualizing information comprehensibly for making informed decisions and solving urgent problems on short notice. Second, the ability of cyber physical systems to physically support humans by conducting a range of tasks that are unpleasant, too exhausting, or unsafe for their human co-workers.
• Decentralized decisions: The ability of cyber physical systems to make decisions on their own and to perform their tasks as autonomously as possible. Only in the case of exceptions, interferences, or conflicting goals, are tasks delegated to a higher level.

Meaning

Current usage of the term has been criticised as essentially meaningless, in particular on the grounds that technological innovation is continuous and the concept of a "revolution" in technology innovation is based on a lack of knowledge of the details.^[13]

The characteristics given for the German government's Industry 4.0 strategy are: the strong customization of products under the conditions of highly flexibilized (mass-) production. The required automation technology is improved by the introduction of methods of self-optimization, self-configuration,

Effects

In June 2013, consultancy firm McKinsey ^[19] released an interview featuring an expert discussion between executives at Robert Bosch - Siegfried Dais (Partner of the Robert Bosch Industrietreuhand KG) and Heinz Derenbach (CEO of Bosch Software Innovations GmbH) - and McKinsey experts. This interview addressed the prevalence of the Internet of Things in manufacturing and the consequent technology-driven changes which promise to trigger a new industrial revolution. At Bosch, and generally in Germany, this phenomenon is referred to as Industry 4.0. The basic principle of Industry 4.0 is that by connecting machines, work pieces and systems, businesses are creating intelligent networks along the entire value chain that can control each other autonomously.

Some examples for Industry 4.0 are machines which can predict failures and trigger maintenance processes autonomously or self-organized logistics which react to unexpected changes in production.

According to Dais, "it is highly likely that the world of production will become more and more networked until everything is interlinked with everything else". While this sounds like a fair assumption and the driving force behind the Internet of Things, it also means that the complexity of production and supplier networks will grow enormously. Networks and processes have so far been limited to one factory. But in an Industry 4.0 scenario, these boundaries of individual factories will most likely no longer exist. Instead, they will be lifted in order to interconnect multiple factories or even geographical regions.

There are differences between a typical traditional factory and an Industry 4.0 factory. In the current industry environment, providing high-end quality service or product with the least cost is the key to success and industrial factories are trying to achieve as much performance as possible to increase their profit as well as their reputation. In this way, various data sources are available to provide worthwhile information about different aspects of the factory. In this stage, the utilization of data for understanding current operating conditions and detecting faults and failures is an important topic to research. e.g. in production, there are various commercial tools available to provide

Challenges which have been identified ^[citation needed] include

• IT security issues, which are greatly aggravated by the inherent need to open up those previously closed production shops
• Reliability and stability needed for critical machine-to-machine communication (M2M), including very short and stable latency times
• Need to maintain the integrity of production processes
• Need to avoid any IT snags, as those would cause expensive production outages
• Need to protect industrial knowhow (contained also in the control files for the industrial automation gear)
• Lack of adequate skill-sets to expedite the march towards fourth industrial revolution
• Threat of redundancy of the corporate IT department
• General reluctance to change by stakeholders
• Loss of many jobs to automatic processes and IT-controlled processes, especially for lower educated parts of society^[21]

Role of big data and analytics

Modern information and communication technologies like Cyber-Physical Systems, big data analytics or cloud computing will help early detection of defects and production failures, thus enable their prevention, increase productivity, quality, and agility benefits that have significant competitive value.

Big Data Analytics consists of 6Cs in the integrated Industry 4.0 and Cyber Physical Systems environment. The 6C system comprises:

1. Connection (sensor and networks)
2. Cloud (computing and data on demand)
3. Cyber (model & memory)
4. Content/context (meaning and correlation)
5. Community (sharing & collaboration)
6. Customization (personalization and value)

In this scenario and in order to provide useful insight to the factory management and gain correct content, data has to be processed with advanced tools (analytics and algorithms) to generate meaningful information. Considering the presence of visible and invisible issues in an industrial factory, the information generation algorithm has to be capable of detecting and addressing invisible issues such as machine degradation, component wear, etc. in the factory floor.^[22][23]

Impact of Industry 4.0

Proponents of the term claim Industrie 4.0 will affect many areas, most notably:

1. Services and business models
2. Reliability and continuous productivity
3. IT security
4. Machine safety
5. Product lifecycles
6. Industry value chain
7. Workers' education and skills
8. Socio-economic factors
9. Industry Demonstration: To help industry understand the impact of Industry 4.0, Cincinnati Mayor John Cranley, signed a proclamation to state "Cincinnati to be Industry 4.0 Demonstration City".^[24]
10. An article published in February 2016 suggests that Industry 4.0 may have a beneficial effects for emerging economies such as India.^[25]

See also

• Computer-integrated manufacturing
• Digital modeling and fabrication
• Industrial control system
• Intelligent Maintenance Systems
• Machine to machine
• Predictive manufacturing system
• SCADA
• Service 4.0
• World Economic Forum 2016
• Fourth Industrial Revolution

References