Industry 4.0 fosters what has been called a "smart factory". Within 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 both internally and across organizational services offered and used by participants of the value chain.
The term "Industry 4.0", sometimes shortened to I4.0 or simply I4, originates from a project in the high-tech strategy of the German government, which promotes the computerization of manufacturing.
The term "Industry 4.0" was revived in 2011 at the Hangover Fair. In October 2012 the Working Group on Industry 4.0 presented a set of Industry 4.0 implementation recommendations to the German federal government. The Industry 4.0 work group members are recognized as the founding fathers and driving force behind Industry 4.0.
On 8 April 2013 at the Hangover Fair, the final report of the Working Group Industry 4.0 was presented.. This working group was headed by Siegfried Dais (Robert Bosch GmbH) and Henning Kagermann (German Academy of Science and Engineering).
As Industry 4.0 principles have been applied by companies they have sometimes been re-branded, for example the aerospace parts manufacturer Meggitt PLC has branded its own Industry 4.0 research project M4.
There are four design principles in Industry 4.0. These principles support companies in identifying and implementing Industry 4.0 scenarios.
Interconnection: The ability of machines, devices, sensors, and people to connect and communicate with each other via the Internet of Things (IT) or the Internet of People
Information transparency: The transparency afforded by Industry 4.0 technology provides operators with vast amounts of useful information needed to make appropriate decisions. Inter-connectivity allows operators to collect immense amounts of data and information from all points in the manufacturing process, thus aiding functionality and identifying key areas that can benefit from innovation and improvement.
Technical assistance: First, the ability of assistance systems to support humans by aggregating and visualizing information comprehensively 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, interference's, or conflicting goals, are tasks delegated to a higher level.
Current usage of the term has been criticized 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.
The characteristics given for the German government's Industry 4.0 strategy are: the strong customization of products under the conditions of highly flexible (mass-) production. The required automation technology is improved by the introduction of methods of self-optimization, self-configuration, self-diagnosis, cognition and intelligent support of workers in their increasingly complex work The largest project in Industry 4.0 as of July 2013 is the BMBF leading-edge cluster "Intelligent Technical Systems Ostwestfalen-Lippe (it's OWL)". Another major project is the BMBF project RES-COM, as well as the Cluster of Excellence "Integrative Production Technology for High-Wage Countries" In 2015, the European Commission started the international Horizon 2020 research project CREMA] (Providing Cloud-based Rapid Elastic Manufacturing based on the XaaS and Cloud model) as a major initiative to foster the Industry 4.0 topic.
In June 2013, consultancy firm McKinsey 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 overall equipment effectiveness (OEE) information to factory management in order to highlight the root causes of problems and possible faults in the system. In contrast, in an Industry 4.0 factory, in addition to condition monitoring and fault diagnosis, components and systems are able to gain self-awareness and self-productiveness, which will provide management with more insight on the status of the factory. Furthermore, peer-to-peer comparison and fusion of health information from various components provides a precise health prediction in component and system levels and force factory management to trigger required maintenance at the best possible time to reach just-in-time maintenance and gain near-zero downtime.
During EDP Open Innovation conducted in Oct 2018 at Lisbon, Portugal, Industry 4.0 conceptualization was extended by Sens-fix B.V. a Dutch company with introduction of M2S terminology. It essentially is characterizing upcoming service industry to cater to millions of machines, managed by the machines themselves, fortunately using Artificial intelligence developed by humans!.
Challenges in implementation of Industry 4.0:
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 know how (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
Low top management commitment
Unclear legal issues and data security
Unclear economic benefits/ Excessive investment
Lack of regulation, standard and forms of certifications
Insufficient qualification of employees
Role of big data and analytics
Modern information and communication technologies like cyber-physical system, big dataanalytics and cloud computing, will help early detection of defects and production failures, thus enabling their prevention and increasing productivity, quality, and agility benefits that have significant competitive value.
Big data analytics consists of 6 Cs in the integrated Industry 4.0 and cyber physical systems environment. The 6C system comprises:
Connection (sensor and networks)
Cloud (computing and data on demand)
Cyber (model & memory)
Content/context (meaning and correlation)
Community (sharing & collaboration)
Customization (professionalization and value)
In this scenario and in order to provide useful insight to the factory management, 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.
Impact of Industry 4.0
Proponents of the term claim Industry 4.0 will affect many areas, most notably:
Manufacturing Sales: Companies like Logic-bay Corporation have released multiple resources addressing Industry 4.0 in the manufacturing sales channel.
Product life cycles
Industry value chain
Workers' education and skills
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".
An article published in February 2016 suggests that Industry 4.0 may have a beneficial effects for emerging economies such as India.
The aerospace industry has sometimes been characterized as "too low volume for extensive automation" however Industry 4.0 principles have been investigated by several aerospace companies, technologies have been developed to improve productivity where the upfront cost of automation cannot be justified, one example of this is the aerospace parts manufacturer Meggitt PLC's project, M4. The discussion of how the shift to Industry 4.0, especially digitization, will affect the labor market is being discussed in Germany under the topic of Work 4.0.