Industry 4.0

Industry 4.0 is the subset of the fourth industrial revolution that concerns industry. The fourth industrial revolution encompasses areas which are not normally classified as an industry, such as smart cities, for instance.

Although the terms “industry 4.0” and “fourth industrial revolution” are often used interchangeably, “industry 4.0” factories have machines which are augmented with wireless connectivity and sensors, connected to a system that can visualize the entire production line and make decisions on its own.

In essence, industry 4.0 is the trend towards automation and data exchange in manufacturing technologies and processes which include cyber-physical systems (CPS), the internet of things (IoT), industrial internet of things (IIOT), cloud computing, cognitive computing and artificial intelligence.

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 determining factor is the pace of change. The correlation of the speed of technological development and, as a result, socio-economic and infrastructural transformations with human life allow us to state a qualitative leap in the speed of development, which marks a transition to a new time era.

• Smart manufacturing
• Smart factory
• Lights out – (manufacturing) also known as dark factories
• Industrial internet of things – (also called internet of things for manufacturing)

Design principles and goals

There are four design principles in Industry 4.0. These principles support companies in identifying and implementing Industry 4.0 scenarios.

1. Interconnection – 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)
2. 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.
3. 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.
4. 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.

Before Industry 4.0

Industry 1.0 refers to the first industrial revolution. It is marked by a transition from hand production methods to machines through the use of steam power and water power. The implementation of new technologies took a long time, so the period which this refers to it is between 1760 and 1820, or 1840 in Europe and the US. Its effects had consequences on textile manufacturing, which was first to adopt such changes, as well as iron industry, agriculture, and mining although it also had societal effects with an ever stronger middle class. It also had an effect on British industry at the time.

Industry 2.0; the second industrial revolution or better known as the technological revolution is the period between 1870 and 1914. It was made possible with the extensive railroad networks and the telegraph which allowed for faster transfer of people and ideas. It is also marked by ever more present electricity which allowed for factory electrification and the modern production line. It is also a period of great economic growth, with an increase in productivity. It, however, caused a surge in unemployment since many workers were replaced by machines in factories.

The third industrial revolution or Industry 3.0 occurred in the late 20th century, after the end of the two big wars, as a result of a slowdown with the industrialization and technological advancement compared to previous periods. It is also called digital revolution. The global crisis in 1929 was one of the negative economic developments which had an appearance in many industrialized countries from the first two revolutions. The production of Z1 (electrically driven mechanical calculator) was the beginning of more advanced digital developments. This continued with the next significant progress in the development of communication technologies with the supercomputer. In this process, where there was extensive use of computer and communication technologies in the production process. Machines started to abrogate the need for human power in life.

Components of Industry 4.0

“Industry 4.0” is an abstract and complex term consisting of many components when looking closely into our society and current digital trends. To understand how extensive these components are, here are some contributing digital technologies as examples:

• Mobile devices
• Authentication and fraud detection
• Multilevel customer interaction and customer profiling
• Internet of Things (IoT) platforms
• Location detection technologies
• Advanced human-machine interfaces
• 3D printing
• Smart sensors
• Big data analytics and advanced algorithms
• Augmented reality/ wearables
• Fog, Edge and Cloud computing
• Data visualization and triggered “real-time” training

With the help of cyber-physical systems that monitor physical processes, a virtual copy of the physical world can be designed. Thus, these systems have the ability of making decentralized decisions on their own and reach a high degree of autonomy (for more information, see “Industry 4.0 characteristics). As a result, Industry 4.0 networks a wide range of new technologies to create value.

Industry 4.0 Drivers

There are three Industry 4.0 Drivers. These drivers support companies in identifying and implementing Industry 4.0 scenarios.

1. Digitization and integration of vertical and horizontal value chains – Vertically, Industry 4.0 integrates processes across the entire organization, for example processes in product development, manufacturing, logistics and service whereas horizontally, Industry 4.0 includes internal operations from suppliers to customers plus all key value chain partners.
2. Digitization of Product & Service Offerings – A seamless interconnected digital thread of product-service ecosystem to enable better lifecycle management by reducing friction in data and decision flow in manufacturing processes, supply chain and planning systems.
3. Digital Business models and customer access – Enable new digital business models by integrating customer experience into the core of digital transformation processes in order to create superior value and higher levels of customer intimacy.

Effects

The increasing use of the Industrial Internet of Things has spawned new applications including machines which can predict failures and trigger maintenance processes autonomously or self-organized logistics which react to unexpected changes in production.

Challenges

Challenges in implementation of Industry 4.0

Economic

• Implementation Costs
• Returns on Investment (ROI)

Social

• Trust
• Jobs redundancy
• Change management

Policies

• Regulations & standards
• IT & Data security

Organizational

• Executive commitment
• IT processes
• Program management
• Training

Role of big data and analytics

Modern information and communication technologies like cyber-physical system, big data analytics 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.

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.