Topic: BusinessDecision Making

Last updated: June 23, 2019

I. INTRODUCTIONIndustry 4.0 is a vision of tomorrow’s manufacturing products finding their way independently through the production process. In intelligent factories machines and products communicates with each other cooperatively driving production raw materials and machines are interconnected with each other using Internet of things. The Objective of this system is to have highly flexible individualized and resource friendly mass production.

The Fourth Industrial Revolution urges us to think creatively about the manufacturing process, value chain, distribution and customer service processes. In the meanwhile, the future of education emphasizes the immense need to look beyond these areas and strategically utilize the “Internet of Things” to prepare the coming workforce for the challenges ahead.For manufacturing companies Industry 4.0 means improved efficiency and flexibility – even the advent of previously unattainable capabilities. The ability to economically produce small-batch “one-off” production runs without regard to the economies of scale is just one of the benefits that will accrue from the new order.As approaches like Industry 4.0 gain popularity, the characteristics of data to be analyzed change.

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Some processes require high-speed data whose value diminishes over time. Heterogeneous IoT devices and sensors produce unstandardized and unstructured data. IT industry continuously comes up with new models which can use distributed architectures to process data more quickly and efficiently. However, available analysis methods are insufficient to use high-speed data flowing from various sources due to their lower level complexities and shortcomings 1 II. HISTORY OF INDUSTRIAL REVOLUTIONAt the end of 18th century, the first steam engines and the intelligent use of hydropower revolutionized production. The late 19th century saw the rise of electrical engineering and mass production. The 1st moving belt conveyor was used as long as 1870 and slaughterhouse.

In the mid-1970’s electronics and information technology began to expand rapidly into an industry. Siemens develop 1st production that was based on computer-assisted controls. 4th industrial revolution is still vision experts believe that it will become reality within next 20 years. In intelligent factories, everything is interconnected wirelessly. Fig. 1 Evolution of industrial automation.

A Graphics source is DFKIIII. ORIGINS OF INDUSTRY 4.0The birth of the fourth industrial revolution, namely Industry 4.0, is assumed to coincide with the Industry 4.0 initiative 2. Industry 4.

0 is a strategic initiative included by the German government as part of its High-Tech Strategy 2020 Action Plan, according to which the Internet-based technologies are used to improve all industrial processes, from manufacturing to distribution, from sales to post-sales. In the same period, similar initiatives were undertaken by other countries, such as Internet + in China 3 and Industrial Internet in the USA 4. All of them moved from the consideration that new paradigms such as Internet of Things (IoT), Cyber-Physical Systems (CPS), crowd sensing, crowdsourcing, cloud computing and Big data, which were already being used to turn “normal” environments into smart environments (e.g., Smart Homes, Smart Cities), could be integrated with industry-related processes to enhance their performance.Intelligence had been already introduced in industries thanks to embedded systems, i.e., systems made of devices where sensors and actuators are embedded and connected to a control unit via field buses 5.

However, traditional embedded systems are conceived as stand-alone systems. The technologies introduced by Industry 4.0 enable communication and cooperation among devices and stand-alone systems so that a higher level of intelligence can be provided to industrial processes 5,6. More specifically, there are two ways in which communication can provide intelligence to objects: (i) less capable objects can leverage the resources of smarter objects, whether they are located nearby or remotely (e.g., cloud computing). Accordingly, less powerful objects typical of the industrial scenario, such as sensors and RFID (Radio Frequency Identification) tags, can cooperate with other more powerful objects to perform smarter applications; (ii) communication can be used by objects that are already smart, such as smartphones, to “augment” their intelligence thanks to information collected by distributed objects, whether it is objective, coming from measures collected by sensors, or subjective, provided by humans.

This is the concept on the basis of crowdsensing and crowdsourcing, where big amounts of data gathered by multiple nodes are processed to get more complex information.According to these considerations, seamless ubiquitous Internet access, communication between intelligent machines and advanced analytics methods are to be considered the pillars of Industry 4.0 Future Internet 2018, 10, 24 3 of 14 revolutions 3, fostered by the IIoT 7,5 and CPPS 8 paradigms. IV. COMPONENTS OF INDUSTRY 4.01.

Simulation- Ideal for machinery and scenario planning2. Autonomous system- program machinery and robots to CT autonomously3. Cloud computing- user’s remote servers to store, manage and process data for faster access4. Additive manufacturing- digital 3D design data builds in layers by depositing materials5. Big data- It can determine the action and improve the process6. Cybersecurity- It protects manufacturer’s most valuable data7. IoT- It connects the Internet to a machine to send and receive process data.

8. Horizontal and vertical system integration- It enables truly automated value chains.V. WHAT MAKES A FACTORY INDUSTRY 4.01.

Interoperability- machines, devices, and people connect and communicate with each other.2. Information transparency- system create a virtual copy of physical world through sensor data.

3. Decentralized decision making- cyber-physical system make simple decisions to become as autonomous as possible.4. Technical assistance- System to support humans in making decisions and solving problems and assist with the task.


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