How To Learn Industry 4.0?

 How To Learn Industry 4.0?

How TO Learn Industry 4.0?

 

Industry 4.0 is that the usage of fresh smart technologies for the enduring automation of outdated manufacturing and industrial practices. the web of Things (IoT), cloud computing, AI and machine-to-machine communication (M2M) are all integrated at a large scale for increased automation. This whole process may analyze and diagnose problems without the necessity for human intervention. Technologies like AI, machine learning, cloud computing, database technologies, big data analytics etc. are now a major need for industrial manufacturing companies.

History

German engineer, economist and executive chairman of the planet Economic Forum, Klaus Martin Schwab first introduced the phrase Fourth technological revolution (Industry 4.0) in 2015-16.

Industry 1.0
It was steam driving & production of machines with steam power. From 1770 – 1870 steam power drove flour mills to grind wheat & other small factories.

Industry 2.0
It was electric power production & driving machines with electric power. Machines were crude & “manual” with simple pressure, temperature gauges installed on the machines for reading the info locally on the equipment.

Industry 3.0
Industry 3.0 was related to the DCS system, data gathering by remote sensors connected by cables. The major inventions of the semiconductor, pc and thus the private computer and therefore the internet marked the Third technological revolution starting within the 1960s. this is often also mentioned because of the “Digital Revolution”.

Industry 4.0
IT technologies are changed manufacturing systems from simple external-combustion engines in the 1700s to today’s AI & machine learning based manufacturing where equipment communicates with one another using software technologies.

Key components of Industry 4.0

  • Mobile devices – laptop, iPad, SmartPhone
  • Location detection technologies including sensors on the assembly floor
  • Smart sensors on machines giving real-time data
  • Big data analytics & advanced algorithms including AI & machine learning
  • Lights out manufacturing ~ minimum head calculate production floor with maximum automation
  • Wearable headsets  and Augmented reality with video screens for training

Four design principles of Industry 4.0

  • Interconnection (Connection and communication ability of machines, sensors, and other people through IoT and IoP)
  • Transparency of knowledge (Collection of vast amounts of data and knowledge from all points within the manufacturing process by operators to enhance functionality)
  • Technical assistance (The ability to help humans with hard tasks)
  • Decentralized decisions (The ability of cyber-physical systems to make decisions on their own and check out to try to do their tasks as autonomously as possible)

Team Dynamics & Industry 4.0– Organizational Structure & Teams 

  • In Modern Manufacturing Organization
  • One of the highest organizational chart components is “team” and therefore the related concept of team development & team building. Teams are often both horizontal and vertical within the chart.
  • While a corporation consists of multiple sets of individuals who combine their individual skill sets, management skills & competencies to figure together – the standard of the chart ultimately depends on the combined competencies of the persons working in teams.
  • Any organization having quite 500 persons cannot function without task-based teams – and without clear team structure and assignments based teams – the economic manufacturing company will collapse and pack up.

 Deployment of digital Twins’ Technology For Vaccines & New Medicines Development

  • Digital Twin technology has long played a task in medical research, specifically within the area of clinical trials, where they will help measure the effectiveness of a therapy by applying an impact to at least one of a genetically similar pair.
  • A new company founded by a former principal scientist at Pfizer, has developed how of digitizing this idea through the utilization of AI.
  • Machine learning platform are built by Unlearn.AI, that builds “digital twin” profiles of patients that become the controls in clinical trials.
  • The unlearn approaches the thought of building these digital twins as a classic machine learning problem, using “clinical trial datasets from thousands of patients to make the disease-specific machine learning models wont to create Digital Twins and their corresponding virtual medical records.”
  • These are quite simple medical profiles – they match people according to demographics, lab tests and biomarkers.
  • The idea is that by building AI-based twins, there’s less of a requirement to hunt out similar actual pairs of people — actual twins, even — to run tests.

 Using Neural Networks google AdWords, Machine Learning & Advanced Algorithms

  • Google advertisement system is predicated on software cookies and on keywords requested by selling companies that want to advertise on Google. It uses these search words to prioritize & place relevant advertising on pages where Google’s advanced algorithms & AI software determines the very best relevance.
  • Clients companies of Google pay to Google when each user clicks on the Google searched & suggested the company to the selling company portal.
  • The Google Ads covers the whole world & includes local, national, and international sellers ~ supported the user’s location on the earth.
  • Google’s text advertisements are precise, focused, 95 % accurate ~ consisting of three headlines with a maximum of 30 characters each, 2 descriptions with a maximum of 90 characters, and a display of two internet sites links of 15 characters each.

Industry 4.0 technologies being deployed in India

1 – CtrlS
It is ranked as Asia Pacific’s largest Tier-4 data centre and managed services provider. It has five world-scale data centres in Hyderabad, Mumbai, Noida, Bangalore, and Chennai. The corporate has more than 3, 500 Indian companies and global multinationals as customers. The data centre in Mumbai could also be 1,000,000 sq. ft. having the capacity to host 50, 000 racks and uses 100 MW electrical power.
2 – ESDS
ESDS has great worth in Banking & Finance, Manufacturing, Education, Energy & Utilities, Healthcare, eCommerce, Agriculture, IT, Entertainment & Media, Telecom, Government and Travel & Tourism.
3 – GPX Global Systems Inc.
GPX has 30, 000 square feet of a data centre in Mumbai. It has a second data centre in Mumbai is 60, 000 square feet with 16 MW of total electric power use.
GPX’s customers have included Telcos, Cloud Service Providers, Internet Service Providers, CDNs, e-businesses and enterprise clients.
4 – Netmagic (NTT Communications Company)
Netmagic is a  subsidiary of NTT Communications Japan, could even be a variety one managed to host and multi-cloud hybrid solution provider with 9 carrier-neutral, state-of-the-art hyperscale and high-density data centres.
It serves from India quite 2, 000 enterprises globally including NTT Communication’s customers across the Americas, Europe and Asia-Pacific region.
5 – NxtGen
NxtGen facilitates their customers to make their digital business without investing and managing complex IT infrastructure, by leveraging its hyper-converged infrastructure.
NxtGen deploys and offers IT infrastructure services from both or a mix of on-premise resources and its own facilities – Infinite DatacenterTM, empowering its customers to adopt the foremost recent hybrid computing model.

AI & Machine Learning Systems & Oracle eAM Integration For Industry 4.0

Machine learning and AI integration into Oracle eAM
Oracle eAM to use AI to detect the maintenance schedules
Oracle eAM to use AI to predict a breakdown
Oracle eAM to impress the data directly from apps like Emerson Delta V smartphone app for updating its database

Industry 4.0 implementation challenges

During the implementation of Industry 4.0 challenges are being faced such as; political Lack of regulation, standards and sorts certifications
Unclear legal issues and data security),
Social
Privacy concerns
Surveillance and distrust
Economic
High economic costs
Business model adaptation
Organizational
IT security issues
Reliability and stability required for critical machine-to-machine communication (M2M), including very short and stable latency times
Need to look out at the integrity of production processes
There is a need to avoid any IT snags, as those would cause expensive production outages
Need to guard industrial know-how. Lack of insufficient skill-sets to expedite the transition towards a fourth technological revolution
Low top management commitment
Insufficient qualification of employees

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