Industrial engineering 4.0

Industry 4.0
by
Pramod Kathmore
(G.H Raisoni College of engineering
and Management, Pune)

Industry 4.0
Industry 4.0 is a name given to the current trend of
automation and data exchange in manufacturing
technologies. It includes cyber-physical systems, the
Internet of things, cloud computing and cognitive
computing. Industry 4.0 is commonly referred to as the
fourth industrial revolution.
𝑃𝑟𝑎𝑚𝑜𝑑𝐾𝑎𝑡ℎ𝑎𝑚𝑜𝑟𝑒

4
From Industry 1.0 to 4.0

Industry 1.0 and 2.0
Industry 4.0
• The first industrial revolution starts around
1780s through the introduction of mechanical
production facilities with help of water and
steam power.
• The second industrial revolution took place 30
years later when the first electricity powered
assembly line was built in 1870. The era of
mass production has begun.

Industry 3.0
The third industrial revolution started in the late
1960s when the first programmable logistic
controller (PLC) Modicon 084 was built. It
enabled production automation through the use
of electronic and IT systems.

Industry 4.0
The industrial revolution 4.0 is happening today
through the use of cyber-physical systems. It
means that physical systems such as machines
and robotics will be controlled by automation
systems equipped with machine learning
algorithms. Minimal input from human
operators will be needed.

How IIoT works
IIoT is a network of intelligent devices connected to
form systems that monitor, collect, exchange and
analyze data. Each industrial IoT echosystem
consists of:
• Intelligent assets that can sense, communicate
and store information about themselves;
• Public and/or private data communications
infrastructure
• Analytics and applications that generate business
information from raw data; and
• People.

Benefits of IIoT
• One of the top touted benefits the industrial
internet of things affords businesses is
predictive maintenance. This involves
organizations using real-time data generated
from IIoT systems to predict defects in
machinery, for example, before they occur,
enabling companies to take action to address
those issues before a part fails or a machine
goes down.

• Another common benefit is improved field
service. IIoT technologies help field service
technicians identify potential issues in
customer equipment before they become
major issues, enabling techs to fix the
problems before they inconvenience
customers.

• Asset tracking is another IIoT perk. Suppliers,
manufacturers and customers can use asset
management systems to track the location,
status and condition of products throughout
the supply chain. The system will send instant
alerts to stakeholders if the goods are
damaged or at risk of being damaged, giving
them the chance to take immediate or
preventive action to remedy the situation.

• IIoT also permits enhanced customer
satisfaction. When products are connected to
the internet of things, the manufacturer can
capture and analyze data about how
customers use their products, enabling
manufacturers and product designers to tailor
future IoT devices and build more customer-
centric product roadmaps.

• IIoT also improves facility management. As
manufacturing equipment is susceptible to
wear and tear, as well as certain conditions
within a factory, sensors can monitor
vibrations, temperature and other factors that
might lead to operating conditions that are
less than optimal.

IIoT versus IoT
• Although the internet of things and the
industrial internet of things have many
technologies in common, including cloud
platforms, sensors, connectivity, machine-to-
machine communications and data analytics,
they are used for different purposes.

• IoT applications connect devices across
multiple verticals, including agriculture,
healthcare, enterprise, consumer and utilities,
as well as government and cities. IoT devices
include smart appliances, fitness bands and
other applications that generally don't create
emergency situations if something goes amiss.

• IIoT applications, on the other hand, connect
machines and devices in such industries as oil
and gas, utilities and manufacturing. System
failures and downtime in IIoT deployments
can result in high-risk situations or even life-
threatening situations. IIoT applications are
also more concerned with improving
efficiency and improving health or safety,
versus the user-centric nature of IoT
applications.

IIoT applications and examples

• In a real-world IIoT deployment of smart
robotics, ABB, a power and robotics firm, is
using connected sensors to monitor the
maintenance needs of its robots to prompt
repairs before parts break.

• Likewise, commercial jetliner maker Airbus
has launched what it calls "factory of the
future," a digital manufacturing initiative to
streamline operations and boost production.
Airbus has integrated sensors into machines
and tools on the shop floor and outfitted
employees with wearable tech, e.g., industrial
smart glasses, aimed at cutting down on
errors and enhancing workplace safety.

• Another robotics manufacturer, Fanuc, is using
sensors within its robotics, along with cloud-
based data analytics, to predict the imminent
failure of components in its robots. Doing so
enables the plant manager to schedule
maintenance at convenient times, reducing
costs and averting potential downtime.

• Magna Steyr, an Austrian automotive
manufacturer, is taking advantage of IIoT to
track its assets, including tools and vehicle
parts, as well as to automatically order more
stock when necessary. The company is also
testing "smart packaging" that is enhanced
with Bluetooth to track components in its
warehouses.

Vendors in IIoT
There are a number of vendors with IIoT platforms, including:
• Ability by ABB, a power and robotics company;
• IoT System by Cisco, a networking company;
• Field by Fanuc, a supplier of industrial automation
equipment;
• Predix by GE Digital, an energy management company;
• Connected Performance Services by Honeywell, a software-
industrial company;
• Connyun by Kuka, a manufacturer of industrial robots
(created in partnership with Infosys, an IT consulting firm);
• Wonderware by Schneider Electric, an energy management
company; and
• MindSphere by Siemens, an industrial manufacturing
company.

The future of IIoT
• Bain & Company predicted industrial IoT
applications will generate more than $300
billion by 2020, double that of the consumer
IoT segment ($150 billion).

• Similarly, IDC Research reported the top three
industries investing in IIoT in 2018 are
manufacturing ($189 billion), with a focus on
asset management; transportation ($85
billion), with a focus on freight monitoring and
fleet management; and utilities ($73 billion),
with a focus on smart grids, while consumer
IoT spending will reach $62 billion.

• More optimistically, Accenture expects IIoT to
add $14.2 trillion to the economy in the same
time period, growing at a 7.3% compound
annual growth rate (CAGR) through 2020.

Industry 4.0 is a collective term
• For technologies and concepts of value chain
organization.
• Is based on the technological concepts of cyber-
physical systems, the Internet of Things and
the Internet of Services,
• Facilitates the vision of the Smart Factory
• Basic principle: By connecting machines, work
pieces and systems, intelligent networks are
created along the entire value chain that can
control each other autonomously

Some examples
• Machines which can predict failures and trigger
maintenance processes autonomously
• Self-organized logistics which react to unexpected
changes in production
• Siemens' PLC manufacturing plant in Amberg,
Germany automated the production of its
automation systems. The result is a reported
99.99885 percent “perfect” production quality
rate

Cyber-Physical Systems (CPS)
• Definition: A system of collaborating
computational elements controlling physical
entities.
• CPS are physical and engineered systems whose
operations are monitored, coordinated,
controlled and integrated by a computing and
communication core.
• They allow us to add capabilities to physical
systems by merging computing and
communication with physical processes.

• Monitors physical processes,
• Creates a virtual copy of the physical world
• Makes decentralized decisions.
• Communicates and cooperates with each
other and humans in real time, over
the Internet of Things

CPS Benefits
• Safer and more efficient systems
• Reduce the cost of building and operating the
systems
• Build complex systems that provide new
capabilities
• Reduced cost of computation, networking,
and sensing
• Enables national or global scale CPS’s

• A real-world example of such a system is the
Distributed Robot Garden at MIT in which a
team of robots tend a garden of tomato
plants.
• This system combines distributed sensing
(each plant is equipped with a sensor node
monitoring its status, navigation, manipulation
and wireless networking.

CPS in Manufacturing
• Comprise:
– smart machines
– storage systems and
– production facilities
• Is capable of
– autonomously exchanging information
– triggering actions
– controlling each other independently

Smart Manufacturing Leadership
Coalition (SMLC)
• A US initiative working on the future of
manufacturing
• Aim is to enable stakeholders in the
manufacturing industry
– To form collaborative R & D, implementation and
advocacy groups
– For development of the approaches, standards,
platforms and shared infrastructure
– That facilitate the broad adoption of
manufacturing intelligence

The Industrial Internet
• An initiative by GE to bring together the
advances of two transformative revolutions:
– (a) The myriad machines, facilities, fleets and
networks that arose from the Industrial
Revolution, and
– (b) The more recent powerful advances in
computing, information and communication
systems brought to the fore by the Internet
Revolution

Industry 4.0: six design principles
• Interoperability: the ability of CPS (i.e. work
piece carriers, assembly stations and products),
humans and Smart Factories to connect and
communicate with each other via the Internet of
Things and the Internet of Services
• Virtualization: a virtual copy of the Smart Factory
which is created by linking sensor data (from
monitoring physical processes) with virtual plant
models and simulation models

• Decentralization: the ability of CPS within
Smart Factories to make decisions on their
own
• Real-Time Capability: the capability to collect
and analyze data and provide the insights
immediately

• Service Orientation: offering of services
(of CPS, humans and Smart Factories) via
the Internet of Services
• Modularity: flexible adaptation of Smart
Factories for changing requirements of
individual modules

Differences between a typical factory today
and an Industry 4.0 factory
Current industry environment
• Key to success is providing high-end quality service or product
with the least cost
• Achieve as much performance as possible to increase profit.
• Data sources are used to provide worthwhile information
about different aspects of the factory.
• The utilization of data for understanding the current condition
and detecting faults and failures is an important topic to
research.

Industry 4.0 Factory
• In addition to condition monitoring and fault diagnosis,
components and systems are able to gain self-awareness
and self-prediction
• These 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

• Force factory management to trigger required
maintenance at the best possible time to reach just-in
time maintenance and gain near zero downtime
• Modern information and communication technologies
like CPS, Big Data and Cloud Computing help predict the
possibility to increase productivity, quality and flexibility.
Industry4.0 Factory

Comparison of today’s factory and an
Industry 4.0 factory

Industry 4.0: Challenges
Economic
• High economic costs
• Business model adaptation
• Unclear economic benefits/ excessive
investment

Social
• Privacy concerns
• Surveillance and distrust
• General reluctance to change by stakeholders
• Threat of redundancy of the corporate IT
department
• Loss of many jobs to automatic processes and IT-
controlled processes, especially for blue collar
workers

Political
• Lack of regulation, standards and forms of
certifications
• Unclear legal issues and data security

Organizational/ Internal
• The security problems of information technology (IT)
are greatly aggravated by the reuse of previously
completed projects.
• The need for reliability and stability for critical
machine-to-machine communication (M2M)
• including very short and stable waiting times.
• The integrity of production processes must be
maintained.
• Avoid any unforeseen obstacle to information
technology that can cause expensive production
downtime.

• Industrial know-how must be protected.
• There is a lack of appropriate expertise that
would speed up the progress towards the
fourth industrial revolution.
• Redundancy in information technology (IT).
• It is difficult for affected parties to change.
• Automated and IT-driven processes result in
the loss of jobs, especially in the lower-tier
social strata

Industrial engineering 4.0

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