A short presentation on how manufacturing industry is changing to smart manufacturing. And What technologies are used into it.

1. Harison Xavier
Corporate BBA + MBA 2018
Management Information
Systems

2. Manufacturing

3. Introduction to
Manufacturing Industry
Manufacturing industries came into being with the
occurrence of technological and socio-economic
transformations in the Western countries in the
18th-19th century.
Manufacturing industries are important for an
economy as they employ a huge share of the
labor force and produce materials required by
sectors of strategic importance such as national
infrastructure and defense.

4. Workspace
Working conditions were terrible during the Industrial
Revolution.
With a long line of people willing to work, employers
could set wages as low as they wanted because people
were willing to do work as long as they got paid.
People worked up to sixteen hours a day for six days a
week.Factories were not the best places to work.
Even children were given jobs. The use of children as
labor for such long hours with little pay led to the
formation of labor unions.

5. Time have passed, there are still unsafe workplace for
employees around the world. Factories are fast
changing.
The sector are bringing in ‘one family‘ principle at its
core with good infrastructure to support it.
Use of latest technology and diverse learning
opportunities motivates employees.
Leadership gives immense focus on employee welfare
and promotes a culture of healthy work life balance.
Seniors are approachable and supportive and
employees are given empowerment and liberty to
function.

6. Reason for implementing smart manufacturing
Streamlined and automated data
Predictive maintenance
Significant cost reductions
Reduce workforce challenges
Enhanced productivity
Efficient IoT Integration and Implementation

8. List of Smart processes
❖ The Implementation of IIoT
❖ Artificial Intelligence & advanced analytics in Manufacturing
❖ Blockchain in Manufacturing
❖ Robotics
❖ Cybersecurity
❖ Additive manufacturing
❖ Big Data Analytics

9. Difference between what was
practiced earlier Vs. smart practice

10. V1
V2
V3
WH Station A Station B Station C
Final Process
Quality
Test
Distribution
Wholesale
/Retail
FINISHED
GOODS
Manufacturing Plant
Paint/
Assembly
WH - Warehouse

11. V1
V2
V3
WH Station A Station B Station C
Final Process
Quality
Test
Distribution
Wholesale
/Retail
FINISHED
GOODS
Manufacturing Plant
Paint/
Assembly

12. Vs.

13. Ford (1903)
Ford Motor Company, commonly known as Ford.
Henry Ford launched the industry's first moving
assembly line in 1913.
Horse-drawn carriages were used to deliver each frame
to the workers.
In the 1940s, formed the company's first Automation
Department.
By the end of the decade, Ford had built a sheet metal
stamping plant, installing hundreds of self-regulating
machines ahead of the official opening in 1950.

14. ❖ In 2012, robots with with laser-guided "eyes" were
installed.
❖ Rather than blindly placing parts on the car, these
new machines could detect the position of objects
and adjust themselves accordingly.
❖ Robots are used to install windshields and fenders
on the new Fords.
❖ There are now 8,797 units build a day around the
world.

15. Tesla, Inc. (2003)
Tesla has established a smart factory in which a network
of devices, sensors, IOT and robots works together
within an integrated system to produce cars and
batteries more efficiently.
The development of novel digital technologies
connected to the Internet of Things, along with
advancements in artificial intelligence and automation, is
enabling a new wave of manufacturing innovation.

16. “Smart factories” will leverage industrial equipment
that communicates with users and with other
machines, automated processes, and mechanisms
to facilitate real-time communication between the
factory and the market to support dynamic adaptation
and maximize efficiency.
Manufacturers are heeding the call and beginning the
journey toward implementing the smart factory
concept.

17. Benefits Of Smart Manufacturing
❖ Remote monitoring of the equipment in Real-time, alerts to operational risks
❖ Higher and uniform quality of manufacturing products
❖ Reduced downtime of equipment thereby improving productivity and optimizing
inventory costs.
❖ Optimization of Maintenance schedule with increased MTBF. (Mean time between failures)
❖ Ensures the safety of the workforce
❖ Facilitates lower servicing costs
❖ Decentralised control of production
❖ Virtual planning of products
❖ Reduce wastage.

19. Reference Note Only
Streamlined and automated data: Smart technologies automate data collection and provide advanced production
analytics, so managers can make more informed decisions. In a smart operating environment, manufacturers can tie
their operations technology with business systems to measure their key performance indicators against business
goals.
Predictive maintenance: With better visibility, manufacturers can predict and resolve maintenance issues before
they lead to downtime or product-quality issues. For example, sensors affixed to machines or devices may send
condition-monitoring or repair data in real time, so manufacturers can identify problems more efficiently.
Significant cost reductions: Manufacturers can identify waste and increase forecast accuracy when their operations
and enterprise systems are connected. They have better insight into supply chain issues, such as inventory levels and
delivery status, as well as demand cycles. With this information, they can reduce costs related to excessive inventory
or unexpected production volume.
Reduce workforce challenges: Automation helps manufacturers launch and complete projects with fewer workers.
Having real-time access to data across multiple platforms frees workers to focus on their core responsibilities. This
allows manufacturers to innovate faster without investing in additional resources.
Enhanced productivity: Smart, connected systems help factories improve throughput. In a connected enterprise,
manufacturers have seamless visibility into bottlenecks, machine performance, and other operational inefficiencies.
With this data, manufacturers can make adjustments to increase yields, improve quality, and reduce waste.