In today’s world, digital transformation is not a choice for businesses anymore. Yes, it has become a necessity due to its limitless opportunities to help them grow.
By implementing the digital transformation in manufacturing, companies can easily enhance their productivity and efficiency.
Today, I will reveal the top advantages of digital transformation in manufacturing and its upcoming trends.
Here we will discuss:
1. Current Challenges Among Manufacturers that Digital Transformation Can Tackle
2. Digital Transformation Benefits in Manufacturing
3. Top Digital Transformation Trends in Manufacturing 2022
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“The biggest part of our digital transformation is changing the way we think.”- Simeon
Preston, CEO, Bupa.
In today’s world, digital transformation is not a choice for businesses anymore. Yes, it
has become a necessity due to its limitless opportunities to help them grow.
By implementing the digital transformation in manufacturing, companies can easily
enhance their productivity and efficiency.
Did you know that 67% of manufacturers have accelerated digital projects because of
COVID-19?
Manufacturing companies have realized that they need to innovate their business to
keep up with the changes taking place at the global level. Being in the industry, if you
also want to know more about it, then this blog is for you.
Today, I will reveal the top advantages of digital transformation in manufacturing and
its upcoming trends. However, let me first take you through some of the
manufacturers’ current challenges.
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Digital Transformation in Manufacturing…
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Current Challenges Among Manufacturers that
Digital Transformation Can Tackle
The challenges making a digital transformation company core necessity for today are
many, and I have mentioned the key ones here:
4. many, and I have mentioned the key ones here:
1. Product Delivery Challenges
Many transaction points often result in stockouts and high order turnover rates.
Short product lifecycles lead to discontinuation or obsolescence issues.
Late shipments with little or no information on the cause of delay, making it difficult for
customers to plan their business operations accordingly.
2. Cost of Quality Challenge
Customers may complain of defective products, resulting in excess costs that manufacturers will
need to incur.
Short product lifecycles can cause supply chain problems. For instance, it is difficult for suppliers
to produce parts on time if there is any uninformed change at an initial stage.
It is challenging for manufacturers to track defects.
Defects may be considered one‐time problems instead of being tracked, leading to false
projections. This can result in incorrect pricing and incorrect inventory management practices.
3. Organizational Capability Challenges
High variability in productivity due to lack of demand visibility.
Fewer interactions among business units and suppliers lead to higher operating costs.
It is challenging to conduct continuous improvement activities because of managerial focus.
4. Operational Challenges
COVID-19 has also revealed the significance of digital technologies in the
manufacturing industry.
Throughout the pandemic, manufacturers like you encountered operational difficulties that
encouraged the flaws in their current businesses.
Real‐time data regarding the supply chain could allow manufacturers to respond quickly to
supply deficiencies.
Check out the image from the Manufacturer’s study and IBM showing the techniques
manufacturers concentrated on during COVID-19 and could profit from digital
technologies.
5.
5. Productivity Challenge
Traditional management approaches are no longer effective in improving profitability.
Operational excellence is more significant pressure, resulting in new tools and technologies.
High variability due to lack of demand visibility results in lower productivity rates. This also makes
it difficult for organizations to adjust their capacity and workforce.
6. Innovation Challenge
Traditional management approaches are no longer effective in improving profitability.
There is more significant pressure for operational excellence, resulting in developing new tools
and technologies to improve quality, efficiency, and competitiveness.
High variability due to lack of demand visibility results in lower productivity rates. This also makes
it difficult for organizations to adjust their capacity and workforce.
6. Digital Transformation Bene몭ts in Manufacturing
“We have seen more Digital transformation in 2 months than in the last 2 years” Satya
Nadella, CEO, Microsoft.
By implementing digital transformation in manufacturing, companies can improve
their operational efficiency by increasing productivity and optimizing costs. Some of
the main benefits of adopting a digital platform for your manufacturing business are as
follows:
7. follows:
1. Increased Productivity – Who Doesn‘t Want that?
By adopting digital tools for Manufacturing, companies can easily enhance their
effectiveness and increase the number of products manufactured per year. It also
leads to reduced costs per product due to automation. Also, it helps in reducing non-
productive time (NPT), which leads to improvement in profit.
2. Improved Customer Experience As Customer is King!
By implementing digital transformation, companies can easily cater to their
customers’ needs and give them the best possible experience. With the presence of
new technologies like social media, analytics, IoT, etc., they can keep themselves
updated about their target market’s requirements and offer them what they want. It
also helps in improving relationships with their customers.
3. Better Workforce Management to Avoid Any Hassle and Delays!
Digital transformation in Manufacturing companies helps optimize human resources
and boost overall productivity by automating business processes. It aids in reducing a
significant amount of the workload, increasing the number of products manufactured,
and optimizing labor costs. By implementing digital tools, companies can have better
control over their workforces.
4. Competitive Edge – Don‘t You Want to be at the Top?
By implementing digital transformation, companies can gain a competitive edge by
using modern tools like IoT, analytics, social media, etc., to understand their target
customer better and offer them improved products that they want. By optimizing
business processes with digitization, companies can gain the upper hand over their
competitors.
5. Improved Decision Making, Which is Really a Big Concern
8. Digital transformation helps businesses make informed and accurate decisions to
visualize and analyze product data to improve quality, performance, and productivity. It
also offers companies a better picture of the market by providing better insights into
customer behavior and purchasing power. Also, it helps in getting accurate and real-
time information about the cost and time involved in various processes.
6. Improved Inventory Management – No Manual Checks Any More!
Digital transformation helps companies stay updated by integrating their inventory
management systems with modern tools like IoT, social media, analytics, etc.
Companies can avoid performing manual checks or wasting time finding the data by
implementing digitization. It helps them keep track of the inventory and remain
updated about products’ location, quantity, quality, etc.
7. Reduced Costs that Every Business Looks Forward to
Companies can reduce cost per product by increasing productivity and efficiency via
digitization. They can manage their expenses more effectively by using advanced tools
like analytics, machine learning, etc., to optimize processes and infrastructure. Also,
they can reduce waste by finding out various activities that are non-value adding or
time-consuming.
8. Improved Inventory Visibility -Transparency is the Key to Success!
Companies can improve their equipment management by integrating different
technologies like IoT, social media, etc., through digital transformation. It also helps
them trace each piece of equipment and provides accurate data about the location,
usage, market value, etc., of equipment. This, in turn, helps them manage their
inventory better and reduces the theft of expensive equipment.
9. Better Strategies that Lead to Higher Growth!
Companies can implement better strategies by using innovative technologies like
9. machine learning to develop analytical reports and respond to customer demands
faster than ever before. It helps companies stay ahead of the curve and understand
their customers better, improving their reputation.
11. 1. Autonomous Systems
Autonomous systems leverage information about the surrounding atmosphere from
sensors. It includes cameras, light & audio sensors, infrared, radar, ultrasound, and
more to explore real-time situations, adapt, and react without human intervention.
Some autonomous systems in manufacturing include:
Autonomous robots
Drones
Autonomous warehouse and factory systems
2. IIoT
12. Industrial Internet of Things (IIoT) is a sub-category of IoT that concentrates on apps in
industrial domains. IIoT is revolutionizing the manufacturing sector by allowing
businesses to regulate the production process instantly. It even helps them to make
more data-driven conclusions with manufacturing analytics. As per McKinsey
prediction, IIoT will be a $500B market by 2025. Advantages of IIoT technologies
include:
Predictive maintenance
The energy efficiency of individual machines
Demand forecasting
Supply chain visibility
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3. Robotics
13. Robotics is an approach to manufacturing that applies machines, tools, computer
control systems, and software. It is possible to use Robotics in various manufacturing
processes, including flexible automation for consumer goods, semiconductors,
telecommunication equipment, pharmaceuticals, etc. Some examples of robotics in
production include:
Machine‐made furniture
Ironing robots
Autonomous maintenance robots
Industrial robots
4. Cloud Robotics
It leverages the power of cloud computing to store, process, share and analyze data
generated by smart devices or machines that include sensors, microcontrollers,
networked systems, etc.
Also, cloud robotics allows corporations to remotely monitor their production process
using real-time data, perform predictive maintenance and make informed decisions to
improve efficiency. The key to implementing cloud robotics is to exploit the seamless
interoperability of cloud technology and robotic technologies.
Some examples of cloud robotics applications in manufacturing include:
14. Some examples of cloud robotics applications in manufacturing include:
Remote surveillance of machines and processes
M2M communication between robots, smart devices, and other connected equipment
Predictive maintenance
5. 3D Printing
Additive manufacturing is a form of 3D printing that adds material layer-by-layer to
create a customizable product for specific applications. 3D printing is suitable for
prototyping and direct investment casting.
However, it has limitations in terms of accuracy and surface finish. To overcome these
restrictions, you can 3D print materials like metals and ceramics.
With 3D printing, you can even produce surgical implants based on CT scans of specific
individuals, while some companies even use 3D printing to manufacture entire
buildings.
6. Digital Twins
It is a virtual representation of a physical object or system, which you can use to
monitor the performance of the object in real-time, predict potential problems and
improve efficiency.
The technology behind digital twins uses data generated by sensors attached to
physical assets, which are then transferred to the cloud for storage, analysis, and
visualization. Some examples of digital twins in manufacturing include:
Industrial process and equipment monitoring
Lubricant usage tracking for optimum performance
Plant equipment condition assessment
7. Industry 4.0
15. Industry 4.0 is a word coined by the German government to represent an evolution in
manufacturing that will enable smart factories to use digital technologies like cloud
robotics, IIoT, and Big Data. It promises to establish communications among intelligent
objects (IoT) capable of:
Sensing their location relative to other objects/equipment
Collecting and analyzing data to optimize performance
16. And transferring real‐time data to SCADA, MES, and ERP systems for effective control over the
production process.
Some benefits of Industry 4.0 include:
Improved predictive maintenance
Virtual commissioning, training & servicing of products
Optimized production planning and supply chain management
8. Augmented Reality
AR or augmented reality is a type of user interface technology that superimposes
computer-generated enhancements on the real world, allowing for contextual
information to be displayed in sync with a person’s natural line of sight, thereby
creating a more immersive experience. Some examples of AR technologies in
manufacturing include:
User manuals and training videos integrated with assembly instructions on product workbenches
Virtual equipment or machine calibration/servicing
Inspection & quality control with video overlay on physical functions
9. Robotic Process Automation (RPA)
A form of software automation, RPA is a business process management system. It
allows employees to configure computer software or a “robot” to capture and analyze
existing apps to automate business processes.
RPA robots are capable of understanding natural language, interpreting relevant data,
initiating transactions, retrieving information from external sources, communicating
with other digital systems, and interfacing with both humans via chatbots and non-
technical users through the form of GUIs.
RPA is used in many processes related to manufacturing, e.g.:
Tasks with low human intervention requirements
Functions with high transaction volume
Operations in physically distributed environments
Applicable in cases where there is a need for processing large volumes of data and an inability to
17. use advanced analytics
10. Data Analytics and Machine Learning
Machine learning is an app of AI focusing on developing computer programs that can
teach themselves to evolve as they acquire new data. Data analytics refers to
strategies and tools for examining, organizing, analyzing, and interpreting several data
sets to discover patterns and identify trends within the data.
Some examples of machine learning algorithms used in manufacturing include:
Regression Analysis
Decision trees
Clustering analysis
Recommender systems or predictive analytics
Process optimization with process mining techniques
Time‐series forecasting and anomaly detection
Final Thoughts
Manufacturing has become an increasingly capital-intensive facility as it takes much
more money to buy equipment and employ people to produce goods. Indeed,
companies are discovering ways to cut costs while increasing production.
Some of the technologies discussed above promise to address these challenges by
reducing waste, optimizing processes, ensuring quality control, and increasing
productivity.
However, you cannot deploy such drastic changes in your business just like that. There
is a need for expertise, and a digital transformation consulting company can help you.
If you still have queries, mention them in the comment section below. All the best! I
hope you have found this blog useful.
18. Frequently Asked Questions
Ques. Which manufacturing technologies are most important?
The manufacturing technologies that will benefit your company depend on several
factors: product type, market, cost structure, and geography. Analyzing your current
production processes using a structured approach can help you determine which
technologies hold your organization’s most significant potential.
Ques. What is digital transformation in the manufacturing industry?
Digital Transformation is transforming a business with the help of new and emerging
technologies. It is all about integrating advanced tools with re-defined processes and
culture to deliver value and improve operational excellence in manufacturing.
Ques. What are the most promising digital innovations for manufacturers?
There is a wide variety of digital technologies that manufacturers can use to improve
the performance of their processes. Some of the technologies you should consider are
Data Analytics, Big Data, Machine Learning, Robotic Process Automation, Artificial
Intelligence, and Cloud Computing.
Ques. What are the four main areas of digital transformation?
The four areas of digital transformation are-
Data‐driven decision making
Process excellence
New product innovation
19. Technologies Software Development Services Solutions Other useful links
New product innovation
Digitizing the workforce
What are digital transformation initiatives?
The digital transformation initiatives are many, and a few of them are-
Digitizing the workforce
Product development and design
Supply chain collaboration
Customer experience management and production
What are the key trends in digital transformation in 2021?
Here are the four key trends in digital transformation-
Data‐driven decision making: Data will be used to make real‐time decisions.
Intelligent automation: AI and robotics will perform repetitive, expensive, and demanding tasks
for humans to do.
The digital evolution of jobs: New jobs that don’t exist today will emerge because of the digital
transformation.
The IoT will take off: The Internet of Things will enable the integration of all types of equipment.
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