Digital Transformation in Manufacturing: Unlocking Efficiency and Innovation

Fourth industrial revolution is upon us: digital transformation in manufacturing. Often denoted as “Manufacturing 4.0,” the revolutionary change integrates digital technologies like artificial intelligence, machine learning, blockchain, and IoT with the massive data easily available to manufacturers. When done right, digitization can turn into digital transformation – a movement that enables businesses to improve productivity, lower costs, elevate workplace safety and chart the path for the manufacturing domain’s future.

This is not all.

Successful manufacturing digitalization efforts come with the potential to evidently boost market share and business’s reputation, while improving their ability to attract key stakeholders. But, as with any industry-wide revolution, manufacturers who are too slow will be in a constant danger of being left behind. In its current state, while a number of manufacturers have started their Manufacturing 4.0 journey, very few have attained the advanced stage of maturity.

While it is clear that digitalization has become imperative for manufacturing houses, change can be difficult. In this situation, how can companies successfully move towards digitalization?

Well the first step would be to understand the impact of digital transformation manufacturing 4.0 in-depth.

Just what we are going to talk about today.

The Current State of Manufacturing Digital Transformation

Even though the transformation of digitalization to digital transformation is critical in the manufacturing space, very few manufacturers have started the journey. Here’s the validation.

• Only 24% of manufacturers currently have a digital transformation strategy in place.
• Due to COVID-19, 18% of manufacturers accelerated their digital transformation efforts. Conversely, 35% had to decelerate implementation, while 47% remained unaffected, largely because 42% had not yet initiated the process.
• The primary anticipated benefits of digitalizing processes include reduced costs (50%) and enhanced data visibility (39%).
• The most common challenges of digital transformation in the manufacturing industry cited are a lack of clear direction, insufficient funds, and difficulties in migrating from legacy systems.
• Nearly 50% of manufacturers seek guidance from consultants to navigate digital transformation.
• While 34% of manufacturers foresee needing more than two years to achieve meaningful progress, only 10% believe they can accomplish this within six months.
• Manufacturers typically gauge the success of digital transformation by assessing ROI and reductions in labor costs.

Now even though all the statistics around manufacturing digitalization point at the fact that it is time to make the move, we cannot ignore how difficult the transformation could be specially when several challenges stand in the way, such as:

• Skills gap when traditional manufacturing systems have to be integrated with digital technologies
• Reliance on legacy systems mixed with a lack of awareness and incentive to digitalize systems
• The need for complete structural changes
• Lack of upper management buy-in
• Resistance from suppliers

Facing similar challenges? Let us give you some evident benefits of digital transformation in manufacturing that would make the decision easier.

Benefits of Digital Transformation in Manufacturing

Manufacturing houses have already come a long way in adopting new digital technologies; toolsets that are not just improving internal operations but also drastically changing customer experience. Here are some advantages that manufacturers are bound to expect as they delve deeper in the transformative journey.

Data Visibility

Prior to digital tools introducing a sea-full of possibilities, manufacturers could only get insights into the manufacturing process and outcome by being physically present on the floor. Today, digital transformation has the potential to empower manufacturers with real-time visibility of every operation.

This high-level data visibility is great for real-time tracking as well. By having complete transparency, manufacturers can get a comprehensive idea of what’s happening with the supply chain at any given time and what can be done to optimize the goods’ flow. Real-time data insights also play a huge role in preventing stock shortages, as well as lowering excess inventory count.

Accurate Predictability

Imagine having the ability to predict problems much before they even start impacting the processes and operations. This is what predictive maintenance and data analytics does for the manufacturing industry. By predicting probable issues, digital transformation can better consistency, lower operational costs, and keep the system downtime at all-time lows.

Greater Operational Efficiency

Digital transformation doesn’t just help manufacturers make accurate predictions, but also improves operational efficiency by streamlining and digitalizing manual processes. Backed by automation tools run by machine learning, artificial intelligence, and other automation tools can lower the probability of human error, save time spent on performing repetitive tasks, and open up time for teams to focus on sophisticated parts of the manufacturing cycle.

Better Quality Control

Human eye has its own limitations when it comes to spotting issues, damages, or even patterns. To counter this, artificial intelligence and machine vision serve as digital technologies that can easily spot data inconsistencies and issues that are otherwise difficult to identify. When integrated properly in the system, these tools can drastically cut down the scrap and rework time.

Improved Customer Experience

The number one reason why businesses trust digital transformation is its multifaceted benefits specific to customer experience improvement. By personalizing products’ recommendations, tracking order status with heightened accuracy, or simply offering real-time support, digital transformation in industrial manufacturing is setting up new standards in the CX department. Ultimately, when manufacturing businesses give better customer experience, they create stronger relationships and improve the probability of repeat client base.

Lowered Time-to-Market

Digital transformation tool sets can expedite the time it takes to launch a new product in the market by creating efficient systems for prototyping, product’s development, and testing. The role of digitalization in manufacturing is two fold: it doesn’t just speed up the development cycle but also the time between cycles in a way that manufacturers are able to respond quickly to new demands. These operational-level enhancements give manufacturing businesses the competitive edge which is needed to continuously grow in the market.

Clear Regulatory Adaptability

Reducing the go-to-market time is just one side of how digital transformation is making manufacturers adaptable to fast-changing market conditions. Adhering to regulatory standards is another critical side of the coin. While pivoting to a digital-first system can help manufacturing houses pivot quickly and meet these evolving customers needs, meeting regulatory requirements like IT safety, data protection, and environmental impact is equally important and leading digital transformation services providers understand this perfectly.

Lowered Costs and Improved Margins

Every factor that we covered above can in one way or the other lower costs across multiple manufacturing elements.

• Inventory management can lower long-term spend.
• Predictive maintenance can bring down the system downtime while drastically reducing the times an equipment had to be replaced.
• Customer experience improvement can lower costs linked with getting new customers.

As businesses work on making manufacturing improvements through digital transformation tech stack, they are bound to see a decline in expenses and an evident rise in profit margins.

Before we proceed, it is critical for businesses to note that these benefits of digital transformation in the manufacturing industry would only be validated when transformation is happening on an end-to-end level. Here’s what we mean by that.

The Four Domains of Digitalization in Manufacturing

Now that you know the current state of the digital manufacturing market and the benefits of digital transformation in manufacturing, the next step is to decide what part of the process to digitalize.

Here are the four areas that manufacturers tend to give most attention in their transformative journey.

Process Transformation

When approaching digital transformation in manufacturing, this is one of the key areas that is all about altering how you do things. Look into your daily business process, whether it’s manufacturing, customer service, or order management and find scope for integrating digital technology to make them more efficient. For example, you can use automation tools in the production line to speed up the workflow and lower the chances of error.

Business Model Transformation

This transformation goes much deeper than simply modifying how things get done; it’s about completely changing the foundation of your business.

It’s about bringing a complete shift. In terms of digital transformation in manufacturing, it will be changing how you generate money and approach your customers’ interactions and experience. One way companies are embracing this is by using subscription models or providing digital services in addition to physical products, to effectively transform their complete business model and align it with the digital age.

Domain Transformation

This stage of transformation aims at enabling businesses to expand or move to new digital sectors or audiences. It might be as drastic as a brick-and-mortar retail company expanding into e-commerce or something fairly straightforward as a manufacturing firm using IoT to offer smart solutions.

Domain transformation here will not just help manufacturers explore new domains and blindspots which were earlier unreachable but also ensure success in the venture.

Cultural Transformation

This is hands-down the most critical and challenging part of digital transformation in the manufacturing industry. It’s all about building a new digital culture inside your organization.

This level of transformation would call for a mindset shift, pushing agility, innovation, and the willingness to adapt to new working models.

To achieve this, extensive staff training will be necessary to alter the company’s structure for supporting digital initiatives, and foster an ecosystem where digital-first thinking is normal.

Once you have identified the areas for digital transformation of manufacturing, the next key aspect that should be considered is the correct adoption of tech in digital transformation manufacturing.

The Key Tech in Digital Transformation Manufacturing

Although technologies like AI, Blockchain, and IoT form the foundation of digital transformation in industrial manufacturing, a number of hardware and software combinations come into play to bring forth scalable transformation.

Autonomous systems

They gather data from the surrounding environment through sensors (e.g. light sensor, audio sensor, cameras, infrared, radar, ultrasound, etc.) to then analyze real-time events, and respond to it without any human intervention. Some of the active autonomous systems in the manufacturing domain include:

• Robots
• Autonomous warehouse
• Autonomous vehicles
• Drones

Robotics

Manufacturing robots are built for automating repetitive tasks, lowering the scope of error, and freeing up human workers’ efforts so that they can focus on productive tasks. AI-powered robots can even train themselves continuously to improve their performance in line with the business requirement. These robots are either developed to be completely autonomous or automate tasks which need human intervention as well. The latter robot type is known as collaborative robots (cobots) in the industry.

IIoT

Industrial Internet of Things is a category of Internet of Things, which works around finding applications in the industrial domain. The technology is revolutionizing the manufacturing space by helping businesses monitor their production process in real-time while helping them make data-driven decisions through manufacturing analytics. At the back of this wide usage scope, McKinsey predicts that IIoT will become a $500 billion market by 2025. Some of the notable advantages of IIoT technologies include:

• Predictive maintenance
• Energy efficiency in individual machines
• Demand forecasting
• Supply chain transparency

3D Printing

Also known as additive manufacturing, it helps companies produce complex objects at a much cheaper and faster rate. Although the traditional manufacturing process is cost-effective for mass production, 3D printing is deemed ideal for products which are not to be built in large volumes. Moreover, it offers a cost-friendly way to create customized products for a wide range of materials including metal.

Augmented and Virtual Reality

The global augmented and virtual reality in manufacturing market size was estimated at USD 8.2 billion in 2022 and is expected to reach around $74.1 billion by 2032, growing at a CAGR of 24.62% between 2023 to 2032. Some use cases of AR/VR in the manufacturing domain include:

• Fast prototyping
• Inventory management
• Machinery maintenance

RPA and Intelligent Automation

Robotic process automation and intelligent automation adoption in the manufacturing space can lower the need for human involvement in rule-based and repetitive tasks to ultimately lower process-related issues. The areas which directly benefit from RPA include:

• Supply chain
• Invoice processing
• Inventory handling
• Manufacturing data management
• Order fulfillment process

Digital Twins

Digital twin in manufacturing is an exact replica (digital) of physical elements like machines, systems, or end products, built to enable businesses in making model-based decisions. The technology has wide ranged applications in the manufacturing domain, including:

• Product development
• Design customization
• Predictive maintenance
• Logistics optimization

Manufacturing Analytics

The analytics tool offers deep-level information around machines, processes, and workers to help predict machines’ future use and servicing requirements, safeguard failures, predict business and inventory needs, and find scope of improvement. Businesses have also been using big data analytics in manufacturing to optimize:

• Demand prediction
• Inventory management
• Order management
• Maintenance
• Risk management
• Automation and robotics
• Transportation optimization
• Product progress tracking
• End user experience monitoring
• Price optimization

At the back of a complete understanding of the best participants for digital transformation manufacturing 4.0 and the technologies that would make it possible, several manufacturing houses have already started implementing and reaping the innumerable value of digital transformation for manufacturing companies.

Real-world Examples of Digital Transformation In Manufacturing Industry

Digital transformation has been facilitating a number of manufacturing houses in getting a competitive advantage in their niches. A successful implementation of a manufacturing digitalization toolset doesn’t just promise better front-back office efficiency but also bring forth overall operational effectiveness and better customer experience.

Here are some of the use cases of digital transformation in manufacturing that shows how companies overcome their challenges to improve efficiency and customer satisfaction.

BAE Systems, the popular UK defense contractor, was finding it difficult to assemble complicated batteries in its manufacturing unit. The company then moved to AR technology in order to better the assembly operations speed while keeping accuracy intact. This digitalization implementation led to the workers being able to easily assemble complex battery products with minimal assembly errors.

ThyssenKrupp Materials Services, one of the biggest material distributors in Germany wanted to use the data insights it was generating to better its operations like optimizing transportation costs, improving service levels, and more. To achieve this, the company introduced custom software, ‘Alfred’, which was built as a self-learning data analytics solution used for giving recommendations on stock levels, maintenance models, and optimized transport routes that would lower the shipping cost and time. This implementation helped the group in improving their operational efficiency through network setup simulation.

Samuel Hubbard, the famous shoe manufacturer based out of California faced challenges with the automation of its everyday operations – the lack of which was causing a delay in the lead generation cycle. After introducing digital transformation software in their front office, the brand could better understand their customer journey, thus offering better customer support. Result? The company increased its sales to around $32,000 B2B orders per month.

Titan Engineering and Automation Limited (TEAL), the popular assembly automation company in India, which provides state of the art turnkey assembly and testing services implemented digital transformation in its design operations. Through this, they could bring a huge improvement – both in speed and quality – in the design solutions delivery to their customers. Additionally, the toolset they used helped achieve efficient operations and consistency in the entire manufacturing process.

Amidst these use cases, the industry is also seeing some top digital transformation trends in manufacturing shaping up; trends that are supporting the digital manufacturing market reach $ 876.10 billion by the time we enter 2029.

Top Digital Transformation Trends in Manufacturing

Digital transformation for manufacturing has become imperative for the future of the industry on both micro ground level and in the macro geopolitical space. Understanding what is trending in the space can help manufacturers deliver value to not just their customers but stakeholders as well through a more streamlined process.

Intelligent Automation

The trend surprised the manufacturing sector with its market size reaching $13.2 billion in 2022, and now it is anticipated to attain a 14.6% CAGR during the ten-year 2023-2030 period.

Through the technology, businesses aim to leverage software and hardware machines’ capabilities to perform complicated tasks without any human involvement – thus minimizing errors and improving efficiency.

Artificial Intelligence

Manufacturing is increasingly getting driven by the Smart Factory 5.0 concept, implying humans are working alongside artificial intelligence systems to better key processes. Just two years ago, in 2022, the global AI manufacturing market size stood at $3.8 billion; and just ten years later, the technology is estimated to touch the $68.36 billion mark, which is almost equal to a CAGR of 33.5% in the forecast 2023-2032 period.

Industrial IoT

The global IoT in manufacturing market size was valued at $ 202 billion in 2022 and is expected to witness a CAGR of 24.70% from 2023 to 2032, reaching $1829.21 billion by 2032. Deeply powered by the technology, manufacturing houses are achieving new possibilities via hyperconnectivity, i.e., networkability of everything.

The key aim of this deep-level hyperconnectivity is to remove any communication gap between stakeholders, machines, and processes. By bringing all the data sources and disparate systems closer and coordinated, manufacturers are able to get real-time visibility into the complete floor and make informed decisions around supply chain management, production, maintenance, and other critical processes.

Digital Twins

The next popular trend which can be efficiently implemented in manufacturing for driving value is digital twins. This technology replicates the complete factory, comprising raw materials, equipment, products, and systems. With extremely realistic virtual replicas, manufacturers can easily draw out the dynamics of how a process would function in the real world to ultimately find and address potential roadblocks.

According to the reports, the digital twin market was valued at $10.25 billion in 2022 and is expected to reach $269.1 billion by 2032, witnessing a CAGR of 38.7% during the forecast period 2023 to 2032.

Microfactories

Another famous trend in manufacturing digitalization is microfactories. They can be understood as a hyper-automated, high-tech manufacturing office which makes use of downsized equipment and small spaces to create high-mix low-volume products. These products are usually highly complex items which are issued in smaller quantities for specific sectors like life sciences, office automation, or medtech. To achieve this, microfactories utilize following advanced technologies:

• Robotics
• Automation
• IoT and AI

Additive Manufacturing

In essence, additive manufacturing means development of three-dimensional objects through the addition of material layer by layer only when it is needed. This approach promises material efficiency and leads to less waste compared to the traditional subtractive approaches. The use cases of the top manufacturing trend include:

• Prototyping
• Expedited tooling and end-use parts production
• 3D printing

Up until this point, we have looked into multiple facets of digital transformation in the manufacturing industry. Translating this information into true value, however, would require a careful implementation of manufacturing digital transformation.

How to Implement Digitalization in Manufacturing?

Digitalization in manufacturing is not a trend anymore; it has become a necessity for staying competitive in today’s fast-changing market. Embracing digital transformation is getting directly linked to enhanced operational efficiency, reduced costs, and improved product quality.

However, the journey requires careful planning and execution.
The below-mentioned steps outline the primary actions to efficiently implement digitalization in your manufacturing operations. By following these, you can guarantee a smooth transition and avail the benefits of a more connected and intelligent manufacturing ecosystem.

Evaluate the present digitalization in manufacturing setup

Start with a thorough assessment of your current digitalization infrastructure. What technologies are you using currently, and how are they effectively serving your business goals? Getting answers to these and other questions would call for a deep dive into the current systems, software utilization, and data handling practices. This stage is all about getting a deep understanding of your digitalization’s starting point.

Set up clear digital transformation goals

What is your vision with digital transformation manufacturing 4.0? Irrespective of whether it is bettering customer engagement, enhancing operational efficiency, or introducing innovation, setting clear, quantifiable objectives is critical. The objectives that you select here must build upon your overall business strategy, ensuring that the digital transformation efforts expedite its achievement.

Build a strategic roadmap

With your business objectives clearly defined, it’s now time to create a strategic plan to become an example of digital transformation in manufacturing done right. This roadmap must have necessary details of how you can achieve digital transformation goals, comprising timeline, key milestones, and a proactive identification of technological and approach combinations. At this stage, it is all about creating a path which is both future-oriented and achievable.

Get organization-wide commitment

Digital transformation goes much beyond the IT department walls. Because it impacts the entire organization, it calls for company-wide engagement as well. It is important to make sure that the transformation’s importance has been communicated to the entire organization.

Securing a buy-in from all the stakeholders will ultimately ease implementation and foster a cohesive environment. Achieving this would involve open communication, addressing apprehensions, and involving all the stakeholders in the planning phase.

Choose the best technology combination

In a world where new technology is introduced every day, selecting the best technologies is pivotal to the digitalization success. This choice must be taken on the basis of both your digital goals and business requirements. Irrespective of the technology you choose – Cloud computing, Computer Vision, Digital Twins, AI, IoT, or other solutions, it must align directly with the end objectives and seamlessly merge with the current systems.

Module-wise implementation

It is important to execute digital transformation in manufacturing efforts in several manageable stages. This phase-wise approach would minimize disruption and allow for necessary changes, without impacting the operational cycle. We also recommend starting with pilot projects or key departments before introducing changes across the complete organization. This method would also aid in efficiently handling budgets and resources.

Prioritize data and analytics

Data is the base of digital transformation. Implement a robust system for efficient data gathering and storage, management, and smart analytics. Utilizing data analytics software at this stage will help get critical insights into your customer behaviors, operational efficiencies ultimately  supporting informed decision-making.

Aid employee training and support

Prepare your team for the digitalization shift. When you roll-out a digital-first system, invest in training and development to get employee buy-in and build their digital capabilities. This step is completely about empowering employees to get used to new tech stack and processes, ensuring they have all the necessary support during the transition phase.

Continuously monitor the outcome and prepare to change

Digital transformation in industrial manufacturing is a continued process. Make monitoring progress against the pre-planned objectives a constant task. Once you have created a system for that, create an environment where you are able to track outcome and make proactive changes on the basis of feedback and performance signs. This continued assessment would help you adjust your strategy and technologies, ensuring that you are able to yield all the desired results.

Digital Transformation Challenges and Solutions in Manufacturing

As manufacturers embrace digital transformation, they face several challenges that can impede progress. Addressing these challenges is crucial to fully realizing the benefits of digital innovation in the industry.

Data Management

Challenge: Managing and aligning vast amounts of data from various sources can be overwhelming. It can lead to data silos and inconsistencies that hinder decision-making and operational efficiency.

Solution: Implement a centralized data management system that ensures data consistency and accessibility across all departments.

Finding a Trusted Tech Partner

Challenge: Choosing the right technology partner for digital transformation is critical, but the abundance of options can make it difficult to find an ideal partner who can truly understand your industry’s unique needs.

Solution: Conduct thorough research to find a technology partner who has proven expertise in delivering successful solutions tailored for the manufacturing sector.

Employee Resistance

Challenge: Implementing digital transformation initiatives often faces resistance from employees who are accustomed to traditional processes and are not open to change.

Solution: Invest in ongoing training to upskill your workforce and promote a culture of adaptability, ensuring your employees are equipped to handle new technologies and processes.

Appinventiv: A Critical Piece of the Manufacturing Digital Transformation Puzzle

As a manufacturing IT services provider, whenever we work with manufacturing houses, we see the term “digital transformation” being spoken as if it’s a one-size-fits-all approach. In reality, it is far from a simplistic definition. We know that digital transformation is an extremely delicate approach that greatly affects businesses, based on their unique requirements, scale, and goals. There is no one approach, technology, or product that can bring complete digital transformation.

We help you choose and implement the best technologies and approach combinations that align with your specific goal. Our team studies your needs and chart out your journey to make technology decisions that focus on seamless integration with your current systems.

This ‘you-focused’ approach that we follow has been critical to our developmental efforts through which we have helped a range of manufacturing houses, right from a construction business looking to improve supply chain visibility, to a hospital chain looking to streamline its vendor partnerships.

FAQs

Q. What is digital transformation in manufacturing?
A. Digital Transformation in manufacturing involves integrating advanced digital technologies, such as IoT, AI, and big data analytics, into production processes. This integration of cutting-edge technologies enables real-time data analysis, automates administrative processes, predicts equipment failure, improves decision-making, enhances operational efficiency, boosts product quality, drives innovation, and does a lot more.

Q. What are the benefits of digital transformation for manufacturing companies?

A. The digital transformation of manufacturing leads to significant benefits such as improved efficiency and reduced operational downtime. By integrating technologies like IoT and AI, manufacturers can anticipate maintenance needs and optimize production processes, thereby reducing costs and enhancing product quality.

Q. How can a manufacturing company start its digital transformation journey?

A. To begin the digital transformation for manufacturing companies, it’s essential to evaluate current technologies and processes to identify improvement opportunities. The next step is to prioritize and implement digital solutions that align with strategic business goals, like automation and data analytics. Engaging all stakeholders and providing training is crucial for a successful transition.

Q. What is the typical cost of digital transformation in manufacturing?

A. The cost of digital transformation in manufacturing varies based on project scope and company size. While initial expenses can be high, they are generally offset by long-term savings from increased productivity and efficiency. Effective cost management is key, requiring a well-defined strategy and phased implementation to keep expenses under control.

THE AUTHOR

Saurabh Singh

CEO & Director