Digital transformation in manufacturing, often referred to as Manufacturing 4.0 or DX, marks a significant shift in the industry's landscape. According to Forrester Consulting, 90% of leaders identify digital transformation as essential for their success going forward, however 75% of manufacturers believe their competitors are ahead of them in terms of implementing this technology. Digital manufacturing, which is a key part of digital transformation, integrates digital technologies with traditional manufacturing processes like artificial intelligence (AI), Industrial IoT (IIoT), and automation. Investments in digital manufacturing have been shown to:
Increase production output by 10%
Boost factory capacity use by 11%
Improve labor productivity by 12%
Let’s take a deeper look at the components, types, and benefits of digital manufacturing to help you develop a strategy for transforming your operations and ultimately stay competitive.
Process transformation, enabled by digitalization, integrates advanced technologies to strengthen operations across the entire workflow, from material handling to shipping finished goods. For instance, automation technologies, such as autonomous mobile robots (AMRs), continuously optimize processes by automating repetitive and potentially dangerous tasks, like transporting hazardous material to assembly lines, reducing human error and improving safety in a facility.
Cloud computing also plays a pivotal role in digital transformation by providing scalable and flexible solutions for data storage, management, and analysis. Cloud-based software can be seamlessly integrated with Industrial IoT technology, enabling leaders to gain real-time access and insights into production performance.
For instance, Cyngn Insight, our autonomous fleet management system, leverages cloud-based communication to give manufacturers valuable insight into their vehicle’s performance, such as location, battery life, and cycle time.
Industrial robots, ranging from autonomous mobile robots to robotic arms, are revolutionizing manufacturing by automating repetitive and labor-intensive tasks, such as transporting bulk material and assembling vehicles, with greater precision and reliability. These robots, which include Cyngn's industrial AV fleet, can operate autonomously and collaboratively with human workers, enhancing productivity and safety on the factory floor while also reducing additional labor costs.
One notable example of AMRs in manufacturing is at one of Siemens' manufacturing plants. By implementing automated mobile robots into its daily operations, the company was not only able to enhance productivity, but was also able to automate 75% of its supply chain.
Lastly, cultural transformation is essential for successful digital transformation, as it fosters a mindset of continuous improvement, adaptability, and collaboration across all levels of the organization. Leaders should use tactics that encourage cross-functional collaboration, inclusive decision making, and open communication channels. This ensures employees are empowered to embrace new technologies and collaboration across departments to break down silos.
In fact, a recent study conducted by Salesforce found that:
90% of workers felt that automation boosted productivity.
85% of workers felt that automation facilitates better cross-team collaboration.
90% of workers trust automation to improve accuracy and promote better decision-making.
Digital transformation in the product life cycle integrates digital technologies at every stage, from design and development to end-of-life management. Companies implementing digital tools in their product life cycles can better visualize and make decisions faster based on insight gathered from prototyping and predictive analytics.
Stage 1 - Design and Development: Use computer-aided design (CAD) and digital twins to create and test virtual prototypes, reducing time-to-market and minimizing costly errors.
Stage 2 - Production: Implement additive manufacturing, robotics, and data analytics to enable predictive maintenance which prevents instances of unplanned downtime.
Stage 3 - Distribution: Employ RFID tracking and predictive analytics to optimize logistics and ensure timely delivery and inventory management.
Stage 4 - End-of-Life Management: Leverage digital tools like automated disassembly lines and sorting machines to efficiently dispose of and sort materials in a sustainable way.
The smart factory represents a significant leap in digital transformation for manufacturing, leveraging automation, robotics, and big data to create highly automated and interconnected environments. Smart factories leverage the digital technologies outlined to optimize traditional manufacturing processes from material handling to sending out finished goods.
For instance, Bosch, a leader in developing technology for multiple business sectors, created a smart factory that uses digital twins to simulate manufacturing processes and robotics for material handling tasks. With over 60,000 equipment sensors integrated throughout the facility, Bosch has achieved a 25% boost in productivity. Furthermore, its automation platform has effectively reduced component and engineering costs by 30-50%.
Digital transformation in value chain management focuses on optimizing the entire manufacturing process, from raw material sourcing to distribution and customer service. Value chain management software leverages AI and enterprise resource planning (ERP) systems to enable real-time tracking of inventory levels, procurement, and logistics, facilitating smoother operations and minimizing waste.
For example, companies like Caterpillar use predictive analytics as a form of value chain management to predict when equipment might fail, schedule maintenance ahead of time and optimize production schedules. Closer collaboration with suppliers and partners across the entire value chain enables manufacturers to share data and gain supply chain visibility, driving proactive decision-making for changing market conditions.
It’s been shown that companies can reduce operational costs up to 90% by implementing automation alone, which is just one component of digital transformation. Investing in digital transformation offers significant cost savings by automating internal processes and reducing labor expenses. Plus, digital transformation prevents unplanned equipment downtime, which can cost organizations upwards of $50 billion per year.
Additionally, the adoption of Manufacturing-as-a-Service (MaaS) models has become a common approach in manufacturing. Traditionally, digital transformation in manufacturing included large up-front fees for upgrading equipment, infrastructure, etc. However, this model allows manufacturers to optimize resource allocation and production scalability and overcome these barriers to adoption.
Consider a production line that’s constantly under maintenance. Through digital transformation, organizations can employ real-time monitoring, data analytics, and automation to prevent unplanned downtime and optimize production in this given production line.
In fact, a study by McKinsey found that manufacturers who invest in digital transformation saw on average a 30-50% reduction in equipment downtime and a 15-30% increase in labor productivity.
Large companies like Toyota and General Electric (GE) employ both IoT sensors and AI to enable real-time data on equipment performance and to monitor production processes across multiple facilities. These advancements enable leaders to improve production speeds, minimize downtime, and boost worker productivity.
In 2019, the manufacturing industry reported 846,000 non-fatal workplace injuries, which equates to 6.6 injuries per 100 workers. However, digital transformation technologies have been shown to significantly reduce workplace injuries by an impressive 72% by minimizing the need for workers to engage in hazardous tasks like stacking pallets or transporting heavy material.
For example, advanced technologies like automation platforms and data analytics allow companies to monitor and identify potential hazards before they occur. This not only improves safety, but also creates happier workers who are freed up to focus on higher-value tasks in safer environments. Plus, happier workers tend to not only stay longer, but also be more productive.
Digital technologies promote sustainability in manufacturing by optimizing resource use and minimizing environmental impact. Manufacturers can boost cost savings and support environmental regulations by adopting automated solutions such as energy-efficient robotic systems and convey belts.
For instance, automated sorting systems use robotic arms to swiftly transport materials and use a combination of cameras, sensors, and machine learning algorithms to identify recyclable and non-recyclable material.
In addition, studies have shown that there is a strong consumer preference for businesses to prioritize sustainability in their operations, where —
78% of consumers believe sustainability is important.
55% are willing to pay more for eco-friendly products.
84% claim that poor environmental practices will alienate them from a brand.
In addition to customer satisfaction through sustainability, digital technologies also allow manufacturers to exceed customer satisfaction by improving product quality, customization, and delivery speed. In fact, real-time data analytics enable manufacturers to gain insights into customer preferences and market trends, enabling them to tailor products and meet diverse customer preferences effectively.
For example, Amazon has set high standards for order fulfillment expectations. To meet this demand, the company deploys hundreds of thousands of automated mobile robots to ensure rapid delivery and maintain its fast delivery guarantees. This results in reduced lead times and expedited delivery, which boosts their customer satisfaction.
28% of manufacturers indicated in a survey conducted by L2L that they don’t have a digital manufacturing strategy, with 38% believing this lack of strategy is a huge barrier to implementing new technologies. Luckily, creating a digital transformation roadmap and following these steps can help to overcome these challenges and to successfully implement new technology in your facility.
Step 1 - Outline Business Objectives: Outline clear objectives, such as increasing production speed and reducing delivery times, along with the steps that will be required to achieve this digital maturity effectively. This includes assessing current capabilities, identifying areas for improvement, and aligning with your business goals.
Step 2 - Prioritize Initiatives: You should prioritize initiatives based on their potential impact on productivity, product quality, and customer satisfaction. One way of doing this is assessing overall equipment effectiveness (OEE). By assessing these KPIs, your organization can better identify process inefficiencies and areas for optimization throughout your entire facility.
Step 3 - Define Timelines: Finally, the roadmap should define key milestones, timelines, and resources needed to guide the phased implementation of digital solutions across your manufacturing operations. You should determine a resource budget and set dates for equipment setup and technology integration to ensure that your digital transformation journey is well-planned, measurable, and aligned with your business objectives.
Learn more: how to calculate your OEE score
To overcome technology debt, manufacturers must prioritize modernizing legacy systems and processes while ensuring they are compatible with new digital solutions. Not only do legacy systems rank as the third highest barrier to implementing digital manufacturing technology, but they can pose significant challenges to interoperability and security vulnerabilities.
Additionally, organizations must allocate resources to address technology debt while minimizing disruptions to ongoing operations. This also requires proactive management of technical debt, which includes continuous evaluation, updating, and scaling of digital infrastructure to support long-term growth and innovation in manufacturing.
The convergence of information technology (IT) and operational technology (OT), known as IT/OT integration, bridges the gap between production systems and enterprise applications, facilitating seamless data flow and real-time decision-making. By aligning OT and IT, manufacturers can improve process control and drive innovation throughout their facility.
Next, your organization should start by identifying repetitive tasks and bottlenecks, such as material transport, that can benefit from automation technologies. Once these tasks are identified, it requires training employees to work alongside these automated systems to maximize the benefits, as well as continuously monitoring performance and optimizing processes. In fact, studies have estimated that automation can free up 30-50% of a skilled worker’s time.
For instance, at Cyngn, our DriveMod vehicles can be deployed within just a few days and our team can train employees on safe operation within just a few hours. As a result, “DriveMod turns every shift into a productivity powerhouse,” said Cyngn’s VP of Engineering, Sean Stetson.
The ability to scale digital manufacturing solutions across operations is essential as an organization’s needs grow and change over time. However, this can be challenging due to the need to address existing technological debt.
To overcome these challenges, organizations should develop a comprehensive scaling plan that includes standardizing processes, integrating new solutions with legacy systems, and training staff to ensure smooth adoption. Scalable technologies and fostering a culture of innovation also helps ensure successful scaling and sustained growth.
Beyond the challenges already mentioned, organizations face similar challenges in the digital transformation journey including resistance to change from workers, data silos, and skill gaps. To overcome these obstacles, leaders must address resistance to change through effective communication and training, promote an open-minded environment, and continuously evaluate and adjust strategies. These strategic approaches will ensure smoother transitions and ultimately maximize the benefits of an organization's digital initiatives.
One way to leverage digital transformation in your own manufacturing facility is by incorporating Cyngn’s fleet of self-driving AMRs into your facility. Our AMRs, which include our autonomous tugger, autonomous forklift, and autonomous stockchaser, can automate repetitive hauling tasks without requiring special infrastructure, allowing manufacturers to reap the many benefits of digital transformation. For instance, our autonomous tugger has been shown to increase productivity by 34% and reduce human labor costs by 64%.
With our DriveMod technology, your industrial worker vehicles can:
Autonomously lift and haul thousands of pounds of goods
Remotely manage vehicles via the FMS or on-vehicle display
Collect real-time data to reveal opportunity for optimization
Leverage multiple, redundant, and intelligent layers of safety
Execute missions based on a variety of flexible, programmable options
Switch into manual mode and be driven by a human