Editor’s note: This article on digital manufacturing was syndicated from Cyngn’s blog.
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 traditional production processes with technologies such as artificial intelligence, the industrial Internet of Things (IIoT), and automation.
Researchers have found that investments in digital manufacturing can:
- 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.
Components of digital manufacturing
Process transformation
Process transformation, enabled by digitalization, integrates advanced technologies to strengthen operations across the entire workflow, from material handling to shipping finished goods.
For instance, technologies such as autonomous mobile robots (AMRs) can continuously optimize processes by automating repetitive and potentially dangerous tasks, like transporting hazardous material to assembly lines. They can thus reduce human error and improve safety in a facility.
Cloud software
Cloud computing also plays a pivotal role in digital manufacturing 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, uses cloud-based communication to give manufacturers valuable insight into their vehicle’s performance, such as location, battery life, and cycle time.
Autonomous vehicles and robotics
Industrial robots, ranging from automated guided vehicles (AGVs) and AMRs to robotic arms and forklifts, are revolutionizing manufacturing by automating repetitive and labor-intensive tasks, such as transporting bulk material and assembling vehicles, with greater precision and reliability.
Such systems can operate autonomously and collaboratively with human workers, enhancing productivity and safety on the factory floor while also controlling labor costs.
One notable example of AMRs in manufacturing is at one of Siemens’ factories. By implementing AMRs into its daily operations, the company was not only able to enhance productivity, but it was also able to automate 75% of its supply chain.
Cultural transformation
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 break down silos across departments. 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.
The three types of digital transformation in manufacturing
1. Product life cycle
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: Use digital tools like automated disassembly lines and sorting machines to efficiently dispose of and sort materials in a sustainable way.
2. Smart factory
The smart factory represents a significant leap in digital manufacturing, including automation, robotics, and big data to create highly automated and interconnected environments. Smart factories are designed 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 more than 60,000 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% to 50%.
3. Value chain management
Digital transformation in value chain management focuses on optimizing the entire operation, from raw material sourcing to distribution and customer service. Value chain management software takes advantage of both 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.
Why investing in digital manufacturing makes sense
1. Cost savings
Companies can reportedly reduce operational costs up to 90% by implementing automation alone, which is just one component of digital transformation. Further investments promise 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.
In addition, the adoption of manufacturing-as-a-service (MaaS) models has become a common approach in manufacturing. Previously, digital manufacturing required large upfront fees for upgrading equipment, infrastructure, etc.
However, the MaaS model allows manufacturers to optimize resource allocation and production scalability and overcome these barriers to adoption.
2. Better processes
Consider a production line that’s constantly under maintenance. Organizations can now 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 that invest in digital transformation saw on average a 30% to 50% reduction in equipment downtime and a 15% to 30% increase in labor productivity.
Large companies such as Toyota and General Electric (GE) employ both IoT sensors and AI to obtain real-time data on equipment performance and to monitor processes across multiple facilities. These advancements enable leaders to improve production speeds, minimize downtime, and boost worker productivity.
3. Improved safety
In 2019, the manufacturing industry reported 846,000 non-fatal workplace injuries, which equates to 6.6 injuries per 100 workers. However, digital 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 instance, robotic sensing and data analytics allow companies to monitor and identify potential hazards before they occur. This not only improves safety, but it 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.
4. Sustainability
Digital technologies can promote sustainability in manufacturing by optimizing resource use and minimizing environmental impact. Manufacturers can save money and comply with environmental regulations by adopting energy-efficient robots.
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 manufacturing and warehousing 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
5. Customer satisfaction
Digital manufacturing allows companies 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 mobile robots to ensure rapid delivery. This results in reduced lead times and expedited delivery, which boosts customer satisfaction.
How to build your digital manufacturing strategy
1. Create a roadmap
Twenty-eight percent 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.
- 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.
- Prioritize initiatives: You should prioritize initiatives based on their potential impact on productivity, product quality, and customer satisfaction. One way of doing this is by assessing overall equipment effectiveness (OEE). By assessing these key performance indicators (KPIs), your organization can better identify process inefficiencies and areas for optimization throughout your entire facility.
- 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.
2. Overcome technology debt
To overcome technology debt, manufacturers must prioritize modernizing legacy systems and processes while ensuring they are compatible with new digital systems.
Not only do legacy systems rank as the third highest barrier to implementing digital manufacturing, but they can pose significant challenges to interoperability and security vulnerabilities.
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.
3. Align OT and IT
The convergence of information technology (IT) and operational technology (OT), known as IT/OT integration, bridges the gap between production systems and enterprise applications. This can facilitate data flow and real-time decision-making.
By aligning OT and IT, manufacturers can improve process control and drive innovation throughout their facilities.
4. Implement factory automation
Next, your organization should start by identifying repetitive tasks and bottlenecks, such as material transport, that can benefit from automation. Once these tasks are identified, the company must train employees to work alongside these automated systems to maximize the benefits.
The organization should also continuously monitor performance and optimize processes. In fact, studies have estimated that automation can free up 30% to 50% of a skilled worker’s time.
For instance, Cyngn said its DriveMod vehicles can be deployed within just a few days, and the company‘s team can train employees on safe operation within just a few hours.
As a result, “DriveMod turns every shift into a productivity powerhouse,” claimed Sean Stetson, vice president of engineering at Cyngn.
5. Scale systems for digital manufacturing
The ability to scale automation and software 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 systems with legacy systems, and training staffers to ensure smooth adoption.
Fostering a culture of innovation can also help ensure successful scaling and sustained growth.
6. Overcome challenges in digital transformation
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 should ensure smoother transitions and ultimately maximize the benefits of an organization’s digital initiatives.
Digital transformation with autonomous industrial vehicles
One example of how to transform facility operations for digital manufacturing is with AMRs such as Cyngn’s fleet. It includes an autonomous tugger, an autonomous forklift, and an autonomous stockchaser, can automate repetitive hauling tasks without requiring special infrastructure.
The company said this enables manufacturers to reap the many benefits of digital transformation. For instance, it said its autonomous tugger has been shown to increase productivity by 34% and reduce human labor costs by 64%.
Cyngn said its DriveMod technology allows industrial vehicles to:
- Autonomously lift and haul thousands of pounds of goods
- Remotely manage vehicles via the fleet-management system (FMS) or on-vehicle display
- Collect real-time data to reveal opportunities for optimization
- Include 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
