The COVID-19 pandemic introduced many challenges to the manufacturing industry. First, there was an unprecedented rise in consumer demand. Then, there were disruptions in many areas of the  supply chain, including procurement, transportation/logistics, warehousing, and order fulfillment. Although the pandemic has mostly come to an end, these challenges are still present today. 

Manufacturers have found ways to overcome these challenges, largely by prioritizing supply chain planning and integrating Industry 4.0 technologies into their processes. Industry 4.0 is constantly evolving—while some manufacturers may be hesitant to implement these technologies, others have begun to see their value. 

In this article, we’ll explore the five major ways Industry 4.0 has improved the overall supply chain planning process. 

1. Real-Time Tracking & Data Transparency

First, supply chain planning managers today are using the connectivity of the Internet of Things (IoT) to leverage real-time tracking. 

Real-time tracking is the ability to accurately follow the location of an item as it moves through the supply chain process. As the product is moved from location to location, an IoT-enabled tracker sends data to a server, which can be checked as frequently as needed. The tracking can also be timed against predetermined goals of days, hours, or minutes. This data transparency helps consumers stay informed of transportation issues and potential delays. 

This is important because operational integrity has become more scrutinized by the consumer over the last decade. With real-time tracking, there aren’t any gray areas where the business can shift liability to other parts of the system while the item is waiting to be moved in the process. And, the customer can no longer blame the company for not meeting expectations because the customer was given an accurate expectation of when the item would be delivered.

The overall benefits of implementing real-time tracking include:

• Increased Efficiency
• Continuous Data Protection
• Improved Process Performance
• Reduction of Product Loss
• Improved Customer Satisfaction
• Increased Data Transparency  

2. RFID & Warehousing

 

RFID (radio frequency identification) is quickly becoming the tool of choice when trying to improve the organization and management of inventory. The RFID technology which relies on radio-frequency to transfer data is being used in tags or chips that can be placed on items as they arrive in shipment. As the items move through the different processes, the tag’s internal memory is updated and can be uploaded for use in the warehouse management system via electromagnetic signals. Once the data is uploaded, it can then be analyzed to better help understand the flow of products, keeping inventory levels stocked and tracking what goes in and out of the building. With many companies focused on running lean, tracking these elements can be crucial to being profitable.

The RFID tags have a number of features that make them ideal for solving inventory tracking challenges over other traditional tools such as barcoding: 

• No line of sight needed – RFID tags can be read from a distance and avoids each tag having to be scanned manually like older barcode technologies. The tags can even be read when behind other products which makes it possible to gather data from entire pallets of items at one time. 
• Accuracy – The data from the tags are uploaded automatically eliminating the possibility of human error.
• Increased Amounts of Data – Barcodes are basically identifiers, but RFID tags can hold large amounts and a wide variety of information in the internal memory until it is uploaded.
• Efficiency – Tracking products in real-time can allow for re-configuring inventory to allow for the most optimum flow of items through the warehouse. 

3. Data Sharing & Collaboration

 

In addition to increasing data transparency, Industry 4.0 technologies are also improving data sharing and collaboration. 

As businesses are forced to become more competitive, they rely more and more on information technologies, such as IoT, artificial intelligence, and cloud services to increase connectivity with supply chain partners. For example, when manufacturing issues arise, data can be autonomously updated into a system which can then be shared with stakeholders, shipping companies, and even consumers. 

Although this increase in communication has many benefits, including improved operational and strategic decision making, increased productivity, improved utilization of resources, and better flexibility and adaptability, possibly one of the most important improvements comes down to customer service. 

If there are questions from customers, support staff can easily look at real-time data to help resolve the problems quickly in ways that were not possible a decade ago. By automatically keeping the customer informed of delays and managing expectations, manufacturers can reduce the amount of resources needed to improve the overall customer experience. 

4. Reducing Equipment Downtime

Transportation and logistics issues aren’t the only cause of supply chain issues—equipment downtime during the manufacturing process can also create disruptions. That’s why more and more manufacturers are implementing predictive maintenance strategies into their supply chain planning processes. 

Although predictive maintenance isn’t a brand-new technology, it has certainly evolved since its inception in the 1990s. Predictive maintenance refers to the practice of using data analysis tools and software to better determine when equipment or parts might fail. The goal is to replace or repair components prior to the predicted failure, rather than reacting to the failure afterwards. This maximizes the lifecycle of the machines without prematurely replacing components. It also prevents unnecessary downtime due to catastrophic failures.

And, by installing condition-monitoring sensors on equipment, managers are able to monitor the health of the equipment in real-time, as well as continuously adjust predictive maintenance plans to improve failure predictions. 

5. Increasing Process Efficiency & Accuracy

Lastly, supply chain automation relies on intelligent, digital technologies to increase process efficiency and accuracy. As consumer demand increases for manufacturers, so does the implementation of automation tools like robots, artificial intelligence, and machine learning, which help increase the accuracy and speed of repetitive tasks.

Industrial robots and cobots can work continuously to accurately handle repetitive assembly and material handling applications. Allocating repetitive tasks to robots allows manufacturers to reassign skilled human workers to more valuable tasks. The accuracy of the robots also reduces rework or mistakes during these processes.

Additionally, AI and machine learning can process enormous amounts of data instantly, giving manufacturers a huge advantage when it comes to compiling data, organizing information, reporting trends, and controlling in-house or outside processes. Low-code automation platforms allow for complete process visibility where real-time information is loaded to a central database and machine learning is used to automatically improve the performance of tasks based on experience.

Improve Supply Chain Planning WIth Help From DSI

While Industry 4.0 technologies offer value to manufacturers, many are hesitant to implement because these technologies can be difficult to understand and challenging to integrate them into the workplace. 

However, manufacturers who aren’t taking advantage of Industry 4.0 will lose out to their competitors who are. The future of manufacturing is in the digital enterprise, and it’s how manufacturers will stay relevant and competitive in the increasingly complex and demanding global market of tomorrow. 

If you have questions about Industry 4.0 or need better supply chain planning solutions, turn to DSI. We’re a world-class engineering and consulting firm in North America. Some of our specialties include layout optimization, material flow, network design and optimization, integrated logistics operations design, and warehousing/distribution. No matter what industry you’re in, our team can help you find solutions to your supply chain challenges. 

Fill out our online form today to schedule a free consultation with one of our experts.

As our world continues to push forward with technological innovation and increasing productivity, manufacturers are streamlining their production facilities and operations by embracing Industry 4.0.

Industry 4.0, in a simple sense, describes integrating technologies, such as cloud computing, analytics, the Internet of Things (IoT), machine learning, and artificial intelligence (AI) into production facilities, assembly lines, and distribution centers. As these technologies advance, their impact on manufacturing and distribution will continue to revolutionize the industry and bring a significant jump in both optimization and production capacity.

In this article, we’ll explore the latest developments with Industry 4.0 in manufacturing and dive deeper into how they improve their efficiency and throughput.

1. Increase in Industry 4.0 Technology Usage to Reduce Supply Chain Issues

With Industry 4.0 technology, companies are taking a closer look at how they can make their supply chains more resilient.

This includes implementing improved data management and data capture systems, integrated process optimization, and enhancing physical process execution through a combination of humans and machines.

Data Capture & Management

Data capture and data management can become a significant bottleneck in a supply chain if not appropriately managed. That’s why companies have begun to improve their data update frequency, data storage and capture systems, and how quickly information is sent out.

With improved data collection and management systems, organizations are able to spot supply disruptions and bottlenecks before they have a chance to spiral out of control, as well as spot subtle trends, including slowly increasing supplier lead times to get ahead of the problem.

Integrated Process Optimization

Process optimization was typically done in silos and not standardized in a way that ensured consistency and the best possible results. With integrated process optimization, companies have begun developing workflows and standards for process optimization to foster transparency and reduce potential errors or pitfalls.

2. Smart Factories

In 2020, there was an increase in manufacturers looking into digital twinning, and this implementation of digital twins is expected to continually increase for years to come.

 A digital twin is essentially a virtual representation of a specific object or system, and is designed to replicate its real-world counterpart. Digital twinning has allowed manufacturers to create what are called “smart factories,” or “digital twin factories,” which are digital replicas of their physical plants and factories. Smart factories help process efficiencies by opening up more collaborative opportunities. 

For example, if one company has multiple locations around the world, it’s hard for all of the employees within that company to meet together to safely collaborate on new product developments and processes. But, with smart factories, technicians and engineers around the world can meet together in this digital space to work on these new processes and products. Although time zones are still a challenge to contend with, there’s no doubt that smart factories are changing the manufacturing industry.

3. 5G, Sensor Advancements, & Predictive Maintenance

Predictive maintenance isn’t a new development in manufacturing, but 5G does expand predictive maintenance capabilities.

Predictive maintenance refers to the process of using condition-monitoring data, machine learning, analytical models, and other technologies to predict issues and eliminate the need for preventative maintenance. 

5G technology and advances in sensors have allowed for significant improvements in the field of predictive maintenance. The amount of bandwidth required to operate vast arrays of sensors in an autonomous environment wasn’t possible before the advent of 5G technology. With 5G, it’s now possible for manufacturers to pull a high volume of data from multiple sensors, which in turn helps to significantly reduce production costs and improve the lifespan of equipment and machinery.

4. Edge Computing

Edge computing is defined as data that is stored and processed at the “edge” of a local network, rather than at a data center. The “edge” of a network refers to various endpoints, or edge devices, that are connected to the network core. These devices could include personal computers and WiFi access points. 

The biggest advantage is that data doesn’t have to travel as far, which increases response time and reduces lag, allowing for better analytic speeds, as well as instant data analysis and processing. Edge computing also provides a better security blanket to the network core and is easily scalable for growing businesses.

Edge computing saw a dramatic rise in adoption in 2022, particularly because it allows monitoring systems in factories and plants to quickly and consistently process and collect data. Manufacturing and production plants are using both edge computing and artificial intelligence to improve quality control processes, identify safety issues or product defects, reduce waste, and more. 

Prior to edge computing, many companies were implementing cloud computing. The issue with cloud computing is that the data is sometimes still being processed and stored hundreds, sometimes even thousands of miles away, which can cause latency issues and gaps in data collection. Cloud computing can also increase downtime if the cloud or network becomes unavailable. Edge computing eliminates these issues, which helps manufacturers increase process efficiency and speed.

The number of manufacturers adopting edge computing is only expected to increase in 2023. In fact, technical research and consulting company Gartner, expects the number of companies using edge computing to increase from 10% to 75% by 2025. 

5. AI & Industry 5.0

 

Over the past two years, you may have heard the term “Industry 5.0.” Industry 5.0 isn’t necessarily a new revolution, but rather an evolution of Industry 4.0.

As you already know, the very foundation of Industry 4.0 is increasing process efficiency through machine learning, automation, and other developing smart technologies. Industry 5.0 takes that same idea, but poses the question—how are humans interacting with this technology? 

At its core, Industry 5.0 is centered around humans and AI safely and efficiently co-existing in a workplace. 

Digital twin factories, sensors, the Internet of Things (IoT), and digitally connected manufacturing are the fourth industrial revolution, implementing artificial intelligence (AI) and machine learning into manufacturing is Industry 5.0. When manufacturers started to implement industrial robots, many employees feared that automation itself would take their jobs away. 

Industry 5.0 helps take this fear away by putting the employees back in charge. Industrial robots and cobots will continue to ensure process speed and accuracy, as well as carry out repetitive manual tasks. This leaves human workers with the responsibility of more creative tasks, like finding solutions that will help reduce waste and environmental impact of manufacturing processes.

Want to Learn More About Industry 4.0 Technologies?

Have questions about Industry 4.0 technologies? Turn to DSI. Founded in 1983, we provide world-class engineering, consulting, and program management services, as well as Industry 4.0 solutions, to clients in many industries. With a team of over 300 professionals and engineers, we can help make any project a success.

Contact us today to schedule a free consultation.