What is AI in manufacturing?

What are the advantages of AI in manufacturing?

AI has become mainstream in the manufacturing industry due to its significant impact on production processes. Organizations are using intelligent systems to perform tasks that usually require human intelligence, such as learning, problem-solving, and decision-making. For the manufacturing sector, AI is utilized to analyze extensive datasets, optimize production lines and minimize supply chain bottlenecks, predict maintenance needs, and enhance overall operational efficiency.

Enhanced efficiency and productivity: By leveraging AI technologies, manufacturers can automate repetitive tasks, streamline workflows, and optimize resource allocation. This not only reduces manual errors but also allows employees to focus on more strategic and complex tasks, ultimately boosting overall productivity. AI technologies also aid in “on-boarding” new production and maintenance employees who may lack process experience—this includes AIOps for network engineers as well.

Improves quality control: AI-powered systems can analyze vast amounts of data in real-time and provide consistent supply chain analytics. By identifying anomalies and deviations from production standards, and detecting defects early, manufacturers can take immediate corrective actions to reduce waste, ensure worker safety, and improve quality.

Enhanced predictive maintenance: By using AI algorithms and machine learning, manufacturers can monitor equipment health proactively, detect potential failures, and schedule maintenance activities accordingly. This approach helps prevent unexpected breakdowns, reduces downtime, and maximizes operational efficiency.

How is AI transforming the manufacturing industry?

Like many industries, the manufacturing sector is undergoing a significant transformation as AI technologies reshape processes, speed decision-making, and improve quality. Let’s look at how AI is reshaping the industry and driving productivity gains:

• Automation and robotics: AI has taken automation and robotics to new levels with regards to productivity and safety. AI-powered robots can automate routine tasks and perform complex tasks with precision. This reduces errors and enables human workers to focus on strategic or value-added activities.
• Supply chain management: AI algorithms enable manufacturers to optimize supply chain processes with real-time monitoring and access to data production capacity, work in process, and transportation routes. Manufacturers can make data-driven decisions, minimize disruptions, and reduce costs. leading to more efficient and profitable outcomes.
• Demand forecasting and inventory management: AI algorithms predict demand patterns by analyzing historical data, market trends, and customer behavior. This enables manufacturers to optimize production schedules, reduce excess inventory while accurately meeting demands and controlling costs.

What are some common use cases and applications for AI in manufacturing?

AI is revolutionizing various aspects of the production process in the rapidly evolving manufacturing industry. Here are some key applications of AI in manufacturing:

• Intelligent machine vision and inspection: AI-powered machine vision systems enable manufacturers to enhance product quality and streamline the quality inspection process. By analyzing images or videos, AI algorithms can detect defects, measure dimensions, and identify anomalies with incredible accuracy, significantly reducing the need for manual inspection.
• Generative Design: AI accelerates product development while enabling creativity and design innovation. Designers enter parameters like materials size, and weight of the desired product and what methods to use and an ideal price point and the algorithms generate blueprints and instructions that can be used to be placed into production quickly.
• Predictive analytics for equipment maintenance: AI-based predictive analytics helps manufacturers optimize equipment maintenance schedules and minimize downtime. By analyzing data, AI algorithms can identify indicators of potential equipment failures and proactively fix to limit breakdowns.
• Real-time adaptive manufacturing: AI systems allow for adaptive manufacturing processes and raises Advance Process Control (APC) to new levels of capabilities. Access to real-time data analysis provides a more accurate assessment of demand to improve supply chain management, resource availability, and production constraints ensuring efficient operations and maximizing productivity.

What are the challenges of implementing AI in manufacturing?

While there are many benefits to implementing AI in manufacturing, it is not without its own set of challenges. To prevent running into any challenges when adopting AI technologies, conduct a review of your existing environment and develop a plan to address data security, integration, and employee training.

• Data privacy and security: manufacturers generate and analyze massive amounts of data that must be protected against unauthorized access, security threats, or misuse. Robust security measures, data handling processes, and remediation plans are critical to safeguard intellectual property and maintain data privacy.
• Integration challenges: Legacy production plants or facilities rely on technology that predates AI. To limit integration issues, evaluate current infrastructure and identify compatibility issues early. Understand what systems may require software or hardware upgrades, or more data processing power. Embracing standardized protocols will reduce hiccups and ensure a smooth transition between AI systems and existing manufacturing processes.
• Operational risks: Almost half of manufacturers surveyed in a Deloitte survey cited operational risk, including cyberattacks, as the biggest threat to AI-powered smart factory initiatives. Sophisticated attacks can compromise IT and OT teams and bring critical production systems to a halt, disrupting services, decreasing revenue, and impacting the lifetime value of a customer.
• Skills gap: AI technologies require highly skilled and trained professionals who can develop, deploy, and maintain AI systems in manufacturing environments. To build a sustainable program companies need to invest in upskilling their workforce and possibly hiring new talent to bridge any gaps while employees learn to utilize AI effectively.

How will AI shape the future of manufacturing?

The manufacturing industry is undergoing a massive shift, including the use of collaborative robots, or cobots. Cobots, equipped with advanced AI algorithms, are autonomous robots that are expected to work directly alongside humans to streamline processes and increase productivity by automating manual tasks. Cobots can perform repetitive tasks with greater speed and accuracy, making them essential for day-to-day operations of manufacturers all over the world. Cobots don’t require protective gear and can work on the plant floor, making it cheaper and safer with improved quality control.

Another shift is the use of edge computing. AI capabilities can now be deployed closer to the devices and sensors at the edge of the network, versus being centralized in the cloud. This move enables real-time decision-making and reduces latency for time-sensitive manufacturing operations.

The use of AI-powered digital twins will simulate and optimize manufacturing processes. A digital twin is a virtual replica of an object or system, such as a machine or an entire production line. Businesses will be able to identify inefficiencies, predict maintenance requirements, and streamline operation with proactive decision-making.

How does Cisco enable AI in manufacturing?

As an industry leader in networking and technology solutions, Cisco recognizes the significance of AI in manufacturing and is committed to helping manufacturers achieve operational excellence. Our innovative portfolio of products and solutions, such as the Cisco Industrial IoT platform (Architectures, Fit for Use Products, Design Build and Implement Services, plus a complete portfolio of consulting and system integration partners) provides businesses with the tools they need to leverage AI and drive digital transformation in their manufacturing operations.

Through AI-powered analytics and automation, Cisco’s application-centric infrastructure can dynamically adapt to application behavior, predict potential performance bottlenecks, and automatically adjust resources to meet demand. This intelligent approach to application management helps manufacturers:

• Connect IT teams to business results via user experience visibility to lower their total cost of ownership
• Monitor application performance and correlate it to application infrastructure to optimize business uptime
• Monitor the performance of traditional, hosted hybrid apps, and microservices-based cloud native applications

With our expertise and cutting-edge technologies, we empower organizations to embrace future trends and innovations in AI for manufacturing, enabling them to stay competitive in an ever-evolving industry, and avoid building the “Brownfield of the Future” with one off point solutions.

Cisco offers a range of AI-powered solutions for the manufacturing industry that will improve product quality, production, and employee safety with intelligent robotics and advanced analytics platforms. By combining AI with industrial networking, Cisco enables manufacturers to collect and analyze real-time data from their production lines and harness these insights for predictive maintenance, quality control, and process optimization. Manufacturers can revolutionize the way they observe, secure, and optimize applications with Splunk Observability.

Cisco also created a strong partnership ecosystem for AI-enabled manufacturing applications. Collaborating with leading technology companies, like Rockwell Automation and Schneider Electric, Cisco ensures that its solutions seamlessly integrate with other AI technologies and applications to enable manufacturers to leverage the power of AI across their entire product development, production, and supply chain management.

Learn more

Check out the solution overview from Cisco Live 2024: A Foundation for AI and ML: Cisco Intelligent Industrial IoT Network. It provides a detailed evolution of AI and ML in network automation, asset visibility, and threat defense for manufacturers.