What Are Some Best AI Applications and Use Cases in Manufacturing?

 Machine learning and artificial intelligence (AI) are transforming the manufacturing industry in some pretty dramatic ways, from increasing efficiencies, increasing defect detection rates, and reducing waste to improving sales forecasts and even giving industry leaders company the insights they need to revamp business models.

Manufacturing can involve some very inefficient processes, which tend to require continual refinement and adjustment. But that is precisely why we are seeing such a dramatic increase in the number of machine learning and artificial intelligence applications in manufacturing.

Some AI Applications and Use Cases in Manufacturing


AI for the Supply Chain


Manufacturers can take advantage of AI-enabled systems to assess different supply chain scenarios to impact time, cost, and revenue. With AI, you can predict optimal routes for delivery, track human performance in real-time, predict delivery times with historical data, and attach weather and traffic reports for better route planning. This is all about delivering the product to the end customers.


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Industrial Automation


Manufacturing workers largely rely on their experience and intuition to monitor many equipment configurations and manually adjust them. It tests their operational efficiency as well as they need to perform tests and perform some troubleshooting activities. This can affect OEE as operators can take shortcuts and focus on things other than economic value.


Manufacturers can improve the efficiency of their teams and reduce labor costs by leveraging AI. Includes:


  • Continuous follow-up and monitoring of operations to quickly identify any anomalies

  • A central repository of operations data to predict optimal equipment settings

  • Automate complex tasks to make scaling on demand easy

  • Manufacturing giant Siemens has partnered with Google to use AI, computer vision, and analytics to improve shop productivity.


AI-based Design


Before designing any product, manufacturers need to test various scenarios and come up with the best possible result. By leveraging AI, generative design software can consider multiple input parameters such as size, weight, manufacturing methodologies, raw materials, and other cost constraints to generate various design combinations.


Recommended To Read: Computer Vision Applications in Manufacturing & Mining


AI and IoT


As the use of sensor-equipped connected devices continues to improve in manufacturing operations, data analytics from these devices can improve productivity and accuracy. With AI and IoT, manufacturers can:


  • Monitor equipment performance, machine temperature and settings, and job site safety

  • Take advantage of HVAC and smart lighting to optimize energy consumption

  • Use advanced analytics with edge devices on the shop floor


Predictive Maintenance


Global management consultancy BCG says that predictive maintenance is essential in Industry 4.0. Additionally, McKinsey says that predictive maintenance provides excellent value to manufacturers. With AI-powered systems, manufacturers can:


  • Avoid unplanned equipment breakdowns by detecting anomalies and inefficiencies.

  • Reduce equipment downtime by predicting maintenance for various spare parts and overall equipment

  • Analyze individual components to reduce overall machinery replacement cost


Process Automation


Manufacturers can streamline their production workflows by leveraging AI-powered process mining tools. Additionally, today's evolving intelligent automation practices can assist in invoice processing, customer service, document management, and other vital business functions.


Recommended To Read: Intellectual Robotic Process Automation- Benefits & Use Cases


Typically, manufacturers operate in different physical locations. You can compare performance across multiple operating facilities to optimize processes and resources.


Quality Control and Inspections


Inspecting each production process for defects and quality conformance is essential for manufacturers, as it affects their revenue and product recalls. Manufacturers can take advantage of machine vision and image recognition technologies to inspect all aspects of the production process. Usually, AI-powered systems can detect defects that can be missed by the human eye and suggest corrective measures accordingly.


Another use of AI in manufacturing is to compare actual assembly parts with those provided by suppliers to find any quality deviations.


Reimagine Sales and Support


The manufacturer's sales support is not very tech-savvy. By leveraging NLP and conversational AI, they can engage their prospects and answer basic product questions before the sale. Access to information is becoming key in this digital age.


AI can help manufacturers build customer loyalty, improve customer service, learn from feedback, and in turn generate more revenue.


Recommended To Read: IOT in manufacturing use cases benefits and challenges


Factory Connected


Connected factories powered by data, IoT, and the cloud are the way forward for manufacturers in the future. It can help manufacturers to:


  • Track utilization of multiple assets

  • Provide real-time visibility into production equipment and shop floor

  • Create a single source of truth for all data across processes

  • Scale capacity without many interventions on demand


Orders Management


Order management systems need to be agile for manufacturers so they can adjust based on fluctuations in demand, market changes, and customer preferences. Using AI, manufacturers can:


  • Automatically create order entries

  • Automatically create purchase requisitions using sensors to track inventories

  • Seamlessly manage inventory planning


Future of AI in Manufacturing


What's next for the role of artificial intelligence in manufacturing? There are many thoughts on this, some coming from the realm of science fiction and some as extensions of technologies that are already in use. The most immediate noticeable evolution will be an increased focus on data collection. The AI technologies and techniques being employed in the manufacturing sector can only do so much on their own.


However, as AI application development takes place over time, we may see the rise of fully automated factories, product designs done automatically with little to no human supervision, and more. However, we will never get to this point unless we continue the trend of innovation. All it takes is an idea. It could be a unification of technologies or the use of technology in a new use case.


If you have an idea or are looking for ways to apply AI technologies to your business’s needs in the manufacturing sector, contact us today to take that first step.

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