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In recent years, data has become the supreme power in transforming any work process or market scenario. Whether it's customer-based data or revenue information, businesses can leverage it to bring significant changes to their operations, cultures, and domains. Utilizing data is much easier said than done, especially since there are so many redundancies and discrepancies in analytical models and algorithms. However, this didn’t stop the manufacturing industry from undergoing a significant transformation in the adoption of new technologies for evaluating data and unearthing hidden patterns and trends. One significant change that can be seen between traditional and advanced manufacturing practices is the adoption of artificial intelligence and its integration into the core business operations.
It has brought several changes to the entire industry, eliminating numerous challenges and constraints while opening a host of new opportunities. Manufacturing businesses can drive higher revenues, cater to their customer needs, and even incorporate the latest market trends with ease. Having said that, we have crafted a detailed guide about the significance and future of artificial intelligence in manufacturing.
Impact of AI incorporation on manufacturing
Artificial intelligence is not just about analyzing past datasets to predict user actions or market trends. Instead, it focuses on several other aspects, like training machine learning algorithms to adopt human-based behaviors, automate work processes, and even predict future market changes and forecasts. With this being said, we have listed a few ways in which AI has brought revolutionary changes in the manufacturing industry.
- Predicting and preventing future risks: With AI-based models, it will be easier for the manufacturers to determine the risks involved with a new product launch plan, manufacturing process, material procurement, and new vendor associations. One can easily detect the anomalies and deduce plans to mitigate the risks appropriately. This will not only reduce the negative impacts on the business but also improve the overall deliverables and productivity.
- Design generation: Thanks to ML-trained algorithms and AI’s neural networks, designers can easily create multiple designs for a single product. All they have to do is sketch a rough design and give some specific inputs. The AI algorithms will evaluate the input conditions, evaluate datasets, and produce innovative product designs.
- Material price forecasting: Manufacturers are always concerned about the varying raw material prices, especially those that need to be imported from other countries. However, with AI in manufacturing, it will be easier to forecast the changes in prices of different raw materials with optimal accuracy and precision. Apart from this, they can also design variable pricing models to handle the deviations in the material costs, predict changes in import fees, and perform other functions with ease.
- Higher quality assurance: One of the major roles of artificial intelligence in the manufacturing industry is ensuring optimal quality assurance in the entire process line. From detecting any anomaly or discrepancy in the business operations to checking product behaviors after manufacturing, professionals can enhance quality assurance techniques and improve the deliverables.
- Robotics: The implementation of robotic technology with integrated AI and ML algorithms has eased several business operations and automated workflows. For example, the use of AI-based CNC machines, robotic arms, and several other such machinery elements have reduced dependency on human force and increased the overall process efficiency. It has also eliminated the risks of production leaks and enhanced the customer experience.
Ways in which AI will revolutionize the manufacturing industry
Robotics process automation
RPA or robotic process automation is a computerized operation where manual, monotonous processes can be automated using different algorithms and conditional logic. It not only reduces the risks involved with human-based operations but also ensures the overall productivity and performance can be enhanced. For example, the working of a CNC metal cutter for sheet metal fabrication can execute automated workflows based on an AI-based input algorithm.
Supply chain management
The use of AI in supply chain management is pretty much evident from the advancements being witnessed in recent times. For example, manufacturing companies can accurately forecast highs and lows in product demands and accordingly plan the manufacturing cycle to complete the orders. Similarly, tracking and predicting stock levels will help in superior inventory control and management, reducing chances of overstocking and understocking, excessive floor occupancy, correct order placement with vendors, and timely procurement of raw materials for production.
AI-based autonomous vehicles
Several AI-based autonomous vehicles like forklifts, conveyor belts, and many more are already in use at numerous manufacturing units and factories. These work on a pre-mapped route, ensuring optimal floor coverage and ensuring correct navigational control. Furthermore, they are reinforced with IoT sensors to detect any obstruction and automatically change direction to avoid collision and workplace injuries. These not only reduce the manual labor involved with the loading and unloading of products but also promote accurate material placement, faster floor operations, and optimize delivery routes.
Factory automation
One of the major areas where artificial intelligence in the manufacturing industry is likely to bring a significant transformation is in factory operations. Whether it’s automating the alarm system using advanced sensors or establishing an interconnected system to monitor different manufacturing machinery units, AI and ML algorithms can reduce dependencies on human interference. It will further reduce operational expenses, increase factory performance, and enhance productivity by several notches.
IoT integrated with AI
Thanks to the integration of artificial intelligence algorithms with IoT devices, manufacturers can implement a highly connected system in the factories and manufacturing units. For example, AI-based vehicles and machinery units with IoT sensors embedded in them can connect automatically, share data through the internet, and function collaboratively. It will have a significant impact on improving floor safety, reducing workplace injuries, and fostering timely maintenance.
Predictive maintenance
Most machines and equipment units fail to perform optimally due to the lack of timely maintenance, appropriate troubleshooting, and anomaly detection. Additionally, manufacturers often have to deal with compliance issues due to the use of outdated machinery units. To cater to these problems, the implementation of an AI-based dashboard for predictive maintenance will be the most feasible decision. It will automatically extract datasets about machine performance, historic maintenance records, and many more for further evaluation and analysis. As a result, manufacturers will be notified about upcoming maintenance schedules, anomalies, and discrepancies in the regular performance metrics, and compliance issues right on time.
Conclusion
The use of artificial intelligence has skyrocketed across the entire global manufacturing industry. From predicting price changes of raw materials to detecting performance anomalies, this technology can help manufacturers overcome several hurdles and streamline business operations. So, if you also want to unearth its true potential and future-proof your business, collaborate with a credible partner for AI consulting services.
