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Manufacturing Sector: 10 Use cases of AI

AI has many benefits for manufacturers. Leaders should consider these 10 manufacturing AI use cases.

1.Cobots assist humans-  Collaborative robots, or cobots, often assist humans. Cobots can learn several tasks, unlike autonomous robots. They can recognize and avoid obstacles and collaborate with humans due to their agility and spatial awareness. Manufacturers use cobots for heavy lifting and manufacturing assembly processes. Automotive cobots can lift and hold heavy car parts while human workers secure them. Cobots can search big warehouses for products.

2.RPA handles tedious tasks - Manufacturing businesses utilise cobots on the production line, while RPA software is better in the back office. RPA software handles high-volume, repetitive activities like data transfers, inquiries, calculations, and record maintenance. RPA software automates order processing, eliminating the need to manually enter data and hunt for errors. Thus, RPA could save time and labour.

3.Digital twins improve performance -  Digital twins help companies understand complex machinery. A digital twin is a virtual representation of a physical object that receives information about its physical counterpart through the latter's smart sensors. The digital twin provides object understanding through AI and other technologies. Companies may monitor an object throughout its existence and receive vital notifications like inspection and maintenance needs.  Sensors on an aeroplane engine send data to its digital twin every time the plane takes off or lands, giving the airline and manufacturer vital engine performance data. This data helps airlines simulate and predict challenges.

4.Predictive maintenance boosts safety and cuts expenses. -  Manufacturing facilities, railroads, and other heavy equipment users are using AI-based predictive maintenance (PdM) to predict service needs. Maintenance delays cost companies time and money. Early machine maintenance wastes money and resources. Waiting too long can wear down the machine. The latter can potentially expose personnel to safety issues. Companies can also use PdM systems to estimate replacement part needs.

5.Lights-out factories save money - "Lights-out factory" AI in manufacturing use cases are rare but promising. A lights-out factory uses AI, robotics, and other cutting-edge technologies to run without humans. Lights-out factories can save money because robots don't need as much as humans. A robotic factory doesn't need lighting, air conditioning, or heating. Adjusting these services saves manufacturers money. Robotic labourers can work 24/7 and produce more things with fewer errors than humans.

6. AI predicts demand -  Machine learning AI systems can recognise human buying trends and inform manufacturers.

Some machine learning algorithms recognise purchase patterns that prompt producers to increase production. This capacity to predict purchase behaviour helps ensure that producers are generating high-demand merchandise before the stores need it.

7.Inventory management avoids bottlenecks -  Some manufacturing organisations are relying on AI technology to better manage their inventory demands. AI systems can keep track of resources and deliver notifications when they need to be replaced. Manufacturers can also use AI to find supply chain bottlenecks. Pharmaceutical companies may use short-lived ingredients. AI algorithms can forecast if that ingredient will arrive on time or, if it's running late, how the delay will influence production.

8.AI improves supply chain management - Supply chain management uses AI well in manufacturing. Supply networks of large manufacturers process millions of orders, purchases, materials, and ingredients. More firms are using AI to automate supply chain activities because manual methods take time and resources. A carmaker may get nuts and bolts from two suppliers. If one supplier mistakenly delivers a bad batch of nuts and bolts, the car manufacturer will need to identify which automobiles were built with that precise nuts and bolts. AI systems can help manufacturers recall vehicles with defective nuts and bolts.

9.AI detects faults -  Automated visual inspection technologies help manufacturers find production line faults. Machine vision cameras can spot defects faster and more accurately than humans.

Visual inspection cameras can readily discover a cellphone problem. Before the product reaches a dissatisfied customer, the AI system can notify personnel.

10.AI accelerates product development - Some manufacturers are turning to AI systems to assist in faster product development, as is the case with medicine companies. AI can analyse experiments and manufacturing data. Data analysis can help pharmaceutical manufacturers cut costs, time, and duplication.

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