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Optimizing Industrial Operations with Artificial Intelligence

By CIOAdvisor Apac | Tuesday, February 05, 2019
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Manufacturing Industry is one of the foremost in using Artificial intelligence (AI). Robotic parts are used in the factories to assemble different parts together and then pack them without any manual help. Starting from the raw materials to the shipped final products, AI plays an eminent role in most of the entities.

Data analytics and Machine learning (ML) were prominently used in industrial operations. The main objective of Data analytics is planning and optimizing operations. Companies have been using this technique, although on a smaller scale. There is ample scope for machine learning to take Data Analytics to a different level.

Artificial Intelligence is used to improve the effectiveness and efficiency of industrial operations. Steel manufacturing companies can benefit from AI tools like control systems, sensors, and ML-based optimization.

Check out CIOAdvisor APAC's Top 10 APAC Machine Learning Solution Providers - Elliptic Labs, Faethm, Megvii,...

Predicting Demand

Prominent companies need an accurate prediction for the demand of steel to invest their capital wisely. Machine learning uses tools like macroeconomic data along with the historical demand for steel to make accurate predictions.

Scheduling Optimization

 Steel manufacturing company’s main concern is its products and timing of production. This is important because electrical energy is costly and one of the most important inputs. The optimization models minimize energy costs, especially at non-peak times.

Optimizing production

 Steel manufacturing industries are prone to accidents. The molten steel can come out of the mold during the casting process or rolled steel can escape from the rollers on to the mill floor. These situations can be dangerous and expensive and may even stop the production. ML can predict and help in minimizing such situations.

Early warning systems

 AI provides necessary information about the machines so that the industry can take rectification steps on time and prevent accidents. This need-based repairing of machinery on time plays a prominent role in enhancing the lifespan of the industrial machines.

Cost of production

 AI tools will help to identify the mathematical correlations that will eliminate the costs of production and enhance the quality of steel.

Outbound transportation

 AI can help by optimizing delivery windows for their customers. Various manufacturing companies have used ML and AI for improving their operations. Statistics show that ML can increase production capacity by a minimum of twenty percent while reducing the rates of material consumption by four percent.

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