The manufacturing industry takes advantage of these real-time tools in order to predict and prevent potential problems, while maximizing the performance of operations and workforces in production plants by collecting, storing and organizing data generated by machines, devices and internal systems on the production floor.
Predictive models combine the power of Big Data with artificial intelligence and machine learning to understand, monitor and optimize processes. Success in manufacturing today rests with whoever business has the most accurate and comprehensive knowledge of digital models and Big Data analytics.
The benefits of implementing predictive models in this industry are:
They use aggregated real-time sensor data from parts, components or machines to more accurately anticipate part, component or machine failure. This optimizes processes and reduces maintenance costs.
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Improve execution manufacturing systems.
They predict major changes in raw material costs, reducing scrap, identifying significant cost drivers, finding bottlenecks in their operations and adjusting their control loops to improve operational efficiency and profitability.
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Establish different connections between the variables and drivers that generates a demand, helping to improve all the supply management practices.
Improve KPI analysis for workforce management.
Organizations need to predict staffing, scheduling, training and productivity challenges by evaluating a wealth of data to gain deep insight into their workforce, this models helps the creation of the right balance of staff or even anticipate which employees are about to leave to keep the dropout rate as low as possible.
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At PREDIK DATA-Driven we support manufacturing industries to start their transition to implement predictive models and big data analytics to reduce the work associated with manual data collection and anticipating future problems.
Do you need help to optimize your production processes?¡Contact us!