Site icon Pakka Maitri

Nayi Soch: Dakshata Vikas Sangh – Abhishek Dixit

Artificial intelligence is transforming manufacturing!

Artificial intelligence (AI) in manufacturing refers to a machine’s ability to think like a human, respond independently to internal and external events, and anticipate future occurrences. When a tool wears out or something unexpected—or perhaps evens something unexpected—happens, the robots can recognize it and take action to fix the issue.

Workplace Safety

Work-related accidents & injuries in the Indian manufacturing industry are a huge issue, and a number of such incidents are seen frequently. Artificial Intelligence (AI)-powered solutions in manufacturing, specifically in sectors like chemicals, heavy machinery, and big assembly lines, can help predict possible faults in equipment, assembly line robots & safety measurements, and thus, help reduce accidents.

Machine Maintenance

Machine Learning (ML) is the type of AI that crunches huge datasets to spot patterns and trends, and then uses them to build models that predict what will come in the future. ML allows forecast fluctuations in demand and supply, estimates the best intervals for maintenance scheduling, and spots early signs of anomalies.

Why Adopt AI?           

  1. Predictive maintenance: By taking historic data from maintenance logs, you can predict how a machine will behave under a future payload, whether you’ll need to fix it, when, why and how – based on what fixed that problem in the past. This can reduce downtime significantly.
  2. Predictive quality:  Predicting and reducing failures can yield significant cost savings.
  3. Scrap reduction: Using metrics to predict behavior across product specifications can minimize scrap and maximize product quality.
  4. Increasing yield:  Predicting if and when a machine or process will no longer meet given specifications enables you to proactively do what’s needed to bring it back into specification, reducing quality passes.
  5. Demand and inventory forecasting:  With a thorough understanding of plant operations and the data behind production, it’s possible to forecast the demand and movement of critical parts, resulting in significant inventory savings.
Exit mobile version