Improved Production Efficiency

Challenge

  • Our task was to develop an ML model to centralize production, accelerate timelines, cut costs, and implement real-time performance tracking for operational ease.

Our Action

  • We analyzed data, developed an ML model, implemented real-time monitoring, standardized procedures, and conducted training for operational enhancement.

Result

  • Optimized operations resulted in reduced production time, costs, and enhanced quality through real-time monitoring and standardized procedures.

Brief

A Food Processing Industrial plant owner in APAC worked with us to improve production efficiency in its plants. Each plant was having operation with their own set of rules and there was a need for synchronization and standardization among the plants

Challenge

Our team had a task to develop the ML model to optimised and centralised production among plants in order to speed up the production time and reduce cost. Also there was a requirement to prepare a system for real-time tracking of performance – to make life easy for the floors managers and other senior members.

Our Action

  • Consolidated data from each plant to identify inefficiencies and establish performance benchmarks.
  • Leveraging advanced algorithms, we designed a centralized production optimization model.
  • Implemented a robust system for real-time performance monitoring.
  • Worked closely with plant personnel to standardize operating procedures.
  • Conducted training sessions to ensure smooth adoption of the new system.

Results

  • Optimized schedules led to a significant reduction in production time.
  • Streamlined operations minimized resource wastage, reducing overall costs.
  • Real-time monitoring enabled prompt intervention to address issues.
  • Consistent procedures improved efficiency and quality control.

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