Dynamic Production Scheduling

Forecast demand and order change to improve production scheduling and performance.

Industry Challenges

Considerable effort is spent in capital-intensive industries to optimize production processes. Problems such as unpredictable manpower, unexpected machinery delays and unforeseen circumstances create challenges in maintaining production efficiency and can result in significant costs and losses for an organization if it is rendered unable to meet customer demands. DT4o’s production planning optimization model helps in planning and scheduling optimization to remove some of the challenges and subsequent losses due to improper scheduling, if unaddressed.

Learn how DT4o approaches production scheduling optimization for its clients.

DT4o Solutions

  • DT4o’s Production Scheduling Optimization techniques assists in effective manpower planning and machine allocation to ensure efficient production process
  • Opportunity to upgrade processes by introducing automation to reduce delays and the need for human intervention
  • Continuous improvement through analysing historical data to forecast demand and predict change orders
  • Maximize throughput and minimize waste by employing DT4o’s AI algorithms and its proven production planning optimization model

Key Challenges & DT4o Dynamic Production Management Solutions

Solution

Analyze relevant historical data through AI for accurate demand forecasting

Solution

Effectively use algorithms to predict changes in customer orders

Solution

Schedules for manufacturing and distribution are enhanced with the use of AI and IoT following DT4o’s production planning optimization model

Core Capabilities

Demand Forecasting Employing AI

Demand Forecasting Employing AI

  • Real time analysis of metrics allows for better forecasting of demand resulting in improved planning
  • Machine learning is used to predict demand based on different variables such as location, customer and product

Optimized Manufacturing and Distribution Schedules

Optimized Manufacturing and Distribution Schedules

  • Enhance value chain process scheduling to combat delays and deviations
  • Identify cost drivers and bottlenecks that could disrupt production and address them in an efficient manner

Predict Changes InOrders

Predict Changes In Orders

  • Implement AI to predict orders that are likely to change based on relevant historical data 

Achieving ElasticScheduling

Achieving Elastic Scheduling

  • Make use of what-if scenario analysis to assess the impact of production alteration on critical success factors
  • Provide customized recommendations focusing on different variables

Business Benefits