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. ThinkDigits’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 ThinkDigits approaches production scheduling optimization for its clients.
ThinkDigits Solutions
ThinkDigits’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 ThinkDigits’s AI algorithms and its proven production planning optimization model
Key Challenges & ThinkDigits 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 ThinkDigits’s production planning optimization model
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
