Scheduling is used for daily order termination in the production environment, ensuring near-optimal resource allocation and adherence to deadlines for most customer orders.
What scheduling systems are for?
Differences in scheduling systems
Impact of variability, an experiment
Compare yourself
We offer simulation or optimization based scheduling technology. Both of them can:
Forward scheduling of production orders
Experimentation with extra customer demands
Consideration of limited resource capacities
Material planning using Bill of Materials (BOM)
Incorporation of priorities, qualities, and other factors
Adjustments based on real-time resource availability
Management of personnel qualifications
Application of changeover matrices for machines
Integration of alternative resources and operators
Shift modeling for workforce planning
Calculation of secondary resources (e.g., limited tools)
Visualization of schedules in Gantt charts
Detailed resource logs and reporting
Seamless integration with databases and other data sources
Simulation-based and optimization-based scheduling techniques differ significantly in their capabilities. Understanding their unique advantages and limitations is essential to harness their full potential effectively.
Dynamic Evaluation: It provides a detailed and dynamic assessment of the production environment. This includes transport activities, delays in parts supply, and production congestion.
Bottleneck Management: Identifies and plans for bottlenecks,ensuring all other processes align properly.
Probabilistic Analysis: This calculates and displays the likelihood of order completion. It factors in random delays like equipment failures or staff unavailability.
Detailed Resource Tracking: Offers precise tracking of staff, batches, and resources, including their availability and movements.
Realistic System Representation: Faithfully replicates the unique features of your production system for precise modeling.
3D Animation: Enables easy validation of daily plans through visual simulation, making it easier to understand and analyze.
In-Depth Modeling: Projects are meticulously developed using simulation models, often uncovering valuable insights (“aha moments”) for all stakeholders.
Reverse Planning: Supports reverse planning strategies to adapt production timelines as needed.
Manual Overrides: Allows manual assignment of orders to specific resources for greater control.
Optimal Combinations: Finds the globally best combination of processes in production based on a user-defined target function. Orders are rearranged and scheduled to achieve the best possible result.
Standardized Frameworks: Includes predefined data templates and a robust model framework suitable for many standard production applications.
Active Feedback Loop: Features a user console with real-time feedback from production, enabling on-the-fly rescheduling in case of discrepancies.
Dependency Visualization: Clearly visualizes order networks and dependencies for better planning and decision-making.
Extensive User Base: Trusted by a large and diverse customer base.
An Experiment: Which Scheduling Method Predicts Delivery Dates More Accurately?
A simulation model was created to replicate a dynamic production process. Key features included:
Stochastic Process Times: Each process step had variable durations within a defined range (least to highest) instead of fixed times.
Random Resource Failures: Resources were prone to unplanned failures, reflecting real-world variability.
The scheduling techniques were tested under these conditions:
Simulation-Based Scheduling: Directly incorporated stochastic process times, resource variations, and failures.
Optimization-Based Scheduling: Required fixed process times; thus, average process times were used, and resource failures were excluded from the model.
Results were plotted in a chart showing the cumulative delays (in hours) of completed orders over time. Each scheduling tool generated production schedules for all orders. The simulation model was run with these schedules to track actual production outcomes under dynamic conditions.
Orange Line – Due Dates: Shows target delivery dates promised to customers. There are no delays (baseline).
Brown Line – Deterministic (Optimization-Based Scheduling): Indicates early order completion with cumulative delays around -1400 hours. Orders were, on average, completed much earlier than their due dates.
Blue Line – Stochastic (Simulation-Based Scheduling): Reflects significant delays, with cumulative delays of approximately +1700 hours. Orders were, on average, completed much later than their due dates.
Green Line – Actual Production Sequence: Shows real production outcomes. It ends with cumulative delays of around +1000 hours. This shows that orders were generally late.
Simulation-based scheduling proves more effective in dynamic production environments. It accurately predicts delivery dates. This is achieved by accounting for variability and unexpected events early in the planning process.
Yet, its sequential processing approach—using start dates and local choice rules—limits its global optimization capabilities. In contrast, optimization-based scheduling uses a global search strategy. This strategy determines the best sequence of orders and operations. It is more suitable for stable and predictable production systems.
Choose simulation-based scheduling for highly variable environments where accuracy in forecasting delivery dates is critical. Opt for optimization-based scheduling in well-controlled settings where maximizing efficiency and meeting due dates is the priority.
Experience the impact of each scheduling type firsthand. We can show how both simulation-based and optimization-based scheduling work within your production system. This will give you a clear understanding of their effects on your processes and outcomes.
Share your project requirements with us, and we’ll help you find the best solution to bring it to life.
Distance is no obstacle! We’ve successfully collaborated online with customers from the USA, Sweden, France, Denmark, Portugal, and many more. Let us help you, no matter where you are.
+49 351 30906020dresden@simulatefirst.com