APS and Digital Twin
A digital twin is a virtual representation of a physical object, process, or system used to simulate, analyze, and optimize its performance. Advanced Planning and Scheduling (APS) systems can be used to fulfill important purposes of digital twins.
APS systems are software tools that use algorithms to optimize production planning and scheduling. They help manufacturers simulate and improve production processes, use resources efficiently, and reduce lead times, inventory, and manufacturing costs.
By using master data from the ERP system, APS creates a virtual representation of the future production schedule—weeks, months, years ahead—like a digital twin. APS systems simulate different production scenarios, identify potential bottlenecks or production constraints, and optimize production schedules.
By using an APS system, manufacturers can reduce stagnation time, improve production efficiency, and increase output by simulating different scenarios and predicting the impact of changes before implementing them in the real world, such as new shift models or investing in new machines. This helps reduce the risk of costly errors and improves overall performance.
The precondition for feasible and good scheduling is that the APS, as the word “twin” implies, is capable of mapping reality to 100% accuracy in terms of:
- product properties
- process rules and restrictions
- resource capabilities
- order dispatching rules
- scheduling logic—process-wise and overall
Most APS software available on the market do not meet this first precondition. There are other reasons why APS systems may fail as a digital twin:
- Lack of master data precision: A digital twin relies on accurate and timely data from various sources such as ERP and MES systems. APS systems may not be able to integrate this data effectively, particularly if the standard times of master data are incorrect, leading to inaccurate simulations and predictions.
- Limited scope: Many APS systems are often focused on optimizing production schedules within a specific facility or department. However, a high-end APS as a digital twin requires a holistic view on the synchronization of the entire value-added chain, including upstream and downstream operations, material supply chain, and customer demand.
- Complex algorithms: Digital twin technology requires complex algorithms to model and simulate the manufacturing process accurately. Many so-called APS systems available on the market may not have the necessary algorithms or computing power to handle the complexity of a digital twin.
- Lack of expertise: Implementing a digital twin requires expertise in multiple disciplines, including data science, modeling, simulation, and standardized processes and methods in all processes. Companies may lack the necessary resources and expertise to successfully implement an APS system.
- Resistance to change: Implementing an APS system as a fully automated scheduling system requires significant changes to existing manual processes and systems. This can lead to resistance from employees and management, making it difficult to implement an APS successfully.
Overall, implementing an APS/Digital Twin requires careful planning, collaboration across multiple teams, a deep understanding of the manufacturing process, and a reliable APS consultant.
Posted by Keiji Fujii