Advanced Planning and Scheduling is a software tool that uses algorithms and data analysis to optimize production planning and scheduling. It generates a detailed plan for efficient execution and, together with MES/MRP systems, predicts future production requirements.
By considering inventory levels, machine availability, order priorities, and lead times, it generates a production schedule that maximizes resource utilization while minimizing waste and costs. Advanced planning and scheduling help manufacturers make informed decisions and quickly respond to changes in demand or supply chain disruptions.
However, even with APS, manufacturing can be challenging as a plan can go awry quickly without considering the manufacturer’s individual dependencies. The VirtusLab provides a new approach to help manufacturers produce quality products, estimate costs, avoid loss, and prevent overcharging the manufacturer’s clients.
The VirtusLab's Research and Development department soon marks the culmination of the software development cycle that adapts to your business needs. This incorporates dependencies, next to production data, inventory levels, machine availability, order priorities, and lead times to generate a production plan.
An ML algorithm provides a detailed prediction of a selected KPI's increase with an outlined specific production queue. The newest approach is that ML models and heuristic models learn from past productions, mistakes, and optimizations. By adding business-specific dependencies, such as human resources and their limitations, the software helps to optimize OTIF, OEE, and the sequence of operations, and reduce production bottlenecks, and idle time based on real-life scenarios. It immediately adapts to your situation, increasing your business's value.
While Advanced Planning and Scheduling (APS) is typically used to optimize production planning and scheduling processes, it lacks the ability to react quickly to ad-hoc dependencies. The Research and Development team at VirtusLab took it upon themselves to solve this problem. Here are the steps you should take to benefit from the R&D approach:
- Identify dependencies: Identify and include the dependencies between stages of the production process. This includes raw material, equipment, and labor requirements. By understanding these dependencies, the R&D approach optimizes the production process for maximum efficiency and cost-effectiveness.
- Define KPIs: Once you know which key performance indicator (KPI) you need to increase and measure the success of the production process, the system can apply changes to the production plan accordingly.
- Collect data: Data comes from various sources, such as ERP, MES, and machines, accumulated within the new APS. This data together with the dependencies creates the base for the new, efficient production plan.
- Ingest data into software: Software creates a digital representation of your company including its processes, dependencies to fuel the optimization algorithms and artificial intelligence.
- Test the outcome: Adjust the production process by utilizing ML algorithms to attain the desired outcomes for your production queue. The models will present a percentage prediction of the optimization of key performance indicators. Additionally, the algorithm integrates past production knowledge and experience to enhance the results. It can also identify the root cause of optimization failure based on the input data.
- Execution and Monitoring: Once the production process is optimized, you can execute the production plan and monitor the process in real-time. This allows you to quickly adjust the plan if necessary to maintain maximum efficiency and optimize the KPIs identified.
Manufacturers enjoy several benefits by using the new R&D approach to APS. The most important one is that manufacturers can finally optimize their production plan and choose the best production queue depending on the chosen KPI, such as ETA, stock level reduction, or any other business goal. The new approach creates a digital twin within the APS of your factory. This enables you to react immediately to machine failure or human dependency, such as a shift change.
This translates into:
- Better resource utilization
- Increased agility
- Cost reduction
- Enhanced customer satisfaction
VirtusLab's innovative integration of advanced planning and scheduling techniques marks a significant advancement in production planning. With its emphasis on adaptability and optimization, manufacturers can now navigate complexities with greater efficiency and precision, heralding a new era of advanced planning and scheduling in the industry.
