detailed scheduling in production is a complex but crucial process. From the optimal use of resources to the minimization of waiting times in production, much depends on how precisely detailed scheduling is carried out. Modern companies are faced with the challenge of designing ever more flexible and efficient production processes. This raises the question: how much of this planning process can be automated? Can software solutions with artificial intelligence (AI) take over detailed scheduling completely, or will human intervention remain indispensable?
1. diverse challenges in the detailed scheduling
detailed scheduling is characterized by a large number of variables that all have to be taken into account in real time: Machine availability, material flows, personnel capacities, personnel qualifications and unexpected disruptions. This high level of complexity often means that even the smallest deviations from the plan can have a major impact on efficiency. Such diverse dependencies and uncertainties make detailed scheduling a particularly challenging task.
2. potential of automation in the detailed scheduling
With the advent of new technologies such as AI and machine learning, there are enormous opportunities to make detailed scheduling more efficient. AI algorithms make this complexity manageable and generate optimized detailed plans in a short time. This type of automated planning surpasses human capabilities, especially in terms of the speed of planning and the KPIs achieved by the plan created, such as on-time delivery, lead times, etc.
3. limits of automation
Despite all the progress, however, there are also clear limits to automation. detailed scheduling benefits greatly from human expertise in many cases. There is always knowledge or contextual information that is not captured in data. This information is often missing in fully automated systems, which means that AI-supported detailed plans cannot be implemented in practice or set the wrong priorities. In practice, we often observe that certain detailed information that would be necessary for full automation is missing. However, achieving these final percentages of data quality would require very extensive data maintenance, which is often not economical.
4 The spectrum of automation: The optimal planning approach
There is no general answer to the question of how much automation makes sense. There is a spectrum of approaches ranging from purely manual planning to complete automation. The optimum point lies between the two extremes: detailed scheduling is automated as much as possible, with human intervention where necessary.
In contexts with very comprehensive and high-quality data, it is perfectly possible to automate almost completely. However, it often makes more sense to make targeted manual adjustments to compensate for missing information and further refine the plan. It is important to change the automatically generated plan as little as possible in order to maintain the optimization of the KPIs. Major interventions should provide an opportunity to scrutinize and further improve the data quality.
5. advantages of the partially automated detailed scheduling
The combination of automation and human expertise offers clear advantages at detailed scheduling :
Increased efficiency
Automation of recurring tasks saves time and reduces planning effort.
Improved planning accuracy
By using real-time data and mathematical optimization, AI systems make better decisions.
Flexibility and control
The human planner remains in a position to intervene and make adjustments in the event of unforeseeable events.
6 Conclusion and outlook
detailed scheduling can be automated in many areas, but humans remain an important factor. The best results are achieved when AI-based software solutions and human knowledge work together optimally. Particularly in cases where the data situation is not perfect, semi-automated planning is the key to success.
Future developments in AI and data processing will continue to drive automation forward. At the same time, it is crucial that software solutions remain flexible so that human expertise and know-how can continue to be meaningfully integrated into the detailed planning process.
