Strategic Capacity Planning
As part of strategic capacity planning, the required workforce is determined, budgets are planned, and various scenarios are considered. Using a true-to-scale model and adaptable standard times and time studies, realistic process times can be detected in the digital twin. Based on the simulated storage tasks, the necessary personnel for each process in the logistic sequence can be realistically identified. This makes it possible to determine in the long term which workforce and shift model is suitable in which situations. Load peaks can be simulated and, allowing for the examination of a mix of regular and temporary employees. Different work time models can be evaluated as well.
Mid-term Capacity Planning
For medium-term planning, future demand is estimated based on expected demand. The objective is to make the most accurate planning possible based on information from the past. At the same time, the expected workforce needs are automatically calculated considering the forecasted sales volumes and order structures. From this, holiday planning can be generated, which is based on holiday requests from higher-level management systems. Approval is then granted on the basis of the expected capacity requirements. A similar procedure is used for foresighted shift planning. The shift structure and numbers are determined for a mid-term period.
Operational Workforce Planning (Online Productivity Control)
One of the key elements in operative workforce scheduling is current load balancing in the digital twin. Based on current orders and, if necessary, short-term forecasts, the expected workload is simulated over the day. This results in a division of employees according to their abilities in the work areas. The expected completion date for each order is constantly monitored, so if a delivery is in danger of being delayed, it is possible to react in time by re-prioritizing orders and reallocating employees. In the event of newly arising circumstances, such as system failures, a reallocation can be initiated at any time. This can be done automatically. The constant transparency of the workload and the reduction of unused resources lead to an increase in productivity in the overall process productivity.