Make the most of scarce resources
In a context of discrete manufacturing, volatility and uncertainty are daily occurrences.
Managing manufacturing activities means managing many types of incidents and interruptions due to supply delays, changes in priority, prototypes to be inserted, machine stoppages (some scheduled, others less so) and absences of critical resources.
Discrete manufacturing productions are also characterized by small production batches that lead to many changes in machine setup.
This, in a context where resources are limited (because they are expensive and scarce) and where zero shortcomings must be the norm.
A powerful scheduling engine
With PlanningForce, this complexity is on the one hand modeled, and on the other hand processed automatically by the planning engine which has been designed to take into account all the constraints that weigh on the planning of industrial production activities.
PlanningForce’s proprietary calculation engine takes into account all project requirements as well as overall resource capacity. It does so to calculate an optimal allocation match between them. It therefore generates a resource-constrained schedule, while also taking into account priorities, resource levels, risks, historical values, and estimated changes in time.
It finds optimal plans for thousands of tasks in just a few seconds, using combinations of heuristic algorithms and applying advanced automatic resource leveling.
Sales & Operations are dynamically connected
PlanningForce builds a much stronger connection between sales & operations. Its very quick planning engine and seamless connection with the ERP system enables the acceleration of timing feasibility confirmation in the sales process to near real time. It also improves reliability as companies meet promised delivery dates.
By supporting powerful simulation capabilities at all planning horizons, PlanningForce becomes a sort of Digital Twin applied to the management of the company. It then allows the company to test multiple scenarios and to measure their impact on a large variety of Key Performance Indicators.
The data model and the capture of relevant data at every step of the value chain feed a data warehouse. This enables advanced analytics and nurtures ongoing improvement.