MangoGem APS Optimizer vs Phoenix APS

MangoGem APS Optimizer is a finite-capacity scheduler for enterprise production planning and supply-chain operations. It combines planning and scheduling in one model, handling sequence setups, cleaning-in-process, tank planning, batching, multi-level bills of materials, and order pegging. Tank planning covers capacity constraints, partial fills, batch splits, coupled resources, blending, flushing, and cleaning in place. The optimizer can target up to five KPIs at once from more than 50 built-in options, using methods including sequencing, heuristic search, genetic algorithms, and machine learning. Teams can compare objectives through what-if scenarios and multi-objective scheduling. MangoGem says the system can handle dozens of resources and hundreds or thousands of activities, with offline, online, and real-time use. It supports machine, labor, and material constraints, multi-site scheduling, collaboration, and configurable access rights. Deployment is available on-premises or in the cloud, as self-hosted software or through the web. The maker says it integrates with ERP systems such as SAP and Microsoft Dynamics NAV, as well as MES and sensor data. Pricing is on request.

Phoenix APS helps planners build feasible production schedules across machines, people, and tools while accounting for calendars, setups, dependencies, and material availability. It enforces capacity limits on machines, lines, and human skills, and models parallel, alternative, and sequential routings at operation level. Machines, operators, and equipment can be scheduled together. Calendar handling includes closures and working-time changes, while dependencies support finish-to-start relationships with configurable lags. Material checks use bill-of-material availability with Fixed or Proportional quantities and AtStart, Uniform, or AtEnd laws. Planners can change assignments and rules to see the impact; infeasible jobs can be parked with reasons and retried using targeted relaxations. The interface includes a Gantt timeline, operations table, quick filters, and a what-if solver. HTTP JSON endpoints let ERP or MES systems send master data and retrieve dated plans. The maker describes the approach as heuristic and rule-based, aimed at fast, explainable feasible plans, with optimization modules on the roadmap. A free beta evaluation installer is available for Windows, but its temporary license does not permit production use. The project is described as personal and non-commercial.