Technology
Superior by Science
High Realism Model
Powerful Interactivity
Simplified for Production Planners
The MangoGem APS Optimizer is a finite capacity scheduler that is designed to simplify complex production planning and scheduling challenges. It handles tasks like sequence setups, cleaning-in-process, tank planning, batching, multi-level BOMs, and order pegging. By combining planning and scheduling into a single, integrated model, it ensures seamless end-to-end coordination.
Powered by smart algorithms and machine learning, the Optimizer adapts to your unique needs, finding the best solutions to improve efficiency and ramp-up times. Unlike traditional AI that needs large data sets, MangoGem's "small data" approach works effectively with limited inputs, creating powerful solutions tailored to your operations.
Whether on-premises or in the cloud, the MangoGem APS Optimizer integrates effortlessly with ERP and MES systems, delivering fast, real-time results to help you stay ahead in today’s demanding production environment.
Build Confidence Among Planners and Managers
Our AI-powered production scheduling replans your entire plant in minutes, ensuring reliable delivery dates and precise work sequencing. Eliminate manual "block fitting" and free up time for strategic tasks. With multi-user collaboration and customizable access rights, your team can work seamlessly while maintaining control over key production areas. Scenario planning offers better visibility and decision-making power, boosting motivation, autonomy, and helping attract top talent.
Advanced Tanks Planning AI
Optimize tank processes by scheduling input/output flows considering capacity constraints with support for allowed and excluded volume levels, partial fills, batch splits, coupled resources such as pipes, multi-tank groups, best fit sizing, and dynamic allocation. Integrate blending, flushing, CIP, changeovers, dwell times, and short shelf-life constraints. Manage variable in-out flow rates, overlapping processes, minimize yield loss, and prevent cross-contamination. Benefit from shared capacity management, campaign-based scheduling, and real-time adjustments with IoT integration. AI-driven algorithms adapt to real-time bottlenecks and support Just-in-Time (JIT) delivery for optimal efficiency in upstream and downstream processes.
Powerful Features
MangoGem APS Optimizer does not use a single “one size fits all” solver method, such as simulation, simple dispatch rules or a search heuristic.
MangoGem APS Optimizer includes many solvers and heuristics and, depending on an analysis of the case at hand, it will try and apply many methods to find the one that produces the best results. MangoGem APS Optimizer includes sequencing, heuristic search, genetic algorithms, machine learning, etc.
MangoGem APS Optimizer can be used offline, online and even in real-time. It can handle large cases, with dozens of resources, and hundreds or even thousands of activities. In order to create close-to-optimal solutions very fast, MangoGem APS Optimizer can also used parallel multi- threaded solvers, and thus benefit from modern multi-core computing hardware.
The MangoGem APS Optimizer is built upon a proprietary versatile, generic and extensible manufacturing and supply chains framework model refined to be able to model accurately a large variety of use cases with the most complex requirements while being part of a standard software product. This unique design ensures compatibility with all kinds of SCM, ERP or MES systems and eases integration time and effort.
MangoGem APS Optimizer is a multi-resource scheduler. Most schedulers can only handle one type of resource, or only a single resource per activity. MangoGem APS Optimizer can handle multiple instances of equipment, people, consumables, tools, locations, etc. and can also combine several resources together. Any activity can have multiple modes to closely model reality.
MangoGem APS Optimizer is also a multi-objective and multi-criteria scheduler. It does not just optimize one single Key Performance Indicator (KPI) at a time, e.g. minimizing makespan but with many setups or bad resource utilization, but can combine several KPIs together, produce Pareto–optimal schedules and analyze objective trade-offs. Many objectives can be selected together such as makespan, deadline satisfaction, Just In Time, resource utilization, consumables usage, activity switches, cycle time, ... MangoGem APS Optimizer can also help you analyze « what if » scenarios without effort.