Only inside DHB4.0 you can have advanced planning & scheduling with powerful features that allow us to build a custom solution. It’s a solution designed to aid you in long and mid-term planning. Is an interactive, multi-constraint scheduling system that provides support for decision-making for overtime, order prioritization, production batches, due date negotiation, order processing. It enables manufacturers to respond quickly and intelligently to unexpected changes, while satisfying customer demands with shorter lead times. With our solution, you can perform risk analysis in real-time and also taking into account the system variation, which allows performing a probabilistic analysis to estimate the underlying risks associated with the schedule. The risk output generated will include the probability of meeting your goals defined in the experimenter tool considering scenarios expected, pessimistic, and optimistic.
Our tailored made production scheduling extends traditional APS to fully take into account the variation that is present in any production system, and provides the necessary output to the professionals in charge of that task in the companies, and also allows you to mitigate the risk and uncertainty. It’s totally integrated with all of our solutions, especially the FlexSim Live, which allows users to model any system at any level of detail and can incorporate all of the random variations.
We also develop simulation-based planning & scheduling solutions totally tailored-made, by combining simulation and mathematical optimization. With more complex systems you need actual insight on what the best approach is. That is why DHB4.0 can incorporate mathematical optimization combined with simulation models to create Simulation-based planning & scheduling. The simulation will show the actual effect of how a combination of optimization and heuristics on the system performance. In this way, it is possible with an iterative approach to find the “best proven” solution including.
The Oil industry is one of the pioneers in the widespread adoption of optimization techniques, for instance, whoever, each sector and company has its particularity.
At an abstract level, refinery optimization is about getting the most from the existing assets; by extension, it can also refer to the most profitable investments in new equipment or new assets. This first distinction gives rise to 2 horizons of application to refinery optimization: long-term, structural optimization, and short-term operations optimization.
Moreover, operations management itself can be addressed in a variety of ways, depending on whether the approach taken to refinery optimization is bottom-up, or top-down:
- The top-down approach is based on hierarchical optimization: the refinery optimization problem is addressed as a succession of optimization problems of different time magnitudes and granularities. The first problem is a mid-term planning problem and is concerned with the refinery as a whole- and a time frame of one to several months. Subsequently, the time frame is subdivided into finer time intervals. At the lowest level, the theoretical goal is to achieve operations scheduling on a day-to-day basis.
- The bottom-up approach is one that starts with local problems and tries to aggregate them into a consistent solution at the refinery level.