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In the OCP phosphate supply chain, source ores (SOs) are extracted according to a tactical extraction programme, constrained by geological conditions that constantly limit and modify the variety of available SOs. Then SOs are blended to get merchantable ores (MOs) respecting composition constraints and ordered by internal (phosphoric acid plant) or external (export) customers. The blending process is performed in a dry blending plant, possibly followed by treatments in a washing plant which modifies the SOs weights and compositions. The choice of alternative routings and blends depends on orders book and SOs availability in the dry blending area or present on mine. To improve the performance in meeting a rolling 4-weeks orders book, a quadratic model was created and implemented. It optimises jointly: (i) for each order, the routing and the SOs quantities used in the dry blending plant; (ii) the SOs quantities transferred from the mine; (iii) security stocks to face some unforeseen change in the MO book order, and the slight instability of the SO chemical composition that triggers a SO multiplication to be contained. The performance of the linearised model has led the relevant OCP site to develop and use an extended version of this model.

Purpose: Demand Driven Material Requirements Planning (DDMRP) aims to deal with variability byadjusting inventory levels while maintaining, or even increasing, customer service levels. This approachbridges the push and pull approaches. Even though it first made its appearance in 2011, research in thisfield remains relatively limited. This paper aims to analyze the temporal evolution of the DDMRP, itscontext of implementation, and the research themes studied in that field to identify areas that still need tobe addressed by future researchers.Design/methodology/approach: The systematic literature review approach used in this paper examinesresearch dealing with the DDMRP published in different languages between 2011 and 2020. To date,published papers focused on performance analysis and comparison of the DDMRP with other methods.This study focuses on the DDMRP itself and its capacity to answer the different operations managementfunctions under a broader vision (context, implementation, setting, etc.). Thus, we analyze the evolution ofthe method in the literature, considering different languages, and present a taxonomy of publishedscientific works. Then, we identify gaps that require further research.Findings: DDMRP is not sufficiently studied in the literature and the proposed tools still need to betested. More research is required to evaluate its adaptability in different and complex environments, addressits ability to cope with product variety, complex BOMs, and other methods. A proposal of new approachesto define and adjust DDMRP parameters and evaluate their sensitivity is also required to make the methodmore scientifically sound. Originality/value: Based on the analysis of papers published in different languages, this paper outlinesthe current state of the art of DDMRP, its shortcomings, and identifies further research to make DDMRPmore robust from both a scientific and industrial perspective

Open-pit phosphate mine is characterized by a stack of layers with different chemical characteristics (Source qualities SQ). The extraction process involves various elementary operations performed by a dedicated or polyvalent machines. The tactical mining scheduling consists to define the blocs to be extracted and assign the machines over the planning horizon. However, the interdependencies and complexity characterizing this problem make the decision-making process so difficult. This paper proposes a multi-criteria approach integrated in an Interactive Decision Support System (IDSS) based on an original sequential approach selecting the most performant mining scenarios. Indeed, a discrete event simulation-based model developed and encapsulated in this IDSS proposes various scenarios. With a developed multi-criteria filtering approach, each scenario is approved by a feasibility study to verify that a scenario can satisfy the demand for merchantable qualities (MQ). Then, the feasible scenarios are analyzed based on their robustness when facing disturbed demand vectors and compared by other effectiveness and efficiency criteria. To preserve only the two or three most performant scenarios.

International audience; as open-pit mines consist in the accumulation of ore layers of different characteristics, their extraction process results from the iteration of a sequence of elementary operations performed on parcels by specialized or multipurpose machines. Medium-term extraction programming consists in deciding the assignment of the available machines over time. This problem is addressed through Discrete Event Simulation implemented in a phosphate mine, taking into account all the extraction constraints to drive the extraction process. This combines an effectiveness criterion (degree of urgency of obtaining certain ore qualities) and an efficiency criterion (machine displacements). While the parameterization used to control simulation quickly produces many technically feasible scenarios, making the final optimal choice is extremely difficult, particularly as one needs to take into account time considerations in extracted ore progressive provisioning and machine use. Our paper describes the bases of a visual decision-support system (DSS), currently under development, which enables the processing of results to compare multiple scenarios and adjust parameterization in order to come up with a good solution. This web-based DSS is coupled to the simulator via a relational database.

This paper presents the architecture of an interactive scheduling decision support system (ISDSS) allowing users to find the optimal solution for fertilizer production on parallel heterogeneous processors. The proposed approach takes into account different production process constraints such as launch time, delivery date, preventive maintenance and the impact of scheduling on supply chain management. The ISDSS implemented is run by a relational database used to customize the structural data and the problem parameters. A user interface is available for ISDSS users to define the scheduling problem and design the solution based on tables and graphs for detecting possible issues. The ISDSS architecture was implemented on java using independent modules.