Driven by the emergence of new technologies, Industry 4.0 or industry of the future refers to a new generation of connected, robotized and intelligent plants factories. Operations are transforming and incorporating a digital vision, reinforced by the introduction of artificial intelligence, big data and data analytics in industrial processes (remote control of machines thanks to autonomous control system, predictive maintenance...).
As a key player in Mathematical Decision Making, OCP SOLUTIONS can provide you with expertise in optimization, modeling, quantitative analysis, and data science techniques.
Capitalizing on OCP Group's knowledge and know-how, and on a track-record of several years in Modeling & Analytics, OCP SOLUTIONS offers you tailor-made models, whether they are domain centric models or multi-domain models.
Modeling et Analytics
Our consultants combine cross-functional skills in Modeling & Analytics and key industries to listen and understand your issues, analyze and exploit data to help you make the best decisions or study market scenarios.
Operations research
Our teams propose models based on Operations Research (optimization of results based on input data and defined systems) or on Machine Learning (data exploitation in order to derive new systems useful for decision-making).
D-B-O-T approach
Our approach is inclusive. The success of a project depends on the ability to get our customers on board upstream, by sharing the diagnosis, building solutions together and building the skills of the teams in a D-B-O-T (Design, Build, Operate and Transfer) approach.
Some case studies:
Developing a solution that generates cost-curves by modeling market dynamics;
Designing and developing a decision-support model to optimize the chartering schedule for deliveries with the objective of minimizing freight and demurrage costs and improving customer satisfaction in terms of lead time
Developing a model for fleet sizing with the objective of minimizing fleet and personal costs based on demand and customer satisfaction;
Developing Data Analytics models to estimate performance based on other exogenous variables in order to allow the calculation of soil deficiencies by region.