Optimization Parallel Computing for a Pulp and Paper Company
Pulp and Paper
Dedicated R&D consulting to significantly reduce computation time through parallelization.
An American pulp and paper company. It is the 2nd largest paper manufacturer in the United States, with operations around the world and expertise in every paper category.
The company's rapid growth generated complex coordination issues between production planning and shipping logistics. Their custom-made planning software had difficulties handling the growing complexities of the operations. For example, the one-month production and shipping plan could take more than 48 hours to compute. Any change to the plan could take an additional 48 hours.
Reorganizing the solving process in a parallelized fashion.
To address these issues and reduce computation time, DecisionBrain proposed to restructure the planning system by leveraging parallelization techniques. In the Proof of Concept, the main problem was reorganized into three subproblems that would be solved in parallel and then recomposed. As a result, the 48 hour computation time was reduced between 30%-40%, maintaining the expected solution quality, allowing WestRock to add new customers within its existing system.
A successful PoC that addressed the overall objectives and KPI's.
By applying this parallelized methodology, the improvements were very positive. It significantly reduced the time that it takes a planner to produce a plan or to make changes to it, and maintained the overall quality of the solution, in terms of low production cost and short lead time. DecisionBrain is currently working on another project that will complement the parallelized solution.
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