IBM Cognitive Technology Helps Aqualia to Reduce Costs and Save Resources in Wastewater Treatment
| Autor: | Vladimir Lipets, Sergey Zeltyn, Alexander Zadorojniy, Segev Wasserkrug |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Engineering
021103 operations research Optimization problem Waste management business.industry Strategy and Management 05 social sciences 0211 other engineering and technologies Cloud computing 02 engineering and technology Management Science and Operations Research Front and back ends Work (electrical) Management of Technology and Innovation 0502 economics and business Production (economics) Sewage treatment Markov decision process IBM Process engineering business 050203 business & management |
| Zdroj: | Interfaces. 47:411-424 |
| ISSN: | 1526-551X 0092-2102 |
| DOI: | 10.1287/inte.2017.0907 |
| Popis: | This work addresses operational management optimization problems in wastewater treatment plants. We developed a novel technology that allows control of such plants, based on real-time sensor readings, with cloud computing at the front end and state-of-the-art operations research and data science algorithms at the back end. We used a constrained Markov decision process as the key optimization framework. We tested our technology in a one-year pilot at a plant in Lleida, Spain, operated by Aqualia, the world’s third-largest water company. The results showed a dramatic 13.5 percent general reduction in the plant’s electricity consumption, a 14 percent reduction in the amount of chemicals needed to remove phosphorus from the water, and a 17 percent reduction in sludge production. Moreover, results showed a significant improvement in total nitrogen removal, especially in low temperature conditions. |
| Databáze: | OpenAIRE |
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