Simultaneous Targeting and Scheduling for Batch Water Networks

Jui Yuan Lee, Dominic Chwan Yee Foo

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


Batch processes have received considerable attention from both industry and academia because of their flexibility and suitability to produce low volume, high value-added products (e.g., fine/specialty chemicals) and also as a result of the recent trend toward product-centered manufacturing globally. This paper presents an optimization technique for water network synthesis in batch processing plants. The mathematical formulation is a mixed integer linear program (MILP) based on the pinch-based automated targeting model (ATM) and a state-task network (STN)-based discrete-time scheduling model. Embedding the ATM in the scheduling framework enables simultaneous process scheduling and water minimization and the true minimum flow/cost targeting prior to detailed water network design. Two modified literature examples and an industrial case study on polyvinyl chloride (PVC) manufacturing are solved to demonstrate the application of the proposed MILP model. Results for the PVC case study show that significant water (50-56%) and cost savings (61-67%) can be achieved through optimal production scheduling and water recovery.

Original languageEnglish
Pages (from-to)1559-1569
Number of pages11
JournalIndustrial and Engineering Chemistry Research
Issue number6
Publication statusPublished - 2017 Feb 15

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • General Chemical Engineering
  • Industrial and Manufacturing Engineering


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