Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity Analysis

Chemical batch process management, regardless of the level where its analysis is focused (such as pre-formulation and new process development, supply chain management, scheduling, process control, fault analysis, etc.) implies the collection and exploitation of huge amounts of data, which should be viewed as sources of information. Consequently, the information infrastructure which supports different activities by streamlining information gathering, data integration, model development and decision making is a crucial component towards process improvement/optimization. In this work it a Batch Process Ontology (BaPrOn) is presented, wherein different concepts regarding batch processes are categorized, and the relationships between them are examined and structured. Properties and relationships are introduced in agreement with ISA-88 standard, which provides a solid and transparent framework for integrating batch-related information.