Process Engineering Overview

Principles

Definition

Process engineering is an applied science and engineering discipline concerned with the design, analysis, control, and optimization of processes involving the physical, chemical, or biological transformation of matter and energy. It investigates the fundamental principles governing these transformations and applies them systematically to develop and manage systems for efficient, safe, and sustainable production or function.

Ontological type

Core Principles

Process Design Methods

Control and Optimization

Key developments

Key Figures

Operability and Robust Design era

Ignacio E. Grossmann [1] is a leading figure in process systems engineering during the Operability and Robust Design era (1981-1995), with affiliations linked to Carnegie Mellon University [2] and the University of Maribor [3]. His 1985 paper titled An index for operational flexibility in chemical process design Part I: Formulation and theory [4] introduced an index for operational flexibility that quantifies formability and flexible operating spaces, a key contribution for the era because it provided a measurable target to embed operability and robustness into design. Grossmann [1] further showed how such quantitative indices could guide design decisions that expand safe operating envelopes and resilience in processes, aligning with the era's emphasis on online monitoring and energy-aware robustness. The work helped shape ongoing research at Carnegie Mellon University [2] and at the University of Maribor [3], reinforcing operability-driven design rules that informed plant architectures during this era.

Design-Driven Intensification era

Douglas C. Montgomery [1] is a foundational figure in design of experiments and process optimization during the Design-Driven Intensification era, with affiliations across Albert Einstein College of Medicine [3] and Cornell University [4] in this period. His key contributions include developing Response Surface Methodology and designed experiments, as detailed in Response Surface Methodology: Process and Product Optimization Using Designed Experiments [7], which provided a rigorous and reproducible framework for mapping process responses and guiding robust optimums. Raymond H. Myers [2] is a prominent figure associated with Virginia Tech [5] and the University of Wyoming [6] during this era. Alongside Montgomery, Myers helped disseminate the same influential RSM framework through the co-authored 1996 paper [7], promoting DOE workflows and model-based design that enabled systematic experiments and accelerated process intensification in the Design-Driven Intensification era.

Integrated Continuous Flow era

Steven V. Ley (Cambridge) anchored integrated flow chemistry by developing multi-step, telescoped sequences in continuous flow and embedding inline analytics to accelerate design-of-experiments and rapid optimization. Timothy F. Jamison (MIT) extended flow applications into photochemical and catalytic cascades, demonstrating model-driven optimization and data-enabled design-of-experiments that support predictive scale-up. Florian Glorius (University of Münster) championed safe, scalable microreactor platforms and plug-and-produce architectures, translating flow chemistry into modular manufacturing workflows with high-throughput analytics. K. Oliver Kappe (University of Graz) provided foundational methods for continuous-flow synthesis and inline analytics, underpinning early adoption of DoE/response-surface workflows and lifecycle-aware process optimization in the integrated-flow era.