Product and Process Design

Driving Innovation

Jan Harmsen, André B. de Haan, Pieter L. J. Swinkels

• Publisher: De Gruyter
• Year: 2018
• ISBN:
  9783110467758
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Chemical & Biochemical Engineering
• Index: Technology & Engineering

Product and Process Design: Driving Innovation is a comprehensive textbook for students and industrial professionals. It treats the combined design of innovative products and their innovative manufacturing processes, providing specific methods for BSc, MSc, PDEng and PhD courses. Students, industrial innovators and managers are guided through all design steps in all innovation stages (discovery, concept, feasibility, development, detailed engineering, and implementation) to successfully obtain novel products and their novel processes.

The authors' decades of innovation experience in industry, as well as in teaching BSc, MSc, and post-academic product and process design courses, thereby including the latest design publications, culminate in this book.

Part C: Design optimization

9Process modeling and optimization

Synopsis

This chapter deals with modeling in support of three successive innovation stages of product. Linear process modeling is associated with applications in the concept stage. Nonlinear process modeling is linked with the feasibility and development stages. Process simulations will find applications in the development stage, while the feasibility stage benefits from optimization applications, which scout the entire design space and optimize over it. The modeling approach chosen here has a practical inclination. Many academic textbooks on modeling cover the common modeling steps, such as development of model equations, mathematical model analysis and numerical means for computing solutions. Therefore, these steps are largely skipped here. Instead the contextual and application sides of modeling in process engineering will get more attention. For instance, how does one get to a relevant model for a process engineering problem? Furthermore, how does one analyze and evaluate the outcomes from computational model applications and how are clues derived for process innovations? Aspects of sensitivity analysis, uncertainties and identification of technological constraints from model based solutions will also be discussed.

9.1Justification and objectives of process modeling

Modeling objectives for process synthesis, analysis and optimization

The purpose of process modeling and computing is to offer effective, quantitative means to synthesize, analyze and evaluate process designs. The main goal of this modeling and computing chapter is to bring out the conceptual aspects of modeling, simulation and optimization for process design applications. In view of limited text space this emphasis will go at the expense of the underlying mathematical and numerical aspects of model building and equation solving. Here we will simply assume that:

–Models will be properly formulated from mathematical and computational perspectives.

–Their domain of applicability (containing feasible physical solutions) is well understood.

–An applied numerical solution procedure is consistent with the model and sufficiently accurate.

The focus will be on the context and practice of developing model applications for the concept, feasibility and development stages in support of product and process designs; see also Chapter 4. Attention will also be given on how to extract relevant information from model applications for purpose of improvement and innovation. There is an established industrial practice of supporting process design case studies with commercial steady state process flow sheet simulators. This vast area of computer aided process simulations has been thoroughly covered in [1], and therefore will be skipped here. Dynamic modeling and model reductions for process control and operations are also omitted.

Further background reading on process modeling for simulation and optimization in process development, design and operations is offered in a number of high quality text books; regarding modeling [2–8]; flow sheeting simulations for design [1, 9–12] and optimization [13–15] and [16].

Conceptual representation of a process: network features

A process is an open system that internally consists of a network interconnected and interacting unit operations. The system is in interplay with its physical, economic and social surroundings. The system performs specified production functions; i.e., turning physical feeds into products with a chemical functionality. The production is guided by process and product control information. The system may operate in different modes over time. Each mode is characterized by a distinct internal state of the process.

A process is connected to its surroundings by:

–Feed, product and waste streams (the latter to waste treatment facilities).

–Control set points for its operational conditions and modes as supervised by plant operators.

–The environmental conditions.

–The cash flow it generates for the process owner.

The behavior and performance of a process is codetermined by the interactions between a process and its surroundings. This includes the imposed modes of operation. Each mode can be seen as the realization of an external scenario, under which the process must make product(s) while performing well enough. Development of scenarios is part of the design; these scenarios are used for testing candidate processes under design. Consequently, the set of process models must be able to handle all scenarios. This explains why next to steady state models also dynamic models are required.

Sharing a generic view on proces...

Table of contents

• Cover
• Title Page
• Copyright
• Preface
• Contents
• Authors’ biographies
• Part A: Innovation and industry
• Part B: Design generation
• Part C: Design optimization
• Part D: Education
• Index