D is for Design

Rather than being some exotic province of polo-necked professionals, the ability to design is a natural human ability. Designers imagine an improvement on reality as it is, we think of a number of ways we might achieve the improvement, we select one of them, and we transmit our intention to those who are to realize our plan. The documents with which we transmit our intentions are, however, just a means to the ultimate end of design - the improvement on reality itself.

I discuss in my books a rather specialized version of this ability, but we should not lose sight of the fact that design is in essence the same process, whether we are designing a process plant, a vacuum cleaner, or a wedding cake.

Designers take a real-world problem which someone is willing to expend resources to resolve. They imagine solutions to that problem, choose one of those solutions based on some set of criteria, and provide a description of the solution to the craftsmen who will realize it. If they miss this last stage and if the design is not realized, they will never know whether it would have worked as they had hoped.

All designers need to consider the resource implications of their choices, the likelihood that their solution will be fit for the purpose for which it is intended, and whether it will be safe even if it not used exactly as intended.

If engineers bring a little more rigor to their decision making than cake designers, it is because an engineer’s design choices can have life and death implications, and almost always involve very large financial commitments.

So how does engineering design differ from other kinds of design?

“Engineering problems are under-defined, there are many solutions, good, bad and indifferent. The art is to arrive at a good solution. This is a creative activity, involving imagination, intuition and deliberate choice.”

- Ove Arup

Like all designers, design engineers have to dream up possible ways to solve problems and choose between them. Engineers differ from, say, fashion designers in that they have a wider variety of tools to help them choose between options.

Like all designers, the engineer's possible solutions will include approaches to similar or analogous problems which they have seen to work. One of the reasons why beginners are inferior to experts is their lack of qualitative knowledge of the many ways in which their kind of problems can be solved, and more important still, those ways which have been tried and found wanting.

Engineers need to make sure they are answering the right question. For example, a UK missile program called “Blue Streak” was a classic engineering failure because the problem was not correctly stated. It was designed to be a long range missile for nuclear warheads, but the missile had to be fuelled immediately before launch and it took 30 minutes to do this. Hence the missile was useless for the intended purpose, as it was not capable of sufficiently rapid deployment.

In “To Engineer is Human” Henry Petroski discusses the importance of avoiding failure in engineering design. Many of his examples of failure, however, were caused not by misspecification, but by designers who forgot that that the models used in design are only approximations, applicable in a fairly narrow range of circumstances.

Billy Vaughn Koen goes still further towards the truth, when he points out that “all is heuristic”. Even arithmetic is a heuristic. There are no absolute truths in mathematics, science or engineering. There are only approximations, probabilities and workable approaches. Engineers may just be a little clearer about these issues than mathematicians and scientists, because our solutions absolutely have to work.

In researching my books, I looked at what had been published in texts intended to describe a process plant design methodology. There were promising sounding books with titles like “The art of…”, “A strategy for...”, “Systematic methods for …”, “Design of simple and robust process plants” etc. I know that students and early stage designers lack an understanding of these things, as well as a gestalt of systems, but the overwhelming majority of these books failed to meet the promise of their titles.

Process plant design is an art, whose practitioners use science and mathematics, models and simulations, drawings and spreadsheets, but only to support their professional judgment. This judgment cannot be supplanted by these things, since people are smarter than computers (and probably always will be). Our imagination, mental imagery, intuition, analogies and metaphors, ability to negotiate and communicate with others, knowledge of custom and practice and of past disasters, personalities and experience are what designers bring to the table.

If more people understood the total nature of design they would see the futility of attempts to replace skilled professional designers with technicians who punch numbers into computers. Any problem a computer can solve isn't really a problem at all - the non-trivial problems of real-world design lie elsewhere.

Engineering problems will almost certainly always be far quicker to solve by asking an engineer, rather than by programming a computer, even if we had the data (which we can never have on a plant which hasn't yet been built), a computer smarter than a person, and a program which codes real engineering knowledge, instead of a simplified mathematical model with next to no input from professional designers.

I wonder how the medical profession would feel if scientists and mathematicians suggested, without consulting medics, that they could produce an expert system which would exceed the competence of doctors?

This is a classic academic purist's mistake: The psychologist claims that sociology is just applied psychology; the biologist says that psychology is just applied biology, the chemist that biology is just chemistry with legs, the physicist that chemistry is just applied physics, the mathematician that physics is applied mathematics, and the philosopher that mathematics is applied philosophy. Emergent properties are irrelevant to the theorist, but in practical matters they may be everything.

Donella Meadows explains, in “Thinking in Systems”, an intuitive system level view which is identical in many ways to the professional engineer’s view. We share this view with the kindergarteners who also excel at a design exercise called the marshmallow challenge which I used to use in my teaching. The roots of this system level view are natural human insights, which we may be educating out of our students.

Meadows explains that she makes great use of diagrams in her book because the systems she discusses, like drawings, happen all at once, and are connected in many directions simultaneously, whilst words can only come one at a time in linear logical order.

Process plant design is system level design, and drawings are its best expression - other than the plant itself - for the same reasons given by Meadows.

“Experimental scientists today, despite Einstein and Darwin, seem loath to abandon the search for an eternal changeless unhistorical reality of which pure mathematics could be the model.”

- Gordon Childe

An inward-looking school of “process design” as a form of applied mathematics has arisen in elite research institutions, whose practitioners collaborate only with their fellow researchers. They build upon each other's work, but their outputs are not used by, or indeed of use to, the profession.

Extending this philosophy to teaching programs, many universities have replaced essential professional knowledge with modules in which students learn to use researcher software so that, later in the course, they can carry out “process design” as these researchers do it.

Adherents of this school of thought argue that it is the job of industry to produce engineers, whilst academia’s job is to provide an education in applied mathematics. They would argue that, not only should we follow institutions such as Tokyo University in not teaching our students to read engineering drawings, they should not even spend much time learning about science.

The prevalence in academia of this approach based on modeling, simulation and mathematical techniques such as network analysis seems to some extent to be an artefact of the way research is funded. Research which takes place in a PC rather than a lab (or worse yet a pilot plant) is relatively cheap to conduct, and thus to fund.

It is of course a valid function of engineering research departments to develop new design methodologies. Some aspects of these approaches may have niche applications in professional practice, but the overwhelming majority will not be taken up by the profession, as they do not help the professional to achieve his aims.

It is inevitable that researchers will consider their work important, even vital, but if it is not of use to the profession, it is research material of academic interest only.