Ontology as key for formalizing engineering knowledge

“But logic itself has no vocabulary for describing the things that exist. Ontology fills that gap: it is the study of existence, of all kinds of entities — abstract and concrete — that make up the world. It supplied the predicates of predicate calculus and the labels that fill the boxes and circles of conceptual graphs”

Sowa – Knowledge Representation, Logical, Philosophical and Computational Foundations

I just wanted to share the above quote from what I often refer to as the bible of advanced engineering informatics or of anybody in any domain who tries to support domain specialists with computational methods.

In my personal thinking this quote is essential and it might be helpful to clearly understand the message my colleague Amy Trappey and I tried to make in our recent publication.

If you are working in the field and you can get your hands on a copy of Sowa … at least for me it was tremendously helpful to explicitly understand what I am working on in my research and teaching.

Design optimization: Searching for the Impact

Design optimization tools become readily available and easy to use (see for example Karamba or Dynamo. It is not surprising that studies exploring these tools are exploding. Many examples exist that illustrate how to design optimization models and execute optimizations. Often, however, these studies fail to provide the true impact that was expected in terms of improving the (simulated) performance of the engineering design. Showing that the deflection of a structure could be reduce by a centimeter or the material utilization used for the structure was reduced by some percent remains of course an academic exercise that can provide little evidence on the engineering impact of optimization technologies.

As we move forward in this field of research, we need to develop more studies that move away from simply showing the feasibility to apply relatively mature optimization methods towards formalizing optimization problems that matter. Finding such problems is not easy as we cannot truly estimate the outcomes of mathematical optimizations upfront. Whether a specific impact can be achieved can only be determined through experimentation – a long, labor extensive and hard process.

Even worse, identifying relevant optimization problems through a discussion with experts is difficult. The outcomes of each design optimization needs to be compared with the solution an expert designer would have developed using his intuition and a traditional design process. Hence, working with expert designers to identify problems might be tricky. After all they are experts and probably already can come up with pretty good solutions. It seems as one would rather need to identify problems that are less well understood, but still relevant. These problems might also be scarce as relevant problems are of course much more widely researched.

In the end, I think we need to set us up towards a humble and slow approach. An approach that is time consuming, that will require large scale cooperation, and needs to face many set-back in terms of providing an impact that truly matters. Maybe this is also the reason why a disruption of design practice is not yet visible. Until we will be able to truly understand how we can impact design practice with optimization we will still need to rely on human creativity and expertise for some time to come. (not saying that we should stop our efforts.

Reading about circular economy

While preparing for our new module ‘Circular economy for the Built Environment: Principles, Practices and Methods’ I was reading three papers today in an effort to select some required readings for our students.

I first read Ghisellini et al (2016) ‘A review on circular economy: the expected transition to a balanced interplay of environmental and economic systems‘. This is a very comprehensive review of a large amount of papers, however, the results from this review were a little inconclusive. In the end, the paper reiterates the different approaches taken in China and the EU, while China employs top-down planning and the EU bottom-up planning. The paper also stresses the need for good business models.

I then read chapter 18 ‘Products & Services’ from Lacy et al.’s book ‘The Circular Economy Handbook’. This chapter discussed possibilities to improve products during all stages of the product life-cycle from design, to use, to use extension, to end of use. I liked the inclusion of ‘use extension’ as a separate phase in the product life-cycle, certainly something we should do much more explicit. The chapter also again stressed the need for good business models, as well as, developing a sound understanding of the product portfolio of a company.

Finally I read Bocken et al. (2016) ‘Product design and business model strategies for a circular economy’. I truly enjoyed reading the paper as it introduced a strong framework about how to design products for slowing down the resource loop and for closing the resource loop. I thought these two goals are quite helpful concepts to think along when designing products. To slow loops, the authors suggest to design for attachment and trust, reliability and durability, ease of maintenance and repair, upgradability and adaptability, standardization and compatibility, as well as, dis- and reassembly. This reminded me at the classical idea of ‘ilities’ from de Weck. To close resource loops the authors suggested to design for a technological cycle that allows to reuse technical materials and sub-products, as well as, for a biological cycle. I found this again a powerful guide for designing products.