In April I joined a team discussing “What is Systems Science?” at the International Federation for Systems Science biennial “conversation” in Linz, Austria. This was a fascinating experience, discussing how to move systems science from a diverse collection of really interesting ideas and practices to a structured and well-founded “science”. Our team leader was Gary Smith, who compared the current state of systems science to Alchemy, and the desired state to Chemistry. So he had an entertaining slide with the slogan “from Al-systemy to Systemry”. Other groups were working on old peoples’ health, using Beer’s Viable System Model as a template; the future of Model Based Systems Engineering, and model based engineering in general; and the use of systems science to support policy interventions.
I am now finishing off a chapter on “The Nature Of Engineered Systems” for the forthcoming Springer Handbook of Systems Science.
And one of my spare time activities is looking after the website for the Royal Forth Yacht Club. We have successfully transitioned from one web hosting service to another and are getting back to routine operation.
I’ve spent the last two years leading an INCOSE Fellows’ project to review and update the definitions INCOSE uses for “System” and “Systems Engineering”.
Key results of this were presented during the International Symposium in Washington DC in July 2018, and a couple of papers were also published last year, one at the International Symposium in Adelaide, and one in Systems Engineering Journal.
Copies of all of these papers can be viewed using the links below.
Our final recommendations will be out for review to INCOSE members shortly, and after any useful improvements from this review are incorporated, will be offered for formal adoption by INCOSE over the winter of 2018-19.
December 2017: I learnt that some copies of my book have been sold from Amazon.com with only 288 of the 394 pages – the back of the book is missing.
If this has affected you I can only apologise profusely!
If you bought a faulty copy, and not yet had it replaced by the reseller, please contact College Publications with details of your purchase, using the contact details here
They will arrange for a replacement hard copy to be sent to you, and also a free electronic copy.
For other customers, you can now buy the digital version direct from College Publications using the same link.
Monitoring of the technical progression of projects is highly difficult, especially for complex projects where the current state may be obscured by the use of traditional project metrics. Late detection of technical problems leads to high resolution costs and delayed delivery of projects. To counter this, we report on the development of a updated technical metrics process designed to help ensure the on-time delivery, to both cost and schedule, of high quality products by a U.K. Systems Engineering Company. Published best practice suggests the necessity of using planned parameter profiles crafted to support technical metrics; but these have proven difficult to create due to the variance in project types and noise within individual project systems. This paper presents research findings relevant to the creation of a model to help set valid planned parameter profiles for a diverse range of system engineering products; and in establishing how to help project users get meaningful use out of these planned parameter profiles. We present a solution using a System Dynamics (SD) model capable of generating suitable planned parameter profiles. The final validated and verified model overlays the idea of a learning “S-curve” abstraction onto a rework cycle system archetype. Once applied in SD this matched the mental models of experienced engineering managers within the company, and triangulates with validated empirical data from within the literature. This has delivered three key benefits in practice: the development of a heuristic for understanding the work flow within projects, as a result of the interaction between a project learning system and defect discovery; the ability to produce morphologically accurate performance baselines for metrics; and an approach for enabling teams to generate benefit from the model via the use of problem structuring methodology.
At the INCOSE International Symposium in Edinburgh last week, I was talking to Ron Carson, who like me is an ESEP, INCOSE Fellow, and just winding down at the end of a long and successful career in industry – Boeing in his case. I was delighted to learn that he is using my book for a Masters level Systems Engineering elective that he is delivering for the Industrial and Systems Engineering Department at the University of Washington in Seattle.
Then I heard from Michael Vinarcik, who decided to use my book after considering several other well known systems architecture textbooks, in his course MPD 5050 on Systems Architecture at UDM in Detroit.
Last week I participated in a panel at the INCOSE International Symposium in Edinburgh. We got great feedback from the panel – Mike Wilkinson, who chaired the panel, had quite a few positive comments from the audience, including one person who said it was “brilliant – the best panel session I have attended”.
Mike put a lot of pressure on us to get down to a single slide. So I thought hard about what I’d said in my position paper, and condensed it into the following graphic. Several people said they found it really interesting and useful, so here it is. The notion is that architecture is on the one hand a bridge between value and feasibility, and on the other between systems science and systems engineering. The architect tries to deal as much as possible in “patterns”, abstracted conceptual arrangements known to occur in certain domains and/or to provide solutions for certain classes of problem.