Tag Archives: Engineering

Pareto principle in train travel

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The moral of this story is don’t travel with me.  Last week, I wrote about my train being delayed by someone pulling the emergency handle before we got to the end of the platform in Liverpool [see ‘Stopped in Lime Street’ on June 26th, 2019].  Four days later, I was once again on a late afternoon train to London waiting for it to leave Lime Street station.  This time we didn’t even get started before the train manager announced that a road vehicle had hit a bridge between Crewe and Liverpool; and, so we were being held in Liverpool for an unknown period of time.  I sent a message to my family telling them about the delay and one, an engineer, replied that I was ‘hitting the low frequency failure modes on the service quality pareto’.  The Pareto principle is also known as the 80/20 principle.  I first encountered it when I was working at the University of Sheffield and the Vice-Chancellor,  Professor Gareth Roberts, used it to describe the distribution of research output in academic departments, i.e., 80% of research was produced by 20% of the professors.  In service maintenance, it is assumed that 80% of service interruptions are caused by 20% of the possible failure modes.  Hence, if you can address the correct 20% of failure modes then you will prevent 80% of the service interruptions, which is an efficient use of your resources.  The remaining, unaddressed failure modes are likely to occur infrequently and, hence, can be described as low frequency modes; including passengers pulling emergency handles or people driving vehicles into bridges.

How do you drive into a bridge and block the main railway lines between London and the north-west of England?  Perhaps the driver was using their smart phone which was not smart enough to warn them of the impending collision with the bridge.  So, there’s a new product for someone to develop: a smartphone app that connects to dashboard camera in your vehicle and warns you of impending collisions, or better still just drives the vehicle for you.  Yes, I know some vehicles come with all of this installed but not everyone is driving the latest model; so, a retro-fit system should sell well and protect train passengers from unexpected delays caused by road vehicles damaging rail infrastructure.

By the way, the 14:47 to London magically became the 15:47 to London and left on time!

Meta-knowledge: knowledge about knowledge

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As engineers, we like to draw simple diagrams of the systems that we are attempting to analyse because most of us are pictorial problem-solvers and recording the key elements of a problem in a sketch helps us to identify the important issues and select an appropriate solution procedure [see ‘Meta-representational competence’ on May 13th, 2015].  Of course, these simple representations can be misleading if we omit parameters or features that dominate the behaviour of the system; so, there is considerable skill in idealising a system so that the analysis is tractable, i.e. can be solved.  Students find it especially difficult to acquire these skills [see ‘Learning problem-solving skills‘ on October 24th, 2018] and many appear to avoid drawing a meaningful sketch even when examinations marks are allocated to it [see ‘Depressed by exams‘ on January 31st, 2018].  Of course, in thermodynamics it is complicated by the entropy of the system being reduced when we omit parameters in order to idealise the system; because with fewer parameters to describe the system there are fewer microstates in which the system can exist and, hence according to Boltzmann, the entropy will be lower [see ‘Entropy on the brain‘ on November 29th, 2017].  Perhaps this is the inverse of realising that we understand less as we know more.  In other words, as our knowledge grows it reveals to us that there is more to know and understand than we can ever hope to comprehend [see ‘Expanding universe‘ on February 7th, 2018]. Is that the second law of thermodynamics at work again, creating more disorder to counter the small amount of order achieved in your brain?

Image: Sketch made during an example class

Archive video footage from EU projects

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This week I am in the US presenting work from our EU projects INSTRUCTIVE and MOTIVATE at the Annual Conference and Exposition of the Society for Experimental Mechanics.  Although the INSTRUCTIVE project was completed at the end of December 2018, the process of disseminating and exploiting the research will go on for some time.  The capability to identify the initiation of cracks when they are less than 1mm long and to track their propagation is a key piece of technology for DIMES project in which we are developing an integrated system for monitoring the condition of aircraft structures.  We are in the last twelve months of the MOTIVATE project and we have started producing video clips about the technology that is being developed.  So, if you missed my presentations at the conference in the US then you can watch the videos online using the links below 😉.

We have been making videos describing the outputs of our EU project for about 20 years; so, if you want to see some vintage footage of me twenty years younger then watch a video from the INDUCE project that was active from 1998 to 2001.

MOTIVATE videos: Introduction; Industrial calibration of DIC measurements using a calibration plate or using an LCD screen

The MOTIVATE project has received funding from the Clean Sky 2 Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 754660.

Image: Peppermill Hotel in Reno, Nevada where the conference is being held.

 

Laboratory classes thirty years on

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Henry Lea Laboratory, The University of Sheffield in the 1960s

I have happy memories of teaching laboratory classes at the University of Sheffield in the mid 1980s and 1990s in the Henry Lea Laboratory.  The laboratory was crammed full of equipment for experiments in mechanics of materials.  We conducted the practical classes on a limited selection of test machines that stood around a set of benches in the centre of the laboratory on which were a series of bench-top experiments for undergraduates.  The outer reaches of the laboratory were packed with test machines of various shapes and sizes that were the domain of the research students and staff.  So, undergraduate students were privileged to conduct their laboratory classes surrounded by research activity – this was one of the advantages of attending a research-intensive university to study engineering.  However, this is not the experience that modern students gain from laboratory classes.  Sheffield, like Liverpool, and many other research-intensive universities has purpose-built teaching laboratories that provide modern spacious facilities for teaching and learning but also segregate undergraduates from the research business of the university.  In the UK, the increase in student numbers, as we moved towards 50% participation in higher education, was probably a prime driver for the design and construction of these facilities.  However, often the growth in student numbers exceeds the planned capacity of the teaching laboratories and the student experience is reduced by being in a group of five or six with only one or two of them being able to get hands-on experience at the same time.  To overcome this problem, I have used practical exercises as homework assignments that can be performed in the kitchen at home by first year students.  These were initially designed for the MOOC on thermodynamics that I developed a few years ago but they work equally well for undergraduate students and allow individuals to gain experience of conducting a simple experiment, recording and processing data, and write a short report about their findings [see post on ‘Blending learning environments‘ on November 14th, 2018 and ‘Slow down time to think [about strain energy]‘ on March 8th, 2017].  I have found that the participation rate is about the same as for traditional laboratory classes but different because students can learn from their mistakes in private and acquire some experimental skills [1].  However, it is a long way from conducting labs for small cohorts in a laboratory where world-class research is in progress.

Reference:

1. Patterson EA, Using everyday examples to engage learners on a massive open online course, IJ Mechanical Engineering Education, doi: 10.1177/0306419018818551, 2018.