eprintid: 753
rev_number: 6
eprint_status: archive
userid: 17
dir: disk0/00/00/07/53
datestamp: 2019-05-11 14:02:32
lastmod: 2019-05-11 14:02:32
status_changed: 2019-05-11 14:02:32
type: report
metadata_visibility: show
creators_name: Murphy, E.
creators_name: Champneys, A.
creators_name: Batarfi, Hanan
creators_name: Barter, Edmund
creators_name: Budd, Chris
creators_name: Dong, Ran
creators_name: Foniok, Jan
creators_name: Kulesza, Kamil
creators_name: Lacey, Andrew
creators_name: Li, Xiaodong
creators_name: Rodrigues, Francisco
creators_name: Wendland, Alex
creators_name: Yim, Ambrose
corp_creators: David Myers
title: Workflow Modelling of Construction Projects
ispublished: pub
subjects: machines
studygroups: ESGI138
companyname: Heathrow
full_text_status: public
abstract: This report details the work carried out by the Study Group on workflow modelling of con- struction projects.
Data on the progress of about a hundred projects over a single five-year planning period were provided by Heathrow Airport (the client) and their four Tier 1 construction contrac- tors. These data are mapped and analysed. Several unusual features are discovered. For example, most projects undergo several tens of adjustments in their scope and price such that while most projects are technically completed under budget, the price and duration is significantly higher than originally planned.
The main question addressed was whether an optimised scheduling of the project would lead to decreased costs and more rapid completion.
First, a machine learning approach is used to gain insight onto which factors are most significant in predicting the final cost and duration of each project. If more data were available, these methods could be further exploited to allow for predictions to be made on which projects are likely to over-run or go over budget and to examine connections between projects at the subcontractor level.
In addition to the data-centric approach, a complementary mathematical model was de- veloped to gain a better understanding of the effect of resource constraints on cost and price extension due to resource competition of concurrent projects, ignoring the confound- ing effect of scope creep seen in the data. The model takes the form of a discrete time stochastic simulation, whose parameters are fit to the existing data. Tentative conclusions from the model indicate that better outcomes can be achieved by spreading out project start dates, and by prioritising completion of smaller projects.
While more data is needed to validate the model, the results suggested that gains can be made if more thoughtful scheduling of projects is implemented, and also if the prioritisation of projects is monitored and adjusted intelligently.
Our major recommendation to Heathrow Airport is to collect or retrieve more data, as outlined in the report, so that both models can be made more realistic and useful. This would allow Heathrow Airport and their contractors to develop and test strategies to make the system more efficient, ultimately saving time and money.
problem_statement: Heathrow Airport commission about £1B worth of construction projects per annum. This work is split into approximately 100 separate projects per year, 80% of which are at the <£1M level. Within a framework agreement, each project is awarded to one of four preferred main contractors, with each contractor being responsible for a separate physical region of the airport. These projects are typically planned and approved during a fixed 5-year planning window, mostly independently of each other. This process therefore tends to lead to sub-optimal deployment of the resources available to each contractor. As with most construction projects, the complexities of planning and financing each project tend to lead to an approach where everything is scheduled to be delivered as soon as possible once the go-ahead is granted. This is unlike manufacturing sectors (such as automotive) in which planning is done from the back to keep factories as close to capacity at all times.
The key question is whether workflow modelling, such as would be used in bulk manufac- turing, could lead to a more optimal result. The things to be optimised include costs, both to the client (the airport) and the supplier (the contractor). Other factors to be optimised include quality of delivered projects and minimisation of over-runs to enable robust plan- ning. An optimal solution would take into account the benefits of even employment levels for the contractors and their supply chain, and minimisation of frustration among the airport’s users (the airlines and their passengers).
date: 2018
citation:   Murphy, E. and Champneys, A. and Batarfi, Hanan and Barter, Edmund and Budd, Chris and Dong, Ran and Foniok, Jan and Kulesza, Kamil and Lacey, Andrew and Li, Xiaodong and Rodrigues, Francisco and Wendland, Alex and Yim, Ambrose  (2018) Workflow Modelling of Construction Projects.  [Study Group Report]     
document_url: http://miis.maths.ox.ac.uk/miis/753/1/esgi-heathrow.pdf