Optimisation of large concrete DfMA structures for the Nuclear Industry

Lead Research Organisation: Imperial College London
Department Name: Civil & Environmental Engineering

Abstract

The overall aim of the project proposed is to optimise the design for manufacture and assembly (DfMA) of large
preassembled components for reinforced concrete construction in nuclear and other large construction projects. To bring
these benefits and capability to the UK nuclear construction supply chain, and to establish a world-leading capability, the
project will verify the reliability of preassembled structural components currently available in the UK and develop new ones
that meet the stringent design and assembly requirements of the nuclear environment. The project team includes Laing
O'Rourke (a current nuclear new build constructor), Imperial College London (expertise in optimisation, logistics and
intelligent transport systems), ARUP (expertise in the design of new nuclear power plants) and BRE (capability of testing
prototype designs).
The project will explore the potential of a number of construction approaches, consisting of a range of elemental sizes and
jointing techniques, for both sub- and super-structure applications in nuclear construction. Key considerations for research
are the structural performance of such systems and joints, their reliability, and innovation with regards to associated
manufacturing and assembly techniques. Therefore, the project consists of six main sub-projects as follows:
1) Design of large underground components,
2) Design of large superstructure components,
3) Joint small scale reliability,
4) Reliability assessment of systems,
5) Optimisation and automation of manufacturing techniques and
6) Optimisation and automation of assembly techniques.
The Department of Civil & Environmental Engineering at Imperial College London will lead research in the optimisation and
automation of assembly techniques. The use of preassembled components in nuclear construction presents a significant
opportunity to apply this expertise in the construction sector. The combination of these technologies will allow the industry
to rethink and streamline the entire design and assembly process in nuclear plant construction and beyond.
The aim of the research carried out at Imperial will be to address the difficulties in handling larger-than-usual construction
components as well as taking advantage of their prefabricated nature. The three key quantities to be determined will be the
number, size and location of tower cranes to be used in the construction process, with each combination having direct
consequences on the overall layout of the construction site and the rate at which the assembly process is accomplished.
As the scale of preassembled components that will be considered can vary significantly (with weights between 20 and
1000t) a variety of scenarios will be considered.
The optimisation models and solution approaches to be developed will seek to balance overall transport and handling costs
against the speed of construction, while ensuring that safety and other operational constraints are satisfied. The models
and solutions will be tested through the use of simulation informed with real data and provide feedback to the parties
responsible for the design of the components used, in an iterative approach that will ensure that the overall design and
construction process will be able to extract the maximum benefit from the use of preassembly.

Planned Impact

The research to be carried out by Imperial College London is significant as it will focus on the optimisation of assembly
operations, a critical aspect of the entire Design for Manufacture and Assembly (DfMA) approach. The UK Government has
identified eight potential sites for the redevelopment of the UK civil nuclear power sector, with plans for 16 GW of nuclear
generation capacity to be developed by 2025. With estimated construction costs for a nuclear station approaching £2
billion, the overall potential size of the nuclear power plant construction market in the UK is expected to be around £16
billion between 2014 and 2025. A recent report on the New Nuclear Build (NNB) Employment Scenarios by construction
skills shows a potential peak at £3bn per annum. There is currently increased pressure to reduce construction costs by
approximately 10% through higher efficiency levels. The expectation is that this should translate to savings for UK energy
consumers.
1. The use of DfMA aims to enable 70% of manufacturing activities to take place through off-site fabrication and onsite
assembly, with a 60% reduction in on-site labour. As a result, it is estimated that the addressable market opportunity
through the use of DfMA on a single power station is approximately £540-800m, rising to a potential £6bn over all 8
planned power stations. As a result, the return on investment for the entire research project will be significant in terms of
productivity benefits even in the case of a single site. DfMA techniques developed in this project would also be applicable
and adaptable to the wider civil infrastructure market that has in the UK a total estimated value of £15.3 billion.
2. As efficiency levels increase in the construction process, the use of DfMA would have immediate environmental impacts,
as a result of less emissions, water consumption, waste and noise. This would further decrease the disruption to areas
surrounding nuclear construction sites that would already benefit from enhanced construction speeds.
3. The overall project will produce evidence on the performance of prefabricated components both during construction and
in the ultimate permanent state of assembly. These will be obtained through design analysis and physical testing of large
sample pieces. The results will be conveyed to the relevant authorities, to pave the way for regulatory sanctioning of DfMA
practices in the nuclear construction sector and therefore providing the opportunity to realise the economic benefits quoted
above.
4. Beyond the impacts for the research community as discussed in the "Academic Beneficiaries" section, the project would
bring immediate benefits to the other industrial collaborators involved. Laing O' Rourke and ARUP will have the opportunity
to apply the methods developed to other construction and engineering advisory activities services in UK, with further
opportunities in their endeavours abroad. Finally, BRE will expand its capability in the nuclear and heavy engineering
sectors. The expertise developed will be transferable to other companies in the UK, either through IP licensing, training or
consulting services, or in the form of knowledge disseminated through workshops and publicised material.
5. The worldwide market for nuclear power generation technology concerns (as of October 2010) about 441 plants
operating worldwide with generating capacity of 375GW. It has become clear over the last 5 years that many more
countries see nuclear power generation as a vital part of their energy mix. As UK commences an intensive nuclear
construction programme, many of these countries are likely to be assessing the techniques and construction practices used
for implementation in their own projects.

Publications

10 25 50
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Angeloudis P (2016) Strategic maritime container service design in oligopolistic markets in Transportation Research Part B: Methodological

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Anvari B (2016) Calibration and Validation of a Shared Space Model: Case Study in Transportation Research Record: Journal of the Transportation Research Board

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Briskorn D (2016) Scheduling co-operating stacking cranes with predetermined container sequences in Discrete Applied Mathematics

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Hsu P (2020) Understanding and visualizing schedule deviations in construction projects using fault tree analysis in Engineering, Construction and Architectural Management

publication icon
Hsu P (2019) Risk-averse supply chain for modular construction projects in Automation in Construction

 
Description The main output of this project during the current reporting period has been a novel optimisation tool that is capable of optimising construction workflows for large-scale projects that make use of Design for Manufacturing and Assembly (DfMA) techniques. It makes use of Genetic Algorithm (GA) optimisation techniques and is capable of producing highly detailed construction timelines.

The methodology developed can evaluate the impact of consequential decisions taking place within the manufacturing, transportation and assembly stages of construction projects that make use of DfMA principles. the main objectives are to minimize makespan and cost while maximizing safety, which is included in this tool. Safety is maximized by minimizing the number of on-site workers on congested construction sites. Using the multi-objective GA-based optimization model implemented in this tool, optimal solutions for different levels of prefabrication can be determined and compared with respect to overall time and cost.
Exploitation Route The lead industrial partner in this project used the findings of this study to carry out an assessment of the effectiveness of currently used project planning practices, as used in large-scale construction projects. Opportunities for improvement through the use of software automation were identified - the algorithm developed as part of this project would be able to reduce project planning workload by 80%, and deliver more efficient component manufacturing timelines.
Sectors Construction,Manufacturing, including Industrial Biotechology,Transport

 
Description A new optimization technique has been developed in order to optimize the manufacturing and deployment of components in modern large scale construction projects. The outputs of this research have been acknowledged in the plans for the construction of a new nuclear power plant (Hinckley Point). More specifically, the scheduling algorithms will help determine the optimal size and dimensions of the prefabricated components to be used in construction. The overall objective is to reduce the construction period of the entire project, while maintaining stringent safety standards (with respect to assembly processes and structural design codes) and keeping costs to a minimum.
First Year Of Impact 2014
Sector Construction,Energy,Manufacturing, including Industrial Biotechology,Transport
Impact Types Economic

 
Title Supply Chain Network Optimisation for Construction Logistics 
Description An optimisation framework that can capture the demand for logistics services in construction, and deliver optimised delivery strategies (including service frequency, depot location and parameters) 
Type Of Material Improvements to research infrastructure 
Year Produced 2016 
Provided To Others? Yes  
Impact Translation of recently developed algorithms for supply chain network optimisation for industrial uses - the algorithms were deployed in case studies with Laing O'Rourke. 
 
Description Collaboration with TSB Project (Nuclear DfMA) project members 
Organisation Arup Group
Country United Kingdom 
Sector Private 
PI Contribution Collaborative research and joint development of DfMA-oriented construction workflow optimisation algorithms.
Collaborator Contribution Our industrial partners have provided intellectual contributions - training of research staff, data and practical advice that collectively ensured that our research outputs remain relevant to industrial operational requirements. Imperial has developed a Multi-objective Optimisation Tool for Performing Prefabrication with the following objectives: 1-Minimizing project's target cost and time while maximising safety in a holistic Manufacturing, transportation and Assembly (MtA) system 2-Modelling the MtA system as a Resource-constrained Complex Flexible Job Shop Scheduling (RCFJSS) 3-Evaluating the developed algorithm and simulating different precast construction strategies using real MtA scenarios
Impact 1- Imperial have given a presentation titled "Analysis of Prefabricated Urban Housing Constructions on Freight Transport Systems" at the Institute for Operations Research and the Management Sciences (INFORMS) Conference on November 11th 2014 (accepted) Abstract: Prefabricated buildings have become the choice of many construction teams as they offer benefits such as shortened construction time, effective pricing, improved safety, reduced defects, improved quality and environmental benefits compared to traditional on-site construction. We explore the effects of prefabricated urban constructions on freight transport systems and identify cost-efficient logistics strategies. Our results will be beneficial for the Construction Method Selection Model which advises to what extent building components should be prefabricated. 2- Imperial have given a presentation titled "Multi-Objective GA-based Optimisation for Manufacturing, Transportation and Assembly of Precast Construction" at 17th British-French-German Conference on Optimisation on June 17th 2015 (accepted) Abstract: Precast production is an enhanced method to utilize construction schedule, cost, workforce, safety and quality. Making production schedules which satisfy multiple objectives is the most important part of precast construction planning. The Manufacturing, transportation and Assembly (MtA) sectors are often strongly linked to each other in construction projects. These sectors require a considerable amount of time, workforce and budget. In addition, the available resources for each sector have specific constraints. The difficulty is due mainly to the high number of constraints in the real-world application. It is important to evaluate the impact of consequential decisions from the manufacturing up to assembly in minimising project\'s time and cost while maximizing safety. Reducing the number of on-site workforce from congested construction site maximises the safety, and prefabricating components in a controlled and protected environment maximises the quality of the elements. In this paper, a Resource-constrained Complex Flexible Job Shop Scheduling (RCFJSS) optimisation approach is presented for minimising makespan and cost of precast techniques. At the same time, the number of on-site workers is minimised considering the holistic MtA system. A multi-objective Genetic Algorithm-based (GA-based) searching technique is used to provide optimal most advantageous solution in consideration of resource constraints. The output of this RCFJSS model provides an optimal allocation of resources on operations for the overall project duration, cost and on-site labour. Using this optimisation model, optimal solutions for different levels of prefabrication can be determined and compared with respect to projects horizon and budget. 3- Imperial have presented their optimised algorithm to the Hinkley Point nuclear team, to display the benefits of genetic algorithms on project programming on July 13th 2015. 4- Imperial have submitted a paper titled ": A Multi-Objective GA-based Optimisation for Holistic Manufacturing, transportation and Assembly of Precast Construction" to Automation in Construction journal on July 29th 2015. This paper is under second revision. Abstract: Prefabrication is an enhanced method to utilise construction schedule, cost, workforce, safety and quality. In this type of construction, components are manufactured and (sub-)assembled in a factory or warehouse, before being delivered to a construction site for installation. Resource scheduling is a temporary execution plan of a prefabricated construction proposal which allows for assessing resource requirements, providing cost and delay analysis. During the scheduling phase, potential problems might be highlighted before they arise. Satisfying multiple objectives (such as time, costs, workforce) is a crucial part of prefabricated construction planning. The Manufacturing, transportation and Assembly (MtA) sectors are often strongly linked to each other in construction projects requiring a considerable amount of time, workforce and budget. In addition, the available resources for each sector have defined constraints. It is important to evaluate the impact of consequential decisions from the manufacturing up to assembly by minimising project's time and cost while maximising safety. Reducing the number of on-site workforce from congested construction site improves safety, and prefabricating components in a controlled and protected environment enhances the quality of the elements. In this paper, a multi-objective Genetic Algorithm-based (GA-based) searching technique is proposed to solve a unified MtA resource scheduling problem. To the best of the authors' knowledge, this is the first time that a GA-based optimisation approach has been applied to a holistic MtA problem. A unified MtA system is defined as a Resource-constrained Complex Flexible Job Shop Scheduling (RCFJSS) problem with the aim of minimising makespan and cost. At the same time, the number of on-site workforce at the same time is constrained. The proposed model allows using multiple combinations of recourses in parallel for processing an operation and considers the workload of the resources in the optimisation process. The proposed GA-based model is evaluated and compared with other exact and non-exact models using instances from the literature and instances inspired by real data from precast constructions. 5- Imperial's proposal for organising a full day workshop on "Integrated Process Planning and Scheduling for Industrialising Construction: Design, Manufacture and Assembly" got accepted at the 26th International Conference on Automated Planning and Scheduling (ICAPS 2016). This workshop will be organised in collaboration with the Knowledge Transfer Network (KTN) - Built Environment Community and Innovate UK on June 12-17, 2016 (London, United Kingdom). More information can be found here:http://icaps16.icaps-conference.org/ippspcp.html 6- Imperial have presented their optimised algorithm to the Hinkley Point nuclear team, to display the benefits of genetic algorithms on project programming on January 20th 2016.
Start Year 2013
 
Description Collaboration with TSB Project (Nuclear DfMA) project members 
Organisation Building Research Establishment
Country United Kingdom 
Sector Private 
PI Contribution Collaborative research and joint development of DfMA-oriented construction workflow optimisation algorithms.
Collaborator Contribution Our industrial partners have provided intellectual contributions - training of research staff, data and practical advice that collectively ensured that our research outputs remain relevant to industrial operational requirements. Imperial has developed a Multi-objective Optimisation Tool for Performing Prefabrication with the following objectives: 1-Minimizing project's target cost and time while maximising safety in a holistic Manufacturing, transportation and Assembly (MtA) system 2-Modelling the MtA system as a Resource-constrained Complex Flexible Job Shop Scheduling (RCFJSS) 3-Evaluating the developed algorithm and simulating different precast construction strategies using real MtA scenarios
Impact 1- Imperial have given a presentation titled "Analysis of Prefabricated Urban Housing Constructions on Freight Transport Systems" at the Institute for Operations Research and the Management Sciences (INFORMS) Conference on November 11th 2014 (accepted) Abstract: Prefabricated buildings have become the choice of many construction teams as they offer benefits such as shortened construction time, effective pricing, improved safety, reduced defects, improved quality and environmental benefits compared to traditional on-site construction. We explore the effects of prefabricated urban constructions on freight transport systems and identify cost-efficient logistics strategies. Our results will be beneficial for the Construction Method Selection Model which advises to what extent building components should be prefabricated. 2- Imperial have given a presentation titled "Multi-Objective GA-based Optimisation for Manufacturing, Transportation and Assembly of Precast Construction" at 17th British-French-German Conference on Optimisation on June 17th 2015 (accepted) Abstract: Precast production is an enhanced method to utilize construction schedule, cost, workforce, safety and quality. Making production schedules which satisfy multiple objectives is the most important part of precast construction planning. The Manufacturing, transportation and Assembly (MtA) sectors are often strongly linked to each other in construction projects. These sectors require a considerable amount of time, workforce and budget. In addition, the available resources for each sector have specific constraints. The difficulty is due mainly to the high number of constraints in the real-world application. It is important to evaluate the impact of consequential decisions from the manufacturing up to assembly in minimising project\'s time and cost while maximizing safety. Reducing the number of on-site workforce from congested construction site maximises the safety, and prefabricating components in a controlled and protected environment maximises the quality of the elements. In this paper, a Resource-constrained Complex Flexible Job Shop Scheduling (RCFJSS) optimisation approach is presented for minimising makespan and cost of precast techniques. At the same time, the number of on-site workers is minimised considering the holistic MtA system. A multi-objective Genetic Algorithm-based (GA-based) searching technique is used to provide optimal most advantageous solution in consideration of resource constraints. The output of this RCFJSS model provides an optimal allocation of resources on operations for the overall project duration, cost and on-site labour. Using this optimisation model, optimal solutions for different levels of prefabrication can be determined and compared with respect to projects horizon and budget. 3- Imperial have presented their optimised algorithm to the Hinkley Point nuclear team, to display the benefits of genetic algorithms on project programming on July 13th 2015. 4- Imperial have submitted a paper titled ": A Multi-Objective GA-based Optimisation for Holistic Manufacturing, transportation and Assembly of Precast Construction" to Automation in Construction journal on July 29th 2015. This paper is under second revision. Abstract: Prefabrication is an enhanced method to utilise construction schedule, cost, workforce, safety and quality. In this type of construction, components are manufactured and (sub-)assembled in a factory or warehouse, before being delivered to a construction site for installation. Resource scheduling is a temporary execution plan of a prefabricated construction proposal which allows for assessing resource requirements, providing cost and delay analysis. During the scheduling phase, potential problems might be highlighted before they arise. Satisfying multiple objectives (such as time, costs, workforce) is a crucial part of prefabricated construction planning. The Manufacturing, transportation and Assembly (MtA) sectors are often strongly linked to each other in construction projects requiring a considerable amount of time, workforce and budget. In addition, the available resources for each sector have defined constraints. It is important to evaluate the impact of consequential decisions from the manufacturing up to assembly by minimising project's time and cost while maximising safety. Reducing the number of on-site workforce from congested construction site improves safety, and prefabricating components in a controlled and protected environment enhances the quality of the elements. In this paper, a multi-objective Genetic Algorithm-based (GA-based) searching technique is proposed to solve a unified MtA resource scheduling problem. To the best of the authors' knowledge, this is the first time that a GA-based optimisation approach has been applied to a holistic MtA problem. A unified MtA system is defined as a Resource-constrained Complex Flexible Job Shop Scheduling (RCFJSS) problem with the aim of minimising makespan and cost. At the same time, the number of on-site workforce at the same time is constrained. The proposed model allows using multiple combinations of recourses in parallel for processing an operation and considers the workload of the resources in the optimisation process. The proposed GA-based model is evaluated and compared with other exact and non-exact models using instances from the literature and instances inspired by real data from precast constructions. 5- Imperial's proposal for organising a full day workshop on "Integrated Process Planning and Scheduling for Industrialising Construction: Design, Manufacture and Assembly" got accepted at the 26th International Conference on Automated Planning and Scheduling (ICAPS 2016). This workshop will be organised in collaboration with the Knowledge Transfer Network (KTN) - Built Environment Community and Innovate UK on June 12-17, 2016 (London, United Kingdom). More information can be found here:http://icaps16.icaps-conference.org/ippspcp.html 6- Imperial have presented their optimised algorithm to the Hinkley Point nuclear team, to display the benefits of genetic algorithms on project programming on January 20th 2016.
Start Year 2013
 
Description Collaboration with TSB Project (Nuclear DfMA) project members 
Organisation Laing O'Rourke
Country United Kingdom 
Sector Private 
PI Contribution Collaborative research and joint development of DfMA-oriented construction workflow optimisation algorithms.
Collaborator Contribution Our industrial partners have provided intellectual contributions - training of research staff, data and practical advice that collectively ensured that our research outputs remain relevant to industrial operational requirements. Imperial has developed a Multi-objective Optimisation Tool for Performing Prefabrication with the following objectives: 1-Minimizing project's target cost and time while maximising safety in a holistic Manufacturing, transportation and Assembly (MtA) system 2-Modelling the MtA system as a Resource-constrained Complex Flexible Job Shop Scheduling (RCFJSS) 3-Evaluating the developed algorithm and simulating different precast construction strategies using real MtA scenarios
Impact 1- Imperial have given a presentation titled "Analysis of Prefabricated Urban Housing Constructions on Freight Transport Systems" at the Institute for Operations Research and the Management Sciences (INFORMS) Conference on November 11th 2014 (accepted) Abstract: Prefabricated buildings have become the choice of many construction teams as they offer benefits such as shortened construction time, effective pricing, improved safety, reduced defects, improved quality and environmental benefits compared to traditional on-site construction. We explore the effects of prefabricated urban constructions on freight transport systems and identify cost-efficient logistics strategies. Our results will be beneficial for the Construction Method Selection Model which advises to what extent building components should be prefabricated. 2- Imperial have given a presentation titled "Multi-Objective GA-based Optimisation for Manufacturing, Transportation and Assembly of Precast Construction" at 17th British-French-German Conference on Optimisation on June 17th 2015 (accepted) Abstract: Precast production is an enhanced method to utilize construction schedule, cost, workforce, safety and quality. Making production schedules which satisfy multiple objectives is the most important part of precast construction planning. The Manufacturing, transportation and Assembly (MtA) sectors are often strongly linked to each other in construction projects. These sectors require a considerable amount of time, workforce and budget. In addition, the available resources for each sector have specific constraints. The difficulty is due mainly to the high number of constraints in the real-world application. It is important to evaluate the impact of consequential decisions from the manufacturing up to assembly in minimising project\'s time and cost while maximizing safety. Reducing the number of on-site workforce from congested construction site maximises the safety, and prefabricating components in a controlled and protected environment maximises the quality of the elements. In this paper, a Resource-constrained Complex Flexible Job Shop Scheduling (RCFJSS) optimisation approach is presented for minimising makespan and cost of precast techniques. At the same time, the number of on-site workers is minimised considering the holistic MtA system. A multi-objective Genetic Algorithm-based (GA-based) searching technique is used to provide optimal most advantageous solution in consideration of resource constraints. The output of this RCFJSS model provides an optimal allocation of resources on operations for the overall project duration, cost and on-site labour. Using this optimisation model, optimal solutions for different levels of prefabrication can be determined and compared with respect to projects horizon and budget. 3- Imperial have presented their optimised algorithm to the Hinkley Point nuclear team, to display the benefits of genetic algorithms on project programming on July 13th 2015. 4- Imperial have submitted a paper titled ": A Multi-Objective GA-based Optimisation for Holistic Manufacturing, transportation and Assembly of Precast Construction" to Automation in Construction journal on July 29th 2015. This paper is under second revision. Abstract: Prefabrication is an enhanced method to utilise construction schedule, cost, workforce, safety and quality. In this type of construction, components are manufactured and (sub-)assembled in a factory or warehouse, before being delivered to a construction site for installation. Resource scheduling is a temporary execution plan of a prefabricated construction proposal which allows for assessing resource requirements, providing cost and delay analysis. During the scheduling phase, potential problems might be highlighted before they arise. Satisfying multiple objectives (such as time, costs, workforce) is a crucial part of prefabricated construction planning. The Manufacturing, transportation and Assembly (MtA) sectors are often strongly linked to each other in construction projects requiring a considerable amount of time, workforce and budget. In addition, the available resources for each sector have defined constraints. It is important to evaluate the impact of consequential decisions from the manufacturing up to assembly by minimising project's time and cost while maximising safety. Reducing the number of on-site workforce from congested construction site improves safety, and prefabricating components in a controlled and protected environment enhances the quality of the elements. In this paper, a multi-objective Genetic Algorithm-based (GA-based) searching technique is proposed to solve a unified MtA resource scheduling problem. To the best of the authors' knowledge, this is the first time that a GA-based optimisation approach has been applied to a holistic MtA problem. A unified MtA system is defined as a Resource-constrained Complex Flexible Job Shop Scheduling (RCFJSS) problem with the aim of minimising makespan and cost. At the same time, the number of on-site workforce at the same time is constrained. The proposed model allows using multiple combinations of recourses in parallel for processing an operation and considers the workload of the resources in the optimisation process. The proposed GA-based model is evaluated and compared with other exact and non-exact models using instances from the literature and instances inspired by real data from precast constructions. 5- Imperial's proposal for organising a full day workshop on "Integrated Process Planning and Scheduling for Industrialising Construction: Design, Manufacture and Assembly" got accepted at the 26th International Conference on Automated Planning and Scheduling (ICAPS 2016). This workshop will be organised in collaboration with the Knowledge Transfer Network (KTN) - Built Environment Community and Innovate UK on June 12-17, 2016 (London, United Kingdom). More information can be found here:http://icaps16.icaps-conference.org/ippspcp.html 6- Imperial have presented their optimised algorithm to the Hinkley Point nuclear team, to display the benefits of genetic algorithms on project programming on January 20th 2016.
Start Year 2013
 
Title DfMA Construction Workflow Optimization Tool (DfMA Decision Making Tool) 
Description This relates to an optimisation tool that is capable of optimise construction workflows for large-scale projects that make use of Design for Manufacturing and Assembly (DfMA) techniques. It makes use of Genetic Algorithm (GA) optimisation techniques and is capable of producing highly detailed construction timelines. DfMA is a simultaneous design and engineering approach where construction components are manufactured and assembled in a controlled factory environment, prior to delivery to a construction site for installation. Precast construction is known as an enhanced method to utilize construction schedule, cost, workforce, safety and quality. DfMA techniques have a significant positive impact on safety, quality and efficiency at every stage of the project. However, prefabrication is not always a better choice than on-site construction methods. For instance, considerable cost overruns and project management issues have each been associated with prefabrication from the manufacturing up to the assembly. The decision on whether or not to prefabricate a building or parts of a building, however, is currently often based more on subjective evidence rather than a thorough analysis of consequential decisions. The available decision making tools either do not cover complete performance attributes while evaluating different construction methods or they do not consider a compromised optimal solution for the overall problem before comparing various construction techniques. Hence, an optimization decision support tool that integrates smaller sub-problems in Manufacturing, Transportation and Assembly (MTA) sectors is developed. Therefore, the individual sub-problems are modelled, combined and optimized according to the overall main objectives of a project. As a result, the optimal solution for different construction techniques can be compared by decision makers before suggesting a recommendation (e.g. Conventional or prefabricated) with an associated level of confidence. In this decision making tool, the holistic MTA system is modelled as a Resource-constrained Complex Flexible Job Shop Scheduling problem with the aim of minimizing the total completion time, cost and the number of on-site workers. A multi-objective GA-based optimization is applied to find a near optimal solution for different construction techniques. This multi-objective GA-based optimization model is developed using the C# programming language with a user-friendly GUI which provides the possibility of defining different levels of prefabrication scenarios. 
Type Of Technology Software 
Year Produced 2014 
Impact This has been one of the first tools of this kind - we have received positive feedback our industrial partners, who are very likely to seek adoption upon the completion of this project. This DfMA Decision Making Tool evaluates the impact of consequential decisions from the manufacturing up to assembly in a multi-objective DfMA project. In DfMA projects, the main objectives are to minimize makespan and cost while maximizing safety, which is included in this tool. Safety is maximized by minimizing the number of on-site workers on congested construction sites. Using the multi-objective GA-based optimization model implemented in this tool, optimal solutions for different levels of prefabrication can be determined and compared with respect to overall time and cost. 
URL http://www.sciencedirect.com/science/article/pii/S0926580516301558
 
Description Publications to Trade Journals 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Media (as a channel to the public)
Results and Impact A series of articles were prepared to disseminate the outputs of our research, which were later published in trade journals (focusing on the Civil Engineering and Construction sectors)
Year(s) Of Engagement Activity 2016
URL https://www.railengineer.uk/2016/06/03/digitally-enabling-electrification/
 
Description Workshop on DfMA 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact One-day workshop organised at Imperial College London, where project participants presented their outputs. Other contributions were included in the workshop programme, involving external academics and industry participants with activities in this field.
Year(s) Of Engagement Activity 2006
URL http://www3.imperial.ac.uk/newsandeventspggrp/imperialcollege/engineering/cts/eventssummary/event_21...