J.P.G. Ramler
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16 records found
1
This thesis examines how inter-firm coordination at the DMI in wind turbine blade manufacturing can be strengthened to support reliable turbine scale-up under deployment pressure. Coordination mechanisms from mature industries are used as the analytical starting point to investigate how these mechanisms appear, differ or remain underdeveloped in the wind blade context. The study follows qualitative research design. Literature on design–manufacturing integration, coordination theory and inter-firm coordination mechanisms was reviewed to construct a reference framework. This framework guided semi-structured expert interviews with participants from OEM, manufacturing and hybrid roles. The interview material was analysed through directed qualitative content analysis and synthesized into Framework C, a refined framework for strengthening inter-firm DMI coordination in the wind blade context.
The findings show that several mechanisms used in mature industries are already visible in wind blade industrialization, especially in design finalization, launch and problem-solving stages. However, the coordination base is uneven. Upstream coordination remains weaker, with limited early manufacturing involvement, fragmented cross-enterprise coordination baselines and underdeveloped supplier development. Prototype and validation learning are also pressured by the need to commercialize larger turbines quickly. Shop-floor capability emerged as a strengthening direction specific to wind blade manufacturing because blade manufacturing depends strongly on manual skill, process discipline and factory stability.
The thesis contributes by showing that coordination practices from mature industries are useful for understanding wind blade industrialization, but cannot be transferred directly. Framework C identifies which mechanisms should be retained, strengthened or added to better fit the wind turbine blade context. Practically, the study suggests that more reliable turbine scale-up requires earlier OEM–supplier coordination, stronger shared coordination structures, active supplier capability development and stronger protection of prototype learning before commercialization. ...
This thesis examines how inter-firm coordination at the DMI in wind turbine blade manufacturing can be strengthened to support reliable turbine scale-up under deployment pressure. Coordination mechanisms from mature industries are used as the analytical starting point to investigate how these mechanisms appear, differ or remain underdeveloped in the wind blade context. The study follows qualitative research design. Literature on design–manufacturing integration, coordination theory and inter-firm coordination mechanisms was reviewed to construct a reference framework. This framework guided semi-structured expert interviews with participants from OEM, manufacturing and hybrid roles. The interview material was analysed through directed qualitative content analysis and synthesized into Framework C, a refined framework for strengthening inter-firm DMI coordination in the wind blade context.
The findings show that several mechanisms used in mature industries are already visible in wind blade industrialization, especially in design finalization, launch and problem-solving stages. However, the coordination base is uneven. Upstream coordination remains weaker, with limited early manufacturing involvement, fragmented cross-enterprise coordination baselines and underdeveloped supplier development. Prototype and validation learning are also pressured by the need to commercialize larger turbines quickly. Shop-floor capability emerged as a strengthening direction specific to wind blade manufacturing because blade manufacturing depends strongly on manual skill, process discipline and factory stability.
The thesis contributes by showing that coordination practices from mature industries are useful for understanding wind blade industrialization, but cannot be transferred directly. Framework C identifies which mechanisms should be retained, strengthened or added to better fit the wind turbine blade context. Practically, the study suggests that more reliable turbine scale-up requires earlier OEM–supplier coordination, stronger shared coordination structures, active supplier capability development and stronger protection of prototype learning before commercialization.
This research examines how information gaps arise across the lifecycle of infrastructure assets in the Netherlands and how Digital Product Passport can address these gaps by improving data continuity, quality, and accessibility. A qualitative methodology was used, combining a structured literature review with fifteen semi-structured interviews involving asset owners, consultants, policy advisors, and specialists in information management. The study identifies where material information is lost, how current systems fail to maintain consistent traceability, and which organizational conditions influence long-term data reliability.
Findings show that weak traceability results mainly from fragmented systems, unclear responsibilities, inconsistent updating routines, and limited digital capacity. Based on these insights, a strategy guide was developed containing twelve strategies that support the practical implementation of DPP in infrastructure projects. The strategies focus on system integration, structured handovers, data ownership, verification mechanisms, and standardized information formats. The guide is illustrated through its application to a prefabricated concrete slab, demonstrating how lifecycle information can be structured in practice.
The research concludes that Digital Product Passport can strengthen traceability when embedded in existing workflows and supported by clear governance and shared data standards. While a DPP cannot resolve all information challenges, it provides a structured framework that reduces information loss and supports more reliable lifecycle data for future decisions. ...
This research examines how information gaps arise across the lifecycle of infrastructure assets in the Netherlands and how Digital Product Passport can address these gaps by improving data continuity, quality, and accessibility. A qualitative methodology was used, combining a structured literature review with fifteen semi-structured interviews involving asset owners, consultants, policy advisors, and specialists in information management. The study identifies where material information is lost, how current systems fail to maintain consistent traceability, and which organizational conditions influence long-term data reliability.
Findings show that weak traceability results mainly from fragmented systems, unclear responsibilities, inconsistent updating routines, and limited digital capacity. Based on these insights, a strategy guide was developed containing twelve strategies that support the practical implementation of DPP in infrastructure projects. The strategies focus on system integration, structured handovers, data ownership, verification mechanisms, and standardized information formats. The guide is illustrated through its application to a prefabricated concrete slab, demonstrating how lifecycle information can be structured in practice.
The research concludes that Digital Product Passport can strengthen traceability when embedded in existing workflows and supported by clear governance and shared data standards. While a DPP cannot resolve all information challenges, it provides a structured framework that reduces information loss and supports more reliable lifecycle data for future decisions.
Consequently, this master thesis addresses this limitation by further developing the project management decision-support tool, Mit-C, through the inclusion of the resources availability and demand required by the mitigation measures. For this purpose, the addition of a significant number of variables and constraints into the original mathematical model was needed, increasing the computational time of the program but improving the realism of the results. The altered model was then validated using a case study: the construction of a warehouse. The tool was used with both simplified and detailed project data to test its performance.
The results demonstrated that including resource constraints has a significant effect on the optimal mitigation strategy and leads to a lower and more realistic probability of finishing the project on time. This difference is more noticeable when using detailed data. It is therefore concluded that while the resource-constrained model produces more pessimistic results, it offers a significantly more realistic, reliable and therefore valuable decision-making tool for project managers. ...
Consequently, this master thesis addresses this limitation by further developing the project management decision-support tool, Mit-C, through the inclusion of the resources availability and demand required by the mitigation measures. For this purpose, the addition of a significant number of variables and constraints into the original mathematical model was needed, increasing the computational time of the program but improving the realism of the results. The altered model was then validated using a case study: the construction of a warehouse. The tool was used with both simplified and detailed project data to test its performance.
The results demonstrated that including resource constraints has a significant effect on the optimal mitigation strategy and leads to a lower and more realistic probability of finishing the project on time. This difference is more noticeable when using detailed data. It is therefore concluded that while the resource-constrained model produces more pessimistic results, it offers a significantly more realistic, reliable and therefore valuable decision-making tool for project managers.
To answer these questions the research combined a literature synthesis on demand-side innovation and modular construction with twelve semi-structured interviews spanning national, provincial and municipal clients, engineering consultancies and sector experts. The analysis followed a three-cycle coding protocol into ten recurring themes and, ultimately, three influence modes: Cultivate, Configure and Convince mapped onto the Desirability-Viability-Feasibility (DVF) framework.
Theoretical insights
This thesis introduces the Cultivate–Configure–Convince (CCC) model and shows that its effective ordering is market-contingent rather than fixed. Derived from coded analysis of thirteen interviews (§5.3), CCC distinguishes three influence modes for suppliers: Cultivate (build awareness, legitimacy, trust), Configure (align technical, organisational, and contractual conditions), and Convince (evidence of viability and risk mitigation). The core contribution is that five procurement-market archetypes exhibit different CCC sequences, meaning CCC should be treated as a repertoire that adapts to procurement structure rather than a universal ladder. This market-sensitive interpretation is consistent with research on demand-side innovation in regulated, high-capital sectors, where public procurement shapes uptake and diffusion (Edler & Georghiou, 2007; Uyarra et al., 2014). Accordingly the figure to the right summarises how sequencing varies across archetypes; detailed rationale is provided in §6.3. Managerially, CCC functions as a market-sensitive sequencing framework: first diagnose the procurement archetype, then time Cultivate/Configure/Convince to focus resources, reduce transaction and political risk, and accelerate innovation adoption. In sum, the thesis reframes influence not as a fixed sequence but as a market-aligned playbook for suppliers and system integrators, with relevance beyond construction wherever procurement mediates innovation.
Practical insights
The evidence indicates that, although technical uncertainties are tolerated and cultural resistance is easing, public clients ultimately prioritise demonstrable life-cycle value. Viability therefore trumps feasibility and desirability. Contractors can break this stalemate only by supplying audited ‘cost-and-carbon’ dashboards, involving engineering consultancies, certified pilots and then hard-wiring IFD metrics into procurement templates. A five-horizon pathway emerges: ignite internally with a small certified span and open data passport, flip external bias by forming a multi-contractor coalition and harvesting tool, prove at scale via ordinary-span interface tests and shared cost benchmarks, lock-in with 3-to-5-span bundles and framework contracts, and, finally, normalise IFD through open data portals and multi-owner agreements. Each horizon is gated by an explicit go/no-go check to limit sunk costs and keep investment tied to verifiable savings...
...
To answer these questions the research combined a literature synthesis on demand-side innovation and modular construction with twelve semi-structured interviews spanning national, provincial and municipal clients, engineering consultancies and sector experts. The analysis followed a three-cycle coding protocol into ten recurring themes and, ultimately, three influence modes: Cultivate, Configure and Convince mapped onto the Desirability-Viability-Feasibility (DVF) framework.
Theoretical insights
This thesis introduces the Cultivate–Configure–Convince (CCC) model and shows that its effective ordering is market-contingent rather than fixed. Derived from coded analysis of thirteen interviews (§5.3), CCC distinguishes three influence modes for suppliers: Cultivate (build awareness, legitimacy, trust), Configure (align technical, organisational, and contractual conditions), and Convince (evidence of viability and risk mitigation). The core contribution is that five procurement-market archetypes exhibit different CCC sequences, meaning CCC should be treated as a repertoire that adapts to procurement structure rather than a universal ladder. This market-sensitive interpretation is consistent with research on demand-side innovation in regulated, high-capital sectors, where public procurement shapes uptake and diffusion (Edler & Georghiou, 2007; Uyarra et al., 2014). Accordingly the figure to the right summarises how sequencing varies across archetypes; detailed rationale is provided in §6.3. Managerially, CCC functions as a market-sensitive sequencing framework: first diagnose the procurement archetype, then time Cultivate/Configure/Convince to focus resources, reduce transaction and political risk, and accelerate innovation adoption. In sum, the thesis reframes influence not as a fixed sequence but as a market-aligned playbook for suppliers and system integrators, with relevance beyond construction wherever procurement mediates innovation.
Practical insights
The evidence indicates that, although technical uncertainties are tolerated and cultural resistance is easing, public clients ultimately prioritise demonstrable life-cycle value. Viability therefore trumps feasibility and desirability. Contractors can break this stalemate only by supplying audited ‘cost-and-carbon’ dashboards, involving engineering consultancies, certified pilots and then hard-wiring IFD metrics into procurement templates. A five-horizon pathway emerges: ignite internally with a small certified span and open data passport, flip external bias by forming a multi-contractor coalition and harvesting tool, prove at scale via ordinary-span interface tests and shared cost benchmarks, lock-in with 3-to-5-span bundles and framework contracts, and, finally, normalise IFD through open data portals and multi-owner agreements. Each horizon is gated by an explicit go/no-go check to limit sunk costs and keep investment tied to verifiable savings...
Building on a comprehensive literature review and exploratory interviews with key procurement and project staff, the study identifies gaps in traditional evaluation processes, particularly the overreliance on static rating templates and the absence of dual-perspective analysis. To address this, a novel AI-enhanced evaluation framework is developed using a design science methodology. The framework enables structured performance assessments based on both internal HOCHTIEF feedback and subcontractor self-evaluations. ChatGPT 4.0, embedded in HOCHTIEF’s internal AI assistant “NextChat” supports this process by interpreting qualitative data, prompting for clarification when needed, generating justifications for ratings, and summarizing insights into actionable reports.
The framework was implemented in a pilot case study involving a subcontractor working on a real HOCHTIEF data centre project. Evaluation inputs from both parties were processed using the AI assistant and benchmarked against HOCHTIEF’s existing manual evaluation methods.
Validation of the framework was multi-faceted. Process validation demonstrated that AI-generated reports aligned closely with manual evaluations, with a Mean Absolute Percentage Deviation (MAPD) of less than 10%, indicating high accuracy. Stakeholder validation was conducted through structured surveys with HOCHTIEF personnel, assessing insightfulness, transparency, clarity of follow-up queries, added value, and perceived limitations. The results were consistently positive.
While the results indicate strong potential for improving subcontractor evaluations through AI integration, the study also highlights critical limitations and risks. These include the need for high-quality, context-rich input data, the need for human oversight and verification of the results, data availability challenges, and the necessity of embedding the tool within existing procurement databases to ensure organizational consistency. Furthermore, successful implementation depends on training and change management strategies, particularly in organizations with limited digital procurement maturity.
The study contributes theoretically by empirically validating the integration of AI and MCDA in construction procurement and practically by providing a scalable tool that enhances the structure, transparency, and usability of post-project subcontractor evaluations. It is supported by established adoption frameworks, including the Technology–Organization–Environment (TOE) model and the Unified Theory of Acceptance and Use of Technology (UTAUT). Overall, this research offers a data-informed, dual-perspective, and AI-supported approach to subcontractor assessment, positioning it as a robust enhancement to current construction management practices. ...
Building on a comprehensive literature review and exploratory interviews with key procurement and project staff, the study identifies gaps in traditional evaluation processes, particularly the overreliance on static rating templates and the absence of dual-perspective analysis. To address this, a novel AI-enhanced evaluation framework is developed using a design science methodology. The framework enables structured performance assessments based on both internal HOCHTIEF feedback and subcontractor self-evaluations. ChatGPT 4.0, embedded in HOCHTIEF’s internal AI assistant “NextChat” supports this process by interpreting qualitative data, prompting for clarification when needed, generating justifications for ratings, and summarizing insights into actionable reports.
The framework was implemented in a pilot case study involving a subcontractor working on a real HOCHTIEF data centre project. Evaluation inputs from both parties were processed using the AI assistant and benchmarked against HOCHTIEF’s existing manual evaluation methods.
Validation of the framework was multi-faceted. Process validation demonstrated that AI-generated reports aligned closely with manual evaluations, with a Mean Absolute Percentage Deviation (MAPD) of less than 10%, indicating high accuracy. Stakeholder validation was conducted through structured surveys with HOCHTIEF personnel, assessing insightfulness, transparency, clarity of follow-up queries, added value, and perceived limitations. The results were consistently positive.
While the results indicate strong potential for improving subcontractor evaluations through AI integration, the study also highlights critical limitations and risks. These include the need for high-quality, context-rich input data, the need for human oversight and verification of the results, data availability challenges, and the necessity of embedding the tool within existing procurement databases to ensure organizational consistency. Furthermore, successful implementation depends on training and change management strategies, particularly in organizations with limited digital procurement maturity.
The study contributes theoretically by empirically validating the integration of AI and MCDA in construction procurement and practically by providing a scalable tool that enhances the structure, transparency, and usability of post-project subcontractor evaluations. It is supported by established adoption frameworks, including the Technology–Organization–Environment (TOE) model and the Unified Theory of Acceptance and Use of Technology (UTAUT). Overall, this research offers a data-informed, dual-perspective, and AI-supported approach to subcontractor assessment, positioning it as a robust enhancement to current construction management practices.
Navigating Delays in Green Water Projects
Identifying Sustainability-Related Challenges and Mitigation Strategies
This thesis investigates how sustainability-related complexities affect the timely execution of green water projects and identifies targeted planning strategies to mitigate those impacts. The central research question driving this study is: What planning strategies can help in the successful implementation of Sustainability in Water Projects?
To answer this, the following sub-questions are explored:
1. What are Green Water Projects?
2. How do they differ from traditional projects?
3. What differentiating green factors could result in delays in Green Water Projects?
4. How can these delays be mitigated?
A qualitative multi-phase research approach was adopted to answer these questions, consisting of four key stages: exploratory interviews, literature review, semi-structured expert interviews, and expert feedback workshop with industry stakeholders at Bilfinger Engineering and Consultancy. The exploratory interviews scoped the landscape and helped define "green water projects" in practical terms. The literature review established the conceptual framework, while the semi-structured interviews provided in-depth insights into sustainability-related project delays. The final expert validation tested the practical applicability of the proposed strategies.
The research draws on real-world experiences, including cases involving hydrogen infrastructure, algae-based protein production, and sustainable fuel development, to contextualize the analysis.
The study identifies four core planning solutions tied to the delay drivers:
• Regulatory Uncertainty: Mitigated through early stakeholder alignment and adaptive frameworks like Front-End Loading (FEL) and the Transition Management Framework.
• Technological Novelty: Addressed via iterative testing and feedback using tools such as the Innovation Chasm Strategy and Adaptive Management.
• Financial Feasibility: Enhanced by reducing risk perception through Risk Scoring Matrices, Process Thinking, and Outcome-Based Financing approaches.
• Institutional Capacity: Strengthened through Organizational Learning, Bow Tie Risk Models, and Multilevel Transition Management, which foster resilience and governance alignment.
Building on these findings the study introduces a comprehensive roadmap structured around four interlinked pillars consisting of early stakeholder engagement, bridging the innovation adoption gap, adaptive project management, and institutional alignment with long-term sustainability goals. These pillars are operationalized through a layered approach across strategic, tactical, and operational levels, reflecting the complex, dynamic, and socio-technical nature of sustainability implementation. This multi-level structure enables flexible and adaptive planning that accommodates evolving regulatory, technological, and financial conditions, thereby supporting resilience in project delivery.
A key insight of this research is the redefinition of the traditional Iron Triangle of project management. By incorporating sustainability as a core dimension alongside cost, time, quality, and scope, the study proposes a new paradigm for project planning that aligns with contemporary environmental and social requirements. This reconceptualization allows project teams to evaluate trade-offs more holistically and design solutions that do not sacrifice long-term goals for short-term efficiency. Although the strategies have been tailored to green water projects, they are designed for adaptability and can be applied more broadly to green projects.
Ultimately, the findings serve as a practical guide for project managers and policy stakeholders seeking to overcome sustainability-induced delays. The research contributes to both academic understanding and industry practice by offering an actionable, multi-level planning framework that supports the successful implementation of sustainable infrastructure. By embedding adaptive and transition management principles alongside enhanced governance synchronization, the proposed strategies enable proactive management of uncertainty and institutional alignment, which are essential for scaling sustainable innovations in complex infrastructure projects. ...
This thesis investigates how sustainability-related complexities affect the timely execution of green water projects and identifies targeted planning strategies to mitigate those impacts. The central research question driving this study is: What planning strategies can help in the successful implementation of Sustainability in Water Projects?
To answer this, the following sub-questions are explored:
1. What are Green Water Projects?
2. How do they differ from traditional projects?
3. What differentiating green factors could result in delays in Green Water Projects?
4. How can these delays be mitigated?
A qualitative multi-phase research approach was adopted to answer these questions, consisting of four key stages: exploratory interviews, literature review, semi-structured expert interviews, and expert feedback workshop with industry stakeholders at Bilfinger Engineering and Consultancy. The exploratory interviews scoped the landscape and helped define "green water projects" in practical terms. The literature review established the conceptual framework, while the semi-structured interviews provided in-depth insights into sustainability-related project delays. The final expert validation tested the practical applicability of the proposed strategies.
The research draws on real-world experiences, including cases involving hydrogen infrastructure, algae-based protein production, and sustainable fuel development, to contextualize the analysis.
The study identifies four core planning solutions tied to the delay drivers:
• Regulatory Uncertainty: Mitigated through early stakeholder alignment and adaptive frameworks like Front-End Loading (FEL) and the Transition Management Framework.
• Technological Novelty: Addressed via iterative testing and feedback using tools such as the Innovation Chasm Strategy and Adaptive Management.
• Financial Feasibility: Enhanced by reducing risk perception through Risk Scoring Matrices, Process Thinking, and Outcome-Based Financing approaches.
• Institutional Capacity: Strengthened through Organizational Learning, Bow Tie Risk Models, and Multilevel Transition Management, which foster resilience and governance alignment.
Building on these findings the study introduces a comprehensive roadmap structured around four interlinked pillars consisting of early stakeholder engagement, bridging the innovation adoption gap, adaptive project management, and institutional alignment with long-term sustainability goals. These pillars are operationalized through a layered approach across strategic, tactical, and operational levels, reflecting the complex, dynamic, and socio-technical nature of sustainability implementation. This multi-level structure enables flexible and adaptive planning that accommodates evolving regulatory, technological, and financial conditions, thereby supporting resilience in project delivery.
A key insight of this research is the redefinition of the traditional Iron Triangle of project management. By incorporating sustainability as a core dimension alongside cost, time, quality, and scope, the study proposes a new paradigm for project planning that aligns with contemporary environmental and social requirements. This reconceptualization allows project teams to evaluate trade-offs more holistically and design solutions that do not sacrifice long-term goals for short-term efficiency. Although the strategies have been tailored to green water projects, they are designed for adaptability and can be applied more broadly to green projects.
Ultimately, the findings serve as a practical guide for project managers and policy stakeholders seeking to overcome sustainability-induced delays. The research contributes to both academic understanding and industry practice by offering an actionable, multi-level planning framework that supports the successful implementation of sustainable infrastructure. By embedding adaptive and transition management principles alongside enhanced governance synchronization, the proposed strategies enable proactive management of uncertainty and institutional alignment, which are essential for scaling sustainable innovations in complex infrastructure projects.
Translating project complexity into award criteria; the balance of quality and price
A case study analysis into the use of award criteria in the procurement of replacement & renovation projects at ProRail
However, there is limited empirical evidence on the extent to which public clients translate project complexity into award criteria. This study addresses that gap by examining the case of ProRail, the Dutch railway infrastructure manager, and its use of award criteria in recent R&R tenders. It aims to analyze to what extent project complexity is translated into award criteria for the procurement of these projects. The research combines qualitative insights from interviews on perceived project complexity with a quantitative analysis of the award criteria and their weightings in four recent ProRail R&R tenders.
Findings reveal a partial but positive relationship: in more complex R&R projects, ProRail uses more project-specific quality criteria that are related to project complexity. Projects that were perceived as less complex relied more on ambition-related award criteria and price. Interview participants also mentioned that at ProRail technical complexity was addressed through strict requirements and not through award criteria, while organizational and environmental complexity were more translated into award criteria to create differentiation between bidders.
The research offers a first empirical foundation for understanding how a public client incorporates project complexity into its procurement practices. Although this study focuses only on ProRail, its findings and recommendations are relevant for other public infrastructure clients and can serve as a basis for future research into the alignment between project complexity and procurement strategies.
...
However, there is limited empirical evidence on the extent to which public clients translate project complexity into award criteria. This study addresses that gap by examining the case of ProRail, the Dutch railway infrastructure manager, and its use of award criteria in recent R&R tenders. It aims to analyze to what extent project complexity is translated into award criteria for the procurement of these projects. The research combines qualitative insights from interviews on perceived project complexity with a quantitative analysis of the award criteria and their weightings in four recent ProRail R&R tenders.
Findings reveal a partial but positive relationship: in more complex R&R projects, ProRail uses more project-specific quality criteria that are related to project complexity. Projects that were perceived as less complex relied more on ambition-related award criteria and price. Interview participants also mentioned that at ProRail technical complexity was addressed through strict requirements and not through award criteria, while organizational and environmental complexity were more translated into award criteria to create differentiation between bidders.
The research offers a first empirical foundation for understanding how a public client incorporates project complexity into its procurement practices. Although this study focuses only on ProRail, its findings and recommendations are relevant for other public infrastructure clients and can serve as a basis for future research into the alignment between project complexity and procurement strategies.
The reuseability of cast-in-situ concrete slab elements
A case study of Schiphol's C-pier
A mixed-methods approach combines a systematic literature review, multiple case studies of recent Dutch reuse initiatives, semi-structured expert interviews, and design-science research. The study develops two complementary frameworks: a Verification Framework, which provides a Eurocode-aligned, stepwise method for assessing the geometry, material properties, durability, and structural performance of reclaimed slabs, and a Communication Framework, which defines how verification data is generated, transferred, and safeguarded across project stages to ensure traceability and alignment among stakeholders.
Validation of both frameworks using real project data shows that reclaimed slabs can meet structural and durability requirements—especially in lower-load, repetitive applications—while achieving substantial embodied-carbon reductions of up to 60% relative to new concrete alternatives. The findings demonstrate that technical feasibility alone is insufficient: successful reuse depends equally on well-structured information flows, early role definition, and integrated collaboration between donor and target projects.
By providing practical guidance for engineers, project managers, contractors, and policymakers, this thesis contributes a coherent, ready-to-apply foundation for professionalising structural concrete reuse. The developed frameworks offer a pathway to reduce uncertainty, improve decision-making, and embed reuse within mainstream construction processes—supporting the wider transition toward a circular built environment. ...
A mixed-methods approach combines a systematic literature review, multiple case studies of recent Dutch reuse initiatives, semi-structured expert interviews, and design-science research. The study develops two complementary frameworks: a Verification Framework, which provides a Eurocode-aligned, stepwise method for assessing the geometry, material properties, durability, and structural performance of reclaimed slabs, and a Communication Framework, which defines how verification data is generated, transferred, and safeguarded across project stages to ensure traceability and alignment among stakeholders.
Validation of both frameworks using real project data shows that reclaimed slabs can meet structural and durability requirements—especially in lower-load, repetitive applications—while achieving substantial embodied-carbon reductions of up to 60% relative to new concrete alternatives. The findings demonstrate that technical feasibility alone is insufficient: successful reuse depends equally on well-structured information flows, early role definition, and integrated collaboration between donor and target projects.
By providing practical guidance for engineers, project managers, contractors, and policymakers, this thesis contributes a coherent, ready-to-apply foundation for professionalising structural concrete reuse. The developed frameworks offer a pathway to reduce uncertainty, improve decision-making, and embed reuse within mainstream construction processes—supporting the wider transition toward a circular built environment.
This research focuses on identifying and analyzing Early Warning Signals (EWS) to mitigate schedule delays during the design phase of infrastructure projects managed by Sweco, a consultancy company in the Netherlands. The primary aim is to explore how effectively EWS can be used to identify potential issues early and prevent project delays.
The research begins by assessing the current knowledge and application of EWS among project managers, controllers and directors at Sweco. Initial findings indicate that while most participants have a basic understanding of the concept of EWS, they do not actively use or recognize it in their daily workflows. Their awareness of these signals primarily stems from gut feelings and extensive experience rather than systematic identification and application.
To identify the most relevant EWS, the study combines insights from existing literature with practical experiences shared by Sweco experts. This process involves creating a comprehensive list of potential EWS, which is then narrowed down and prioritised based on their perceived impact and likelihood. The prioritisation is similar to a risk assessment method, considering both the probability and potential impact of each signal.
The study examines how to measure data related to the signals and proposes measures on how to handle those EWS better. Some of the suggestions include establishing clear working agreements, balancing formal and informal communication, enhancing collaboration through workshops and visual tools, and leveraging advanced technologies like AI and BIM. The study further emphasises the importance of continuous client communication, internal quality checks, and ensuring appropriate expertise for project tasks.
The research provides a comprehensive framework for identifying, measuring, and managing EWS to improve project outcomes and reduce schedule delays in infrastructure projects. The findings emphasise the need for systematic approaches and technological integration to enhance early warning capabilities and project management practices. By implementing the recommended strategies, Sweco can better anticipate potential issues, make informed decisions, and ultimately deliver projects more efficiently.
Keywords: Early Warning Signals (EWS), schedule delay, design phase, infrastructure projects, project management, measurability, prioritisation
...
This research focuses on identifying and analyzing Early Warning Signals (EWS) to mitigate schedule delays during the design phase of infrastructure projects managed by Sweco, a consultancy company in the Netherlands. The primary aim is to explore how effectively EWS can be used to identify potential issues early and prevent project delays.
The research begins by assessing the current knowledge and application of EWS among project managers, controllers and directors at Sweco. Initial findings indicate that while most participants have a basic understanding of the concept of EWS, they do not actively use or recognize it in their daily workflows. Their awareness of these signals primarily stems from gut feelings and extensive experience rather than systematic identification and application.
To identify the most relevant EWS, the study combines insights from existing literature with practical experiences shared by Sweco experts. This process involves creating a comprehensive list of potential EWS, which is then narrowed down and prioritised based on their perceived impact and likelihood. The prioritisation is similar to a risk assessment method, considering both the probability and potential impact of each signal.
The study examines how to measure data related to the signals and proposes measures on how to handle those EWS better. Some of the suggestions include establishing clear working agreements, balancing formal and informal communication, enhancing collaboration through workshops and visual tools, and leveraging advanced technologies like AI and BIM. The study further emphasises the importance of continuous client communication, internal quality checks, and ensuring appropriate expertise for project tasks.
The research provides a comprehensive framework for identifying, measuring, and managing EWS to improve project outcomes and reduce schedule delays in infrastructure projects. The findings emphasise the need for systematic approaches and technological integration to enhance early warning capabilities and project management practices. By implementing the recommended strategies, Sweco can better anticipate potential issues, make informed decisions, and ultimately deliver projects more efficiently.
Keywords: Early Warning Signals (EWS), schedule delay, design phase, infrastructure projects, project management, measurability, prioritisation
Enhancing Safety Performance in the Construction Industry
A Qualitative Comparison between Infrastructure and Oil & Gas projects on 43 client roles in 3 preconstruction phases with perspectives from both clients and contractors
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This study investigates how to stimulate the realisation of urban mining hubs in the Netherlands. The primary research question is: How can the realisation of urban mining hubs in the Netherlands be stimulated? Data was collected through a literature review and semi-structured interviews with key stakeholders in the construction sector.
Findings highlight the undefined role of hubs within the urban mining process and the advantages they offer, including resource conservation, financial savings, and employment opportunities within a circular economy. Barriers include insufficient material supply and demand, inventory uncertainties, and inadequate legislation. An actionable framework was developed, consisting of three phases: initiation, optimisation, and expansion, with a focus on innovation, education, and collaboration among stakeholders. ...
This study investigates how to stimulate the realisation of urban mining hubs in the Netherlands. The primary research question is: How can the realisation of urban mining hubs in the Netherlands be stimulated? Data was collected through a literature review and semi-structured interviews with key stakeholders in the construction sector.
Findings highlight the undefined role of hubs within the urban mining process and the advantages they offer, including resource conservation, financial savings, and employment opportunities within a circular economy. Barriers include insufficient material supply and demand, inventory uncertainties, and inadequate legislation. An actionable framework was developed, consisting of three phases: initiation, optimisation, and expansion, with a focus on innovation, education, and collaboration among stakeholders.
Findings show that literature treats changes as formal and prospective and deviations as informal and retrospective; once deviations occur, they are accepted or rectified, with limited guidance beyond acceptance. In practice, deviations arise through bilateral agreements, unilateral contractor actions, or errors; formal change orders differ by sector, with the public sector imposing strict regulations and finance delays, while private sector relies more on informal agreements. The study identifies six preventive measures: improve final design; include paid, thorough contractor reviews in contracts; reduce change-order bureaucracy; enhance teamwork and communication; anticipate unforeseen events; hire qualified professionals. For managing deviations, four feasible practices are recommended: seek specialist opinions; document informal agreements; embed deviation management into regulations; rely on experience and safety considerations. Conclusions stress understanding the differences, reducing deviations, and applying proposed practices, while noting they are not universal remedies. The study suggests avenues for further research, including sector-specific analyses, agile methodologies, client/financier perspectives, ethics, and a protocol for middle-ground modifications. ...
Findings show that literature treats changes as formal and prospective and deviations as informal and retrospective; once deviations occur, they are accepted or rectified, with limited guidance beyond acceptance. In practice, deviations arise through bilateral agreements, unilateral contractor actions, or errors; formal change orders differ by sector, with the public sector imposing strict regulations and finance delays, while private sector relies more on informal agreements. The study identifies six preventive measures: improve final design; include paid, thorough contractor reviews in contracts; reduce change-order bureaucracy; enhance teamwork and communication; anticipate unforeseen events; hire qualified professionals. For managing deviations, four feasible practices are recommended: seek specialist opinions; document informal agreements; embed deviation management into regulations; rely on experience and safety considerations. Conclusions stress understanding the differences, reducing deviations, and applying proposed practices, while noting they are not universal remedies. The study suggests avenues for further research, including sector-specific analyses, agile methodologies, client/financier perspectives, ethics, and a protocol for middle-ground modifications.
Gaining Insights into the Use and Documentation of Lessons Learned in Tender Processes
Addressing the Gaps in Knowledge Sharing
Underwater concrete floors: improving design efficiency
A parametric approach to studying the impact of design parameters and the benefits of fibre reinforcement
The objective of this thesis is to investigate how design efficiency of underwater concrete floors can be improved. In an effort to reduce material usage and achieve cost-effective structures, the following research question was stated:
“What is the influence of design parameters and how can parameters be adjusted to improve design efficiency of an underwater concrete floor, and to what extent can the addition of fibre reinforcement contribute to this optimization?”
A parametric model was developed to provide insight to the sensitivity of parameters and their impact on design resistance. Furthermore, the model was utilized to examine under what circumstances potential material savings can be obtained by implementing fibre reinforced concrete in UCF’s. This was accomplished through the evaluation and comparison of the minimum required thickness based on bending moment resistance in various scenarios, for both UCF’s and steel fibre reinforced UCF’s (SFUCF).
Results obtained with the parametric model established that, in order to enhance the bending moment resistance of an uncracked UCF, increasing the nominal thickness becomes relatively more effective compared to increasing the concrete strength class for higher normal forces. When utilizing a compression arch to obtain bending moment resistance, the implementation of ribbed tensile elements or an increase in nominal thickness are found to be the most suitable methods for increasing resistance. For enhanced shear force resistance, increasing the nominal thickness over the concrete class provides relatively more additional resistance for slender UCF’s. The results found that through the application of ribbed piles, most punching shear force resistance can be obtained.
Three use cases for a SFUCF were identified using the parametric model. When centre to centre (c.t.c.) distances larger than 4.4m are applied in combination with a substantial normal force, significant material savings of up to 0.3m thickness are possible, which equates to a reduction of material usage by 30%. For situations where the effective height of the compression arch is small, it was also found that material usage could be reduced by 30%. Perhaps the most significant use case for a SFUCF is when the normal force is close to zero, and additional normal force cannot be obtained through membrane action. In these situations, the application of a SFUCF can make an otherwise near impossible project feasible.
As a new design approach, a cost-based optimization tool was developed using the parametric model. An already executed UCF was evaluated using the tool, it was determined that a more cost-effective design could have been achieved, with potential savings of up to 30% in costs.
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The objective of this thesis is to investigate how design efficiency of underwater concrete floors can be improved. In an effort to reduce material usage and achieve cost-effective structures, the following research question was stated:
“What is the influence of design parameters and how can parameters be adjusted to improve design efficiency of an underwater concrete floor, and to what extent can the addition of fibre reinforcement contribute to this optimization?”
A parametric model was developed to provide insight to the sensitivity of parameters and their impact on design resistance. Furthermore, the model was utilized to examine under what circumstances potential material savings can be obtained by implementing fibre reinforced concrete in UCF’s. This was accomplished through the evaluation and comparison of the minimum required thickness based on bending moment resistance in various scenarios, for both UCF’s and steel fibre reinforced UCF’s (SFUCF).
Results obtained with the parametric model established that, in order to enhance the bending moment resistance of an uncracked UCF, increasing the nominal thickness becomes relatively more effective compared to increasing the concrete strength class for higher normal forces. When utilizing a compression arch to obtain bending moment resistance, the implementation of ribbed tensile elements or an increase in nominal thickness are found to be the most suitable methods for increasing resistance. For enhanced shear force resistance, increasing the nominal thickness over the concrete class provides relatively more additional resistance for slender UCF’s. The results found that through the application of ribbed piles, most punching shear force resistance can be obtained.
Three use cases for a SFUCF were identified using the parametric model. When centre to centre (c.t.c.) distances larger than 4.4m are applied in combination with a substantial normal force, significant material savings of up to 0.3m thickness are possible, which equates to a reduction of material usage by 30%. For situations where the effective height of the compression arch is small, it was also found that material usage could be reduced by 30%. Perhaps the most significant use case for a SFUCF is when the normal force is close to zero, and additional normal force cannot be obtained through membrane action. In these situations, the application of a SFUCF can make an otherwise near impossible project feasible.
As a new design approach, a cost-based optimization tool was developed using the parametric model. An already executed UCF was evaluated using the tool, it was determined that a more cost-effective design could have been achieved, with potential savings of up to 30% in costs.