Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Building and Real Estate | en_US |
| dc.contributor.advisor | Zayed, Tarek (BRE) | en_US |
| dc.creator | Hussein, Mohamed Mamdouh Yusuf | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/12204 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Optimum and sustainable supply chain management of modular integrated construction using operations research and blockchain technologies | en_US |
| dcterms.abstract | Modular integrated construction (MiC) is among the technologies that potentially ameliorate the construction industry's current stagnation situation. MiC is characterized by a multi-echelon supply chain (SC) has three stages: production, logistics, and construction. Poor management of the MiC supply chain (MiC-SC) is among the key barriers that impede its wider adoption. This poor management is stemmed from the lack of efficient SC planning that integrates the MiC-SC stages and the lack of collaboration, trust, and real-time information sharing among its stakeholders, resulting in a weekly integrated, less sustainable and suboptimal SC that could wipe away the MiC advantages. Therefore, the primary aim of this research is to optimize the decision-making for more sustainable logistics and supply chain management of MiC (MiC- SCM) and enhance stakeholder collaboration while ensuring data privacy, security, information sharing and immutability. This aim could be achieved through the following objectives: 1) identify and assess the critical factors required to successfully implement just- in-time (JIT) in MiC-SC; 2) model, analyze and optimize MiC-SC decisions in case of using road transportation; 3) develop a decision support system for sustainable multimodal logistics planning in MiC-SC; and 4) develop a digital twin-based blockchain framework for optimized and secured MiC-SCM. | en_US |
| dcterms.abstract | To achieve the first objective, a systematic review of quantitative studies identifies critical factors (CFs) for implementing JIT in MiC. Then, the importance of each CF is assessed by conducting a meta-analysis. Regarding the second objective, a multimethod simulation model is developed to capture the dynamic behaviour of MiC-SC stakeholders through agent-based modelling (ABM) and model their internal operations using discrete-event simulation (DES). Next, the Taguchi approach (TA) is adopted to identify the significant SC decisions that impact its key performance indicators (KPIs). Then, a simulation-optimization (SO) approach is applied to find the near-optimum Pareto frontier of SC decisions that minimize the project duration, SC costs, and carbon emissions. As for the third objective, a holistic modelling approach that integrates three methods is developed to model, study and optimize multimodal logistics of MiC-SC (ML-MiC). First, a hybrid multi-agent simulation model is developed to model the ML-MiC. Second, design of experiment (DOE) is used to reveal the main and interaction effects between ML-MiC decisions. Third, metamodeling is adopted to find the near-optimum ML-MiC decisions that optimize its KPIs. Finally, a digital twin-based blockchain (DT-BC-SCM-MiC) framework is developed for secured and optimized MiC-SCM (Objective 4). In this framework, the digital MiC-SC is built by developing a hybrid simulation model fed with collected IoT real-time data. To secure the link between the IoT system and the digital MiC-SC, a permissioned BC network is developed. | en_US |
| dcterms.abstract | Two case studies of MiC projects in Hong Kong are used to validate the developed models. The results demonstrate the capability of these models to achieve the research objectives. This research makes original contributions toward an optimum and sustainable MiC-SCM. The theoretical contributions are: 1) the meta-analysis addresses the disagreement in the literature regarding the assessment of CFs of JIT; 2) developing hybrid multi-agent simulation models that capture the dynamic interactions between MiC-SC stakeholders and their internal operations in case of using unimodal and multimodal transportation; 3) integrating the simulation models with DOE to discern the impact of multiple SC decisions on different KPIs; 4) integrating the simulation models and the DOE with two SO techniques: metaheuristics and local metamodeling, to find the near-optimum SC decisions; and 5) extending the benefits of IoT, simulation, optimization, and BC technologies to add more descriptive and analytical value to the current practice in MiC-SCM. The practical contributions are: 1) providing a checklist and ranking of CFs to support the successful application of JIT in MiC-SC; 2) estimating the impact of multiple SC decisions on different KPIs in a riskless environment; 3) demonstrating the need for collaborative decision-making between stakeholders; 4) providing stakeholders with the near-optimum SC decisions to improve the MiC-SC sustainability; and 5) The DT-BC-SCM-MiC system would support real-time information sharing and optimum SC decision planning while maintaining data privacy, security, and immutability. | en_US |
| dcterms.abstract | These points would contribute to the theory development of MiC-SCM. Also, integrating new technologies such as digital twin, blockchain, and IoT enables MiC-SC stakeholders to coordinate, discern, and optimize the MiC-SC decisions, hence boosting the collaboration, transparency, and trust between them towards a more optimal, smarter, and sustainable MiC-SCM. | en_US |
| dcterms.extent | xix, 285 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2022 | en_US |
| dcterms.educationalLevel | Ph.D. | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.LCSH | Modular construction | en_US |
| dcterms.LCSH | Buildings, Prefabricated | en_US |
| dcterms.LCSH | Business logistics | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | open access | en_US |
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