國立虎尾科技大學 |

Enhance Collaboration Reliability at Task Level for Construction Projects Using Blockchain Technology.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Enhance Collaboration Reliability at Task Level for Construction Projects Using Blockchain Technology./
作者:	Chen, Gongfan.
面頁冊數:	1 online resource (245 pages)
附註:	Source: Dissertations Abstracts International, Volume: 85-06, Section: A.
Contained By:	Dissertations Abstracts International85-06A.
標題:	Web studies. -
電子資源:	click for full text (PQDT)
ISBN:	9798381024333

Enhance Collaboration Reliability at Task Level for Construction Projects Using Blockchain Technology.
Chen, Gongfan.

Enhance Collaboration Reliability at Task Level for Construction Projects Using Blockchain Technology. - 1 online resource (245 pages)

Source: Dissertations Abstracts International, Volume: 85-06, Section: A.

Thesis (Ph.D.)--North Carolina State University, 2023.

Includes bibliographical references

Reliable workflow is critical in enhancing the construction industry's overall productivity. A reliable workflow can be achieved by ensuring that communication flows smoothly between all specialty trades involved, constraints are removed, and instant feedback is available. Moreover, a transparent and accountable environment can uphold a reliable workflow because all parties can understand their responsibilities, risks, and expected outcomes unambiguously. Recently, the adoption of blockchain technology in construction has emerged as a disruptive trend, providing opportunities to facilitate and decentralize production management through the power of smart contracts. However, the following questions are yet to know: (1) how to investigate the impacts of constraints arising from the specialty trades' variations in terms of project outcomes, (2) how to derive fair profit allocation contract consensus among specialty trades when working in the coalition, and (3) how to integrate semantically rich as-built data to provide automatic project appraisals and instant decision-making to enhance a reliable workflow. This research aims to provide contextualization, incentivization, and digitalization to enhance task-level collaboration reliability using blockchain-enabled smart contracts. Three primary goals are to (1) quantify the interdependent interrelated impacts of project constraints arising from variations in specialty trades on project outcomes, (2) derive a fair benefit distribution method among specialty trades when working in a collaborative work setting, and (3) integrate semantically rich as-built images to automate smart contract executions.First, the research selected a modular construction project to investigate the impact of specialty trades' variations on the project's duration and costs. A simulation model was deployed, and the resulting profits were encoded in smart contracts as incentive-penalty sharing rules. These rules were designed to enforce a higher level of performance among specialty trades, thereby ensuring reliable constraint removal. To record and share as-built images as unique evidence for performance verification, an InterPlanetary File System (IPFS)-based approach was integrated into the framework. Next, the research combined and permutated various collaborative variables for three specialty trades, generating 27 scenarios in simulation. The Shapley value was then applied to aggregate the outcomes and determine the fair benefit-sharing mechanism, which was subsequently embedded in smart contracts and tested in various scenarios to validate the effectiveness and efficiency of the developed framework. Lastly, a high-rise residential building was selected, and as-built image data was collected. To classify the as-built image into different progress categories, a deep learning model was developed for blockchain oracle development. Furthermore, the research analyzed the various impacts of prerequisite delays in-depth and identified optimal mitigation strategies. Ultimately, a decentralized application was developed, which synchronizes as-built images, classified results, and mitigation strategies to enable automatic smart contract executions.The first case study revealed that reliable constraint removal leads to substantial reductions in wait time for equipment and labor, resulting in an overall cost savings of 4.7% compared to the benchmark scenario. For example, the removal of material constraints resulted in a 45.7% and 78.5% reduction in equipment and labor wait times, respectively. Additionally, the use of simulation to convert implicit construction dynamics into explicit contract consensus facilitated the adoption of smart contracts in the construction industry.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798381024333Subjects--Topical Terms:

1148502
Web studies.
Index Terms--Genre/Form:

554714
Electronic books.

Enhance Collaboration Reliability at Task Level for Construction Projects Using Blockchain Technology.
LDR:05098ntm a22003497 4500 001 1143889
005 20240517105019.5
006 m o d
007 cr mn ---uuuuu
008 250605s2023 xx obm 000 0 eng d
020 $a 9798381024333
035 $a (MiAaPQ)AAI30727236
035 $a (MiAaPQ)NCState_Univ18402041242
035 $a AAI30727236
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Chen, Gongfan. $3 1468698
245 1 0 $a Enhance Collaboration Reliability at Task Level for Construction Projects Using Blockchain Technology.
264 0 $c 2023
300 $a 1 online resource (245 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 85-06, Section: A.
500 $a Advisor: Hsiang, Simon;Han, Kook;Jaselskis, Edward;Fang, Shu-Cherng;Liu, Min.
502 $a Thesis (Ph.D.)--North Carolina State University, 2023.
504 $a Includes bibliographical references
520 $a Reliable workflow is critical in enhancing the construction industry's overall productivity. A reliable workflow can be achieved by ensuring that communication flows smoothly between all specialty trades involved, constraints are removed, and instant feedback is available. Moreover, a transparent and accountable environment can uphold a reliable workflow because all parties can understand their responsibilities, risks, and expected outcomes unambiguously. Recently, the adoption of blockchain technology in construction has emerged as a disruptive trend, providing opportunities to facilitate and decentralize production management through the power of smart contracts. However, the following questions are yet to know: (1) how to investigate the impacts of constraints arising from the specialty trades' variations in terms of project outcomes, (2) how to derive fair profit allocation contract consensus among specialty trades when working in the coalition, and (3) how to integrate semantically rich as-built data to provide automatic project appraisals and instant decision-making to enhance a reliable workflow. This research aims to provide contextualization, incentivization, and digitalization to enhance task-level collaboration reliability using blockchain-enabled smart contracts. Three primary goals are to (1) quantify the interdependent interrelated impacts of project constraints arising from variations in specialty trades on project outcomes, (2) derive a fair benefit distribution method among specialty trades when working in a collaborative work setting, and (3) integrate semantically rich as-built images to automate smart contract executions.First, the research selected a modular construction project to investigate the impact of specialty trades' variations on the project's duration and costs. A simulation model was deployed, and the resulting profits were encoded in smart contracts as incentive-penalty sharing rules. These rules were designed to enforce a higher level of performance among specialty trades, thereby ensuring reliable constraint removal. To record and share as-built images as unique evidence for performance verification, an InterPlanetary File System (IPFS)-based approach was integrated into the framework. Next, the research combined and permutated various collaborative variables for three specialty trades, generating 27 scenarios in simulation. The Shapley value was then applied to aggregate the outcomes and determine the fair benefit-sharing mechanism, which was subsequently embedded in smart contracts and tested in various scenarios to validate the effectiveness and efficiency of the developed framework. Lastly, a high-rise residential building was selected, and as-built image data was collected. To classify the as-built image into different progress categories, a deep learning model was developed for blockchain oracle development. Furthermore, the research analyzed the various impacts of prerequisite delays in-depth and identified optimal mitigation strategies. Ultimately, a decentralized application was developed, which synchronizes as-built images, classified results, and mitigation strategies to enable automatic smart contract executions.The first case study revealed that reliable constraint removal leads to substantial reductions in wait time for equipment and labor, resulting in an overall cost savings of 4.7% compared to the benchmark scenario. For example, the removal of material constraints resulted in a 45.7% and 78.5% reduction in equipment and labor wait times, respectively. Additionally, the use of simulation to convert implicit construction dynamics into explicit contract consensus facilitated the adoption of smart contracts in the construction industry.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Web studies. $3 1148502
650 4 $a Information technology. $3 559429
650 4 $a Decision making. $3 528319
650 4 $a Building information modeling. $3 805456
655 7 $a Electronic books. $2 local $3 554714
690 $a 0543
690 $a 0489
690 $a 0646
710 2 $a North Carolina State University. $3 845424
710 2 $a ProQuest Information and Learning Co. $3 1178819
773 0 $t Dissertations Abstracts International $g 85-06A.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30727236 $z click for full text (PQDT)