| 1. |
- Cusumano, Linda, 1981, et al.
(författare)
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Current benefits and future possibilities with digital field reporting
- 2024
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Ingår i: International Journal of Construction Management. - 1562-3599. ; In Press
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Tidskriftsartikel (refereegranskat)abstract
- Mobile phones and tablets enable contractors to digitally collect large amounts of production remarks and facilitate the acquisition. The increased data access and machine learning techniques allow the construction industry to take a significant step forward in shifting from implicit to explicit knowledge. However, this step requires both standardisation and data quality assurance combined with project incitements ensuring continuous data collection. Therefore, this study examines the current data quality and standardisation of inspection data generated using the production software Dalux Field, mining a dataset of more than 95000 production issues. Additionally, a survey of production software users assesses project and project member benefits and future possibilities with digital inspection reporting. The results show considerable benefits with digital inspection reporting, such as time savings, cost reductions and increased general quality control. However, the standardisation in reporting between projects and team members is low. Finally, this paper suggests methods for improving data quality and standardization for automation of the data analysis, allowing new projects in project-based organisations to benefit from previous project experiences.
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| 2. |
- Cusumano, Linda, 1981, et al.
(författare)
-
Current benefits and future possibilities with digital field reporting
- 2024
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Ingår i: INTERNATIONAL JOURNAL OF CONSTRUCTION MANAGEMENT. - 1562-3599 .- 2331-2327.
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Tidskriftsartikel (refereegranskat)abstract
- Mobile phones and tablets enable contractors to digitally collect large amounts of production remarks and facilitate the acquisition. The increased data access and machine learning techniques allow the construction industry to take a significant step forward in shifting from implicit to explicit knowledge. However, this step requires both standardisation and data quality assurance combined with project incitements ensuring continuous data collection. Therefore, this study examines the current data quality and standardisation of inspection data generated using the production software Dalux Field, mining a dataset of more than 95000 production issues. Additionally, a survey of production software users assesses project and project member benefits and future possibilities with digital inspection reporting. The results show considerable benefits with digital inspection reporting, such as time savings, cost reductions and increased general quality control. However, the standardisation in reporting between projects and team members is low. Finally, this paper suggests methods for improving data quality and standardization for automation of the data analysis, allowing new projects in project-based organisations to benefit from previous project experiences.
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| 3. |
- Cusumano, Linda, 1981
(författare)
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Data-driven and production-oriented tendering design using artificial intelligence
- 2023
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Construction projects are facing an increase in requirements since the projects are getting larger, more technology is integrated into the buildings, and new sustainability and CO2 equivalent emissions requirements are introduced. As a result, requirement management quickly gets overwhelming, and instead of having systematic requirement management, the construction industry tends to trust craftsmanship. One method for a more systematic requirement management approach successful in other industries is the systems engineering approach, focusing on requirement decomposition and linking proper verifications and validations. This research project explores if a systems engineering approach, supported by natural language processing techniques, can enable more systematic requirement management in construction projects and facilitate knowledge transfer from completed projects to new tendering projects. The first part of the project explores how project requirements can be extracted, digitised, and analysed in an automated way and how this can benefit the tendering specialists. The study is conducted by first developing a work support tool targeting tendering specialists and then evaluating the challenges and benefits of such a tool through a workshop and surveys. The second part of the project explores inspection data generated in production software as a requirement and quality verification method. First, a dataset containing over 95000 production issues is examined to understand the data quality level of standardisation. Second, a survey addressing production specialists evaluates the current benefits of digital inspection reporting. Third, future benefits of using inspection data for knowledge transfers are explored by applying the Knowledge Discovery in Databases method and clustering techniques. The results show that applying natural language processing techniques can be a helpful tool for analysing construction project requirements, facilitating the identification of essential requirements, and enabling benchmarking between projects. The results from the clustering process suggested in this thesis show that inspection data can be used as a knowledge base for future projects and quality improvement within a project-based organisation. However, higher data quality and standardisation would benefit the knowledge-generation process. This research project provides insights into how artificial intelligence can facilitate knowledge transfer, enable data-informed design choices in tendering projects, and automate the requirements analysis in construction projects as a possible step towards more systematic requirements management.
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| 4. |
- Cusumano, Linda, 1981, et al.
(författare)
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Intelligent building contract tendering - potential and exploration
- 2022
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Ingår i: IABSE Symposium Prague, 2022: Challenges for Existing and Oncoming Structures - Report. - Zurich, Switzerland : International Association for Bridge and Structural Engineering (IABSE). ; , s. 1902-1909
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Konferensbidrag (refereegranskat)abstract
- Project tendering is the construction business “Tightrope-walking.” It is a time-limited balance act where technical and business specialists find the best technical proposal at the right price. The purpose and aim of this study were to explore artificial intelligence (AI) in the tender work and to identify challenges and possibilities with data-driven decision-making. An AI work support tool was adopted and used to extract and process client requirements. The tool and digital-work procedure were presented and discussed with tender specialists from a large contractor in a workshop. A two-step survey was performed in connection to the workshop, investigating the potential users' insights and attitudes for implementation. The main result and conclusion were that AI and digitalization could support tendering; however, successfully generating business value will require higher levels of digitalization, well-structured databases, and access to historical project data.
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| 5. |
- Cusumano, Linda, 1981, et al.
(författare)
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Natural language processing as work support in project tendering
- 2022
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Ingår i: Current Perspectives and New Directions in Mechanics, Modelling and Design of Structural Systems. - London : CRC Press. - 9781003348443 ; , s. 1583-1588
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Konferensbidrag (refereegranskat)abstract
- When producing a tender, contractors manually analyze client requirements contained within many different text documents. The combination of requirements lead to crucial design decisions and every decision is related to costs and risks. This study explores the possibility of making the client requirement analysis in design-bid contracts automated to reduce the risk of conceptual design mistakes. The research approach chosen includes developing a work support tool based on natural language processing and analyzing its usefulness through a combination of surveys and a workshop for tendering specialist. The results show that applying digitalized working methods and using artificial intelligence in the tender phase can enable data-informed decision making and generate benchmarking and risk management opportunities. The study contributes to insights regarding automation and digitization possibilities in tender projects and how artificial intelligence tools can be designed for supporting data-driven decisions.
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| 6. |
- Desivyana, Nindya, 1997, et al.
(författare)
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Challenges in the adoption of sustainable criteria in the Swedish property development industry
- 2023
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Ingår i: Procedia Computer Science. - : Elsevier BV. - 1877-0509. ; 219, s. 1752-1759
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Konferensbidrag (refereegranskat)abstract
- The construction industry is facing an increased focus on sustainability and climate neutrality, causing property developers to implement new requirements into the procurement documents, which are also driven by the national agenda. This study explores the current state of sustainability practice among Swedish property developers and identifies the main obstacles to expand further the implementation of the sustainability criteria. How the property developers define and implement sustainability requirements has been assessed through qualitative semi-structured interviews, focusing on sustainability certification systems, Life Cycle Assessment (LCA), and social sustainability. The results show usage of sustainability certification systems for marketing purposes and high awareness and practice of LCA, even though the accuracy of LCA was questioned. This study also identified guideline gaps for circular economy and social sustainability measurements, which could relate to low initiatives from the certification systems.
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