A Generative AI-Enabled Design Tool: Analysing problematic projects for improved productivity and cost efficiency

支持人工智能的生成设计工具：分析有问题的项目以提高生产力和成本效率

• 批准号: 10077663
• 金额: $ 8.82万
• 依托单位: ZEST CONSULT LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10077663
• 关键词: Generative; AI; Enabled; Design; Tool

This proposal is a **feasibility study** exploring a novel Generative AI approach addressing the critical construction challenge of time and cost overruns caused by re-work.**Project entails the following activities**:* Explore feasibility of developing an AI-enabled design tool as a solution using data from previous projects to analyse problematic projects identifying issues requiring additional oversight and management to avoid re-work and time/cost overruns.* Provide AI expertise in developing/deploying Applied AI solutions for construction industry through collaboration between a party in need of the solution and a party that can develop it.Critical factors limiting improvements in productivity in the construction industry are time and cost overruns due to unforeseen challenges and re-work. This project has the potential to unlock huge productivity improvements.**Areas of focus**Our project focuses on the following themes:**Data Driven Decision Making:*** **_Better project delivery_**: using past project data and industry wide benchmarks to develop estimators for accurate project plans; reducing likelihood of delays/cost overruns.* **_Enhanced safety_**: using data to identify safety risks and proactive mitigating measures.* _**Quality control**_: using data to monitor quality of workmanship on construction projects to meet quality standards and avoid rework.**Design:*** _**Generative design**_: using AI to generate new design options based on set parameters/constraints.* **_Analysing problematic projects_**: using AI to analyse data from previous construction projects to identify patterns and predict future outcomes.InnovationsOur project sets the foundations for developing a Generative AI-enabled design tool to analyse problematic projects using data recorded by construction companies; offering valuable insights enables them to take proactive measures, allocate resources effectively, make informed decisions to mitigate risks; resulting in overall improved outcomes, productivity, and cost efficiency.Our solution provides a step-change on how AI solutions are applied in the construction industry from a siloed problem-specific approach to a holistic system-based approach.**Relevance**Our project explores suitability of using Generative AI-enabled systems for the following capabilities:1. **Data analysis**: analyse large volumes of project data; identifying patterns/anomalies.2. **Risk prediction**: analyse historical project data; identifying/predicting risks/hazards likely leading to problematic projects.3. **Real-Time Monitoring**: monitoring ongoing construction projects by integrating data; detecting deviations from the project plan.4. **Natural Language Processing**: analyse textual project documentation data; extracting valuable insights.5. **Benchmarking/Comparative Analysis**: compare project data with industry benchmarks/best practices; identifying projects performing below expectations or at higher cost/time overrun risks.6. **Human-in-the-Loop**: explore inclusion of humans in guiding AI processes and influencing results.

该提案是一项**可行性研究**，探索一种新颖的生成人工智能方法，解决返工造成的时间和成本超支的关键施工挑战。**项目需要进行以下活动**：*探索开发人工智能的可行性启用设计工具作为解决方案，使用以前项目的数据来分析有问题的项目，识别需要额外监督和管理的问题，以避免返工和时间/成本超支。*通过与需要解决方案的一方和限制建筑行业生产率提高的关键因素是由于不可预见的挑战和返工而导致的时间和成本超支。该项目有潜力实现巨大的生产力提高。**重点领域**我们的项目重点关注以下主题：**数据驱动决策：*** **_更好的项目交付_**：使用过去的项目数据和行业广泛的基准来开发准确的项目计划的估算器；减少延误/成本超支的可能性。* **_增强安全性_**：使用数据来识别安全风险和主动缓解措施。* _**质量控制**_：使用数据来监控建筑项目的工艺质量，以满足质量要求**设计：*** _**生成式设计**_：使用人工智能根据设置的参数/约束生成新的设计选项。* **_分析有问题的项目_**：使用人工智能分析来自之前的施工创新我们的项目为开发生成式人工智能设计工具奠定了基础，该工具可以使用建筑公司记录的数据来分析有问题的项目；提供有价值的见解，使他们能够采取主动措施、有效分配资源、做出明智的决策来降低风险；从而全面提高成果、生产力和成本效率。我们的解决方案为人工智能解决方案在建筑行业的应用方式提供了逐步改变，从孤立的特定问题方法到基于整体系统的方法。**相关性**我们的项目探讨了使用生成式人工智能系统实现以下功能的适用性：1。 **数据分析**：分析大量项目数据；识别模式/异常.2. **风险预测**：分析历史项目数据；识别/预测可能导致问题项目的风险/危害。3． **实时监控**：通过整合数据监控正在进行的建设项目；检测与项目计划的偏差。4． **自然语言处理**：分析文本项目文档数据；提取有价值的见解.5。 **基准/比较分析**：将项目数据与行业基准/最佳实践进行比较；识别绩效低于预期或成本/时间超支风险较高的项目。6． **人在环**：探索人类参与指导人工智能流程和影响结果。