42127 Digital Engineering for Infrastructure and Facilities
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Subject handbook information prior to 2024 is available in the Archives.
Credit points: 12 cp
Result type: Grade and marks
There are course requisites for this subject. See access conditions.
Recommended studies:
A background in engineering or construction related disciplines, or one year of relevant work experience on infrastructure construction projects, and basic familiarity with general CAD or BIM concepts is recommended for participants in this course.
Description
Digital Engineering for Infrastructure and Facilities addresses an industry-recognised need for contemporary civil infrastructure projects. It equips participants with a theoretical foundation and practical skills through engagement with industry best practices, workflows, and real-world datasets. Key areas covered include Common Data Environments, Survey and Existing Conditions Modelling, Design Coordination, and Quantity Take-Off for Planning, Cost and Carbon Estimation. On successful completion participants are well-prepared to take a leading role in the digital delivery of infrastructure and building projects, making them more efficient, effective, and adaptable to the evolving needs of modern methods of construction.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
| 1. | Establish and manage infrastructure projects by effectively incorporating digital engineering principles, tools, and techniques. (D.1) |
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| 2. | Consider best practice approaches for effectively communicating and collaborating with project teams and stakeholders throughout infrastructure projects. (E.1) |
| 3. | Apply information management strategies and tools to design and establish a common data environment for infrastructure and building projects. (C.1) |
| 4. | Interpret and manage multiple data sources to create comprehensive digital representations of infrastructure sites, ensuring accuracy and relevance. (D.1) |
| 5. | Implement and evaluate effective design coordination strategies using digital tools and methodologies to resolve discrepancies and ensure data integrity. (D.1) |
| 6. | Accurately extract model-based take-offs facilitating detailed project planning, costings and carbon measurement for data-driven decision-making. (B.1) |
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):
- Socially Responsible: FEIT graduates identify, engage, and influence stakeholders, and apply expert judgment establishing and managing constraints, conflicts and uncertainties within a hazards and risk framework to define system requirements and interactivity. (B.1)
- Design Oriented: FEIT graduates apply problem solving, design thinking and decision-making methodologies in new contexts or to novel problems, to explore, test, analyse and synthesise complex ideas, theories or concepts. (C.1)
- Technically Proficient: FEIT graduates apply theoretical, conceptual, software and physical tools and advanced discipline knowledge to research, evaluate and predict future performance of systems characterised by complexity. (D.1)
- Collaborative and Communicative: FEIT graduates work as an effective member or leader of diverse teams, communicating effectively and operating autonomously within cross-disciplinary and cross-cultural contexts in the workplace. (E.1)
Contribution to the development of graduate attributes
This subject contributes to the development of the following Engineers Australia Stage 1 Competencies:
- 1.3 In-depth understanding of specialist bodies of knowledge within the engineering discipline.
- 1.5 Knowledge of engineering design practice and contextual factors impacting the engineering discipline.
- 2.1 Application of established engineering methods to complex engineering problem solving.
- 2.2 Fluent application of engineering techniques, tools and resources.
- 2.3 Application of systematic engineering synthesis and design processes.
- 2.4 Application of systematic approaches to the conduct and management of engineering projects.
- 3.4 Professional use and management of information.
- 3.5 Effective oral and written communication in professional and lay domains.,
- 3.6 Effective team membership and team leadership.
Teaching and learning strategies
The subject is delivered in four blocks and utilises a mixture of workshops, online computing studios, and independent online learning activities to support student learning. With the aim of developing digital engineering knowledge and practical skills, students will utilise project-based learning, industry case studies, and real-world datasets. Engaging in regular pre-class activities and working through the five assessment tasks build essential knowledge in the implementation of consistent and consolidated digital engineering workflows that support the collaborative production and management of project information. Visual and model-based methods are used to communicate information workflows and engage student learning. Each week students are expected to prepare for workshops and computing labs by completing a set of pre-class tasks. The tasks involve activities such as reading from key resources, watching videos, and other online learning content. Responses to the pre-class tasks are used in online tutorial classes to add depth to discussion and are an essential component of the subject. During the online computing labs, students will build on pre-class tasks to learn and apply concepts with the aim being to develop skills across the four key areas of digital engineering covered by this subject. These skills will be practiced in online studios and are designed to be relevant to the assessment tasks. Areas of learning in workshops and computing studios will include group discussion and technical Q&A sessions related to assessment task activities. Teaching and learning strategies are designed to support the acquisition of digital engineering skills in a group setting under the supervision of an industry mentor, with these skills relating directly to the substantive summative assessment tasks.
Content (topics)
Block 1: Digital Strategy, Setup & Collaboration
Participants will develop skills in creating a unified, shared project vision to ensure coordination across disciplines, collaborative teamwork, and minimisation of potential conflicts. Participants also build practical skills in the setup of master data management schemas and tools, and establishing and effectively utilising a Common Data Environment, supporting data creation, validation, sharing, and updating of workflows. This block therefore focuses on the role of communication, selection of technology, and design of digital workflows using a common data environment.
Block 2: Survey and Existing Conditions Modelling
This block introduces participants to the intricacies of surveying and modelling existing conditions, cultivating practical knowledge across several pivotal topics essential to the implementation of digital engineering in linear infrastructure projects, including: Site, GIS & Base Map Data; Digital Survey (Digital Terrain Modelling); Managing Point Cloud & GIS Data; Geo-referencing and Model Setout.
Block 3: Design Coordination
In this block you will develop your expertise in design coordination covering the essentials of coordinating infrastructure systems, including streamlined multidisciplinary coordination, identifying and resolving discrepancies early and minimising errors. You will acquire the skills to verify and validate project data, ensuring accuracy, relevance, and completeness, and navigate the common challenges in data management, including understanding how to maintain data integrity throughout the project lifecycle. You will delve into the structured process of reviewing technical designs, ensuring they meet project specifications, standards, and stakeholder expectations, and learn how to facilitate collaborative design reviews, gather feedback, and make informed adjustments to designs, promoting project success.
Block 4: Quantity Take-Off for Planning, Cost and Carbon
The focus of this block is on model- based quantity take-off and is tailored to equip participants with the skills and knowledge required to harness Digital Engineering and 3D models to support the quantification of project essentials, facilitating planning, cost and carbon estimating. Participants will dive into the nuances of extracting accurate quantity take-offs from 3D models, facilitating detailed project planning, near real-time cost updates as the design evolves, and the innovative use of 3D models for carbon measurement.
Assessment
Assessment task 1: Implementing a CDE
| Intent: | To successfully design and implement an individual instance of a functioning common data environment, that satisfactorily hosts the digital models provided, demonstrates evidence of the required assessment workflows, and captures the results in a series of reports exported from the dashboard of the common data environment. |
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| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2 and 3 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): C.1, D.1 and E.1 |
| Type: | Laboratory/practical |
| Groupwork: | Individual |
| Weight: | 20% |
| Length: | Your submission should a visually rich document and be of an appropriate length to document the practical tasks undertaken and their outputs. As a guide your submission should be no longer than 6-10 pages, not including front cover and references. |
Assessment task 2: Evaluating site and existing conditions data
| Intent: | To assess and ensure the scope, control and integrity of survey and existing conditions modelling data across various stages of the project. |
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| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2 and 4 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): D.1 and E.1 |
| Type: | Case study |
| Groupwork: | Individual |
| Weight: | 20% |
| Length: | Your submission should be a visually rich document and be of an appropriate length to document the practical tasks undertaken and their outputs. As a guide your submission should be no longer than 6-10 pages, not including front cover and references. |
Assessment task 3: Detecting and Reporting on Clash and Data Validation Issues
| Intent: | To build technical and management skills to identify clash and data validation issues about discipline-specific models, ensuring the design coordination of infrastructure or building systems. |
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| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2 and 5 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): D.1 and E.1 |
| Type: | Report |
| Groupwork: | Group, group and individually assessed |
| Weight: | 20% |
| Length: | Your submission should be a visually rich document and be of an appropriate length to document the practical tasks undertaken and their outputs. As a guide your submission should be no longer than 6-10 pages, not including front cover and references. |
Assessment task 4: Extracting and Evaluating Quantities for Planning, Cost and Carbon Estimating
| Intent: | To gain insights into the intricacies of model-based scheduling, cost estimation, and carbon calculation, by grouping quantities from discipline-specific datasets. |
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| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2 and 6 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): B.1, D.1 and E.1 |
| Type: | Report |
| Groupwork: | Individual |
| Weight: | 20% |
| Length: | Your submission should be a visually rich document and be of an appropriate length to document the practical tasks undertaken and their outputs. As a guide your submission should be no longer than 6-10 pages, not including front cover and references. |
Assessment task 5: Online Graded Activities
| Intent: | To test your understanding of the course content through graded online activities and receive ongoing formative feedback. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 3, 4, 5 and 6 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): B.1, C.1, D.1 and E.1 |
| Type: | Quiz/test |
| Groupwork: | Individual |
| Weight: | 20% |
| Length: | Four quizzes, reflections, or discussions will be provided throughout the course following the completion of each Block. |
Minimum requirements
In order to pass the subject, a student must achieve an overall mark of 50% or more. Students must submit all assessment tasks. Students who do not submit all assessment tasks may be referred to the Responsible Academic Officer and a fail recorded for the subject (Student Rule 3.8.2)
Recommended texts
Recommended texts will be provided as part of a Reading Lists that will accompany the delivery of each Block’s workshops and computing studios.