Industry Partners

AIMM stands for 'Agents for Improved Maintenance Management.' The AIMM system is a prototype tool that has developed the state of the art life cycle modelling of buildings through the linking of a 3D model with maintenance data to allow both the facility manager and the designer to gain access to building maintenance information and knowledge that is currently inaccessible. AIMM integrates data mining agents into the maintenance process to produce timely data for the facility manager on the effects of different maintenance regimes.

Assurance of learning : the role of work integrated learning and industry partners

In the partnering with students and industry it is important for universities to recognize and value the nature of knowledge and learning that emanates from work integrated learning experiences is different to formal university based learning. Learning is not a by-product of work rather learning is fundamental to engaging in work practice. Work integrated learning experiences provide unique opportunities for students to integrate theory and practice through the solving of real world problems. This paper reports findings to date of a project that sought to identify key issues and practices faced by academics, industry partners and students engaged in the provision and experience of work integrated learning within an undergraduate creative industries program at a major metropolitan university. In this paper, those findings are focused on some of the particular qualities and issues related to the assessment of learning at and through the work integrated experience. The findings suggest that the assessment strategies needed to better value the knowledges and practices of the Creative Industries. The paper also makes recommendations about how industry partners might best contribute to the assessment of students’ developing capabilities and to continuous reflection on courses and the assurance of learning agenda.

Work integrated learning : an industry partners’ perspective

In recent years the Australian tertiary education sector may be said to be undergoing a vocational transformation. Vocationalism, that is, an emphasis on learning directed at work related outcomes is increasingly shaping the nature of tertiary education. This paper reports some findings to date of a project that seeks to identify the key issues faced by students, industry and university partners engaged in the provision of WIL within an undergraduate program offered by the Creative Industries faculty of a major metropolitan university. Here, those findings are focussed on some of the motivations and concerns of the industry partners who make their workplaces available for student internships. Businesses are not universities and do not perceive of themselves as primarily learning institutions. However, their perspectives of work integrated learning and their contributions to it need to understand more fully at practical and conceptual levels of learning provision. This paper and the findings presented here suggest that the diversity of industry partner motivations and concerns contributing to WIL provision requires that universities understand and appreciate those partners as contributors with them to a culture of learning provision and support. These industry partner contribution need to be understood as valuing work as learning, not work as something that needs to be integrated with learning to make that learning more authentic and thereby more vocational.

Wrong way, go back! Negotiating success in industry-based research

Literature addressing methodological issues in organisational research is extensive and multidisciplinary, encompassing debates about methodological choices, data-collection techniques, epistemological approaches and statistical procedures. However, little scholarship has tackled an important aspect of organisational research that precedes decisions about data collection and analysis – access to the organisations themselves, including the people, processes and documents within them. This chapter looks at organisational access through the experiences of three research fellows in the course of their work with their respective industry partners. In doing so, it reveals many of the challenges and changing opportunities associated with access to organisations, which are rarely explicitly addressed, but often assumed, in traditional methods texts and journal publications. Although the level of access granted varied somewhat across the projects at different points in time and according to different organisational contexts, we shared a number of core and consistent experiences in attempting to collect data and implement strategies.

High-risk, high-stake relationships: building effective industry-university partnerships for Work Integrated Learning (WIL)

Many industry peak and professional bodies advocate students undertake professional work placements as a key work integrated learning (WIL) experience in accredited university degree courses. However, mismatched expectations and gaps in the way industry partners (IPs) are supported during these work placements can place these high-stake alliances at risk. A review of models and strategies supporting industry partners indicates many are contingent on the continued efforts of well-networked individuals in both universities and IP organisations to make these connections work. It is argued that whilst these individuals are highly valued they often end up representing a whole course or industry perspective, not just their area of expertise. Sustainable partnership principles and practices with shared responsibility across stakeholder groups are needed instead. This paper provides an overview of work placement approaches in the disciplines of business, engineering and urban development at an Australian, metropolitan university. Employing action research and participatory focus group methodologies, it gathers and articulates recommendations from associated IPs on practical suggestions and strategies to improve relationships and the resultant quality of placements.

Talking across the fence : partners for art education

This presentation explores a model for building and sustaining secondary – tertiary partnerships in Arts education. It traces the evolution of partner relationships in a challenging educational landscape, assesses the value of dialogue between educators, design professionals and community stakeholders, and tells the story of a particular secondary – tertiary partnership exploring new pedagogy in Art and Design, between Kelvin Grove State College, the School of Design Creative Industries Faculty of QUT, and the Design Minds program of the State Library of Queensland. Among other benefits, tertiary and industry partners have brought a myriad of diverse voices into the classrooms, enabled the direct interaction of learners with tertiary student mentors, and with art and design practitioners. The working model has also now matured into formal and informal partner agreements that help guarantee its viability into the future. This presentation, which deals with the opening of new terrain between committed partners, is also the story of how design has gradually been integrated in the curriculum, enriching and expanding the repertoire of Art programs, and how one Visual Art Faculty in a large inner city Brisbane School has adopted design thinking and “metadesign” as a model for future innovation. From the process of interaction and dialogue among educators and practitioners over several years has emerged a conviction that both partnering and design pedagogy are key tools in developing forward thinking curriculum for the Arts. In addition, hammering out a model that works for students across different year levels and in diverse settings by putting ideas into practice and micro-managing this process in studios and workshops has challenged teachers to rethink their own Art pedagogy. Finally, in the ecosystem of Schools and in the wider systems that are now driving change in education, survival for the Arts may depend on the networking and affirmation derived from innovating partners. Our story, the story of committed individuals who have sustained a dialogue across boundaries, may provide a valuable model for other arts educators fighting to retain agency in their schools.

The ceiling to coproduction in university-industry research collaboration

The purpose of this paper is to provide insight into government attempts at bridging the divide between theory and practice through university-industry research collaboration modelled under engaged scholarship. The findings are based on data sourced from interviews with 47 academic and industry project leaders from 23 large scale research projects. The paper demonstrates a ceiling to the coproduction of knowledge arising from the preconceived beliefs of both academics and industry partners regarding project roles and responsibilities. The findings show that coproduction was constrained by academic partners assuming control over much of the research activities and industry partners failing to confront or challenge academic decision-making because both academics and industry partners placed a higher value on academic knowledge compared with applied or practical knowledge. It is argued the theory of engaged scholarship, and consequent initiatives to encourage engaged scholarship, fail to account for the superior status of academic knowledge.

Facing up to the risks in commercially focused university-industry R&D partnerships

The number of university–industry R&D partnerships (UIPs) has increased significantly over the past decade, in most OECD countries and in Australia, yet the study of risk in such commercially focused collaborative ventures is still a developing area. This review paper seeks to contribute to debate on this increasingly important phenomenon by addressing three key areas of risks for universities in entering such collaborations. The commercialization of research findings presents particular risks to universities, most notably the possibility of financial loss, which has a greater impact than for companies in cross‐sector collaborations. Another major type of risk faced by universities is relational risk, and this can significantly alter the trust dynamics that underpin research and innovation. There are also institutional risks to universities and their research staff engaged in commercializable R&D and, ultimately, to their reputation as a neutral source of expertise. It is argued there is a need for universities in Australia to develop comprehensive policies to manage the risks of commercialization and R&D collaboration with industry partners.

Project-oriented design-based learning: aligning students’ views with industry needs

This paper focuses on the alignment of students' views on project-oriented design-based learning (PODBL) with today's industrial needs. A Collaborative relationship between academic institutions and industrial expectations is a significant process towards analytical thinking (linking the theory and practice). Improving students' knowledge as well as the students' transition into industry, requires efficient joint ventures by both learning institutions and industry partners. Project-based learning (PBL) is well developed and implemented in most engineering schools and departments around the world. What requires closer attention is the focus on design within this project-based learning framework. Today design projects have been used to motivate and teach science in elementary, middle, and high school classrooms. They are also used to assist students with possible science and engineering careers. For these reasons, design-based learning (DBL) is intended to be an effective approach to learning that is centered on a design problem-solving structure adopted for a problem-oriented project-based education. Based on an industry design forum, which the authors conducted in Melbourne, Australia in 2012, a research study was performed to investigate the industry and academic requirements for students focusing on achieving design skills. To transform the present situation in the academic teaching and learning environment and to fulfill industry needs, this research study also investigated the students' views on design skills.

How does the healthcare industry involve users in medical device development? Pointers for UbiHealth

This paper introduces the Multidisciplinary Assessment of Technology Centre for Healthcare (MATCH) and outlines the problem of integrating a user-centred approach for development of medical devices together with the information and communication technology environments in which they are increasingly required to operate. We highlight some of the regulatory requirements that are relevant to user needs consideration in medical device development. Finally, we reveal a range of limitations in the current practice of the medical device industry in the area of user needs capture, based on responses from interviews with MATCH’s industry partners.

Knowmore (House of Commons)

Knowmore (House of Commons) is a large scale generative interactive installation that incorporates embodied interaction, dynamic image creation, new furniture forms, touch sensitivity, innovative collaborative processes and multichannel generative sound creation. A large circular table spun by hand and a computer-controlled video projection falls on its top, creating an uncanny blend of physical object and virtual media. Participants’ presence around the table and how they touch it is registered, allowing up to five people to collaboratively ‘play’ this deeply immersive audiovisual work. Set within an ecological context, the work subtly asks what kind of resources and knowledges might be necessary to move us past simply knowing what needs to be changed to instead actually embodying that change, whilst hinting at other deeply relational ways of understanding and knowing the world. The work has successfully operated in two high traffic public environments, generating a subtle form of interactivity that allows different people to interact at different paces and speeds and with differing intentions, each contributing towards dramatic public outcomes. The research field involved developing new interaction and engagement strategies for eco-political media arts practice. The context was the creation of improved embodied, performative and improvisational experiences for participants; further informed by ‘Sustainment’ theory. The central question was, what ontological shifts may be necessary to better envision and align our everyday life choices in ways that respect that which is shared by all - 'The Commons'. The methodology was primarily practice-led and in concert with underlying theories. The work’s knowledge contribution was to question how new media interactive experience and embodied interaction might prompt participants to reflect upon the kind of resources and knowledges required to move past simply knowing what needs to be changed to instead actually embodying that change. This was achieved through focusing on the power of embodied learning implied by the works' strongly physical interface (i.e. the spinning of a full size table) in concert with the complex field of layered imagery and sound. The work was commissioned by the State Library of Queensland and Queensland Artworkers Alliance and significantly funded by The Australia Council for the Arts, Arts Queensland, QUT, RMIT Centre for Animation and Interactive Media and industry partners E2E Visuals. After premiering for 3 months at the State Library of Queensland it was curated into the significant ‘Mediations Biennial of Modern Art’ in Poznan, Poland. The work formed the basis of two papers, was reviewed in Realtime (90), was overviewed at Subtle Technologies (2010) in Toronto and shortlisted for ISEA 2011 Istanbul and included in the edited book/catalogue ‘Art in Spite of Economics’, a collaboration between Leonardo/ISAST (MIT Press); Goldsmiths, University of London; ISEA International; and Sabanci University, Istanbul.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Evaluation of functional performance in commercial buildings

This report fully summarises a project designed to enhance commercial real estate performance within both operational and investment contexts through the development of a model aimed at supporting improved decision-making. The model is based on a risk adjusted discounted cash flow, providing a valuable toolkit for building managers, owners, and potential investors for evaluating individual building performance in terms of financial, social and environmental criteria over the complete life-cycle of the asset. The ‘triple bottom line’ approach to the evaluation of commercial property has much significance for the administrators of public property portfolios in particular. It also has applications more generally for the wider real estate industry given that the advent of ‘green’ construction requires new methods for evaluating both new and existing building stocks. The research is unique in that it focuses on the accuracy of the input variables required for the model. These key variables were largely determined by market-based research and an extensive literature review, and have been fine-tuned with extensive testing. In essence, the project has considered probability-based risk analysis techniques that required market-based assessment. The projections listed in the partner engineers’ building audit reports of the four case study buildings were fed into the property evaluation model developed by the research team. The results are strongly consistent with previously existing, less robust evaluation techniques. And importantly, this model pioneers an approach for taking full account of the triple bottom line, establishing a benchmark for related research to follow. The project’s industry partners expressed a high degree of satisfaction with the project outcomes at a recent demonstration seminar. The project in its existing form has not been geared towards commercial applications but it is anticipated that QDPW and other industry partners will benefit greatly by using this tool for the performance evaluation of property assets. The project met the objectives of the original proposal as well as all the specified milestones. The project has been completed within budget and on time. This research project has achieved the objective by establishing research foci on the model structure, the key input variable identification, the drivers of the relevant property markets, the determinants of the key variables (Research Engine no.1), the examination of risk measurement, the incorporation of risk simulation exercises (Research Engine no.2), the importance of both environmental and social factors and, finally the impact of the triple bottom line measures on the asset (Research Engine no. 3).