Keith grew up in Gisborne, and has lived in Wairoa and Wellington, however, Napier is where he has spent much of his life. As a fifth Term Napier City Councillor, he can confidently say that the prosperity of this community has been a priority for him. Many people in the community know him through his 28 year career as a Detective Sergeant in the NZ police, his years of commitment to sport through both rugby and basketball, as well as his operation of a successful Ahuriri hospitality business. During his time with Council, and as the Chair of Council’s Infrastructure and Strategy Committee, he has championed significant projects for the community with a focus on revitalising Napier city. He led the Marine Parade design and development, pathway extensions, city vision and moving of the weigh bridge. He has also worked hard to advocate for residents on issues like freedom camping, water improvements and the reinstatement of the War Memorial.
The term “Fourth Industrial Revolution” was only coined as late as 2016 by Schwab during the World Economic Forum in Davos. Now – a mere three years later – the scale, speed and impact of new technologies, built around artificial intelligence (AI), machine learning, robotics, the Internet of Things (IoT), big data, autono- mous vehicles, additive manufacturing and biotechnology, are changing our industry and the world completely. The previous three industrial revolutions had a significant impact on engineering, but this revolution is larger and faster than before and will significantly disrupt many engineering activities.
The wide spectrum of digital disruptions facing the fraternity can be viewed as either a threat or an opportunity to reposition ourselves.
A threat, because we know that any repeatable activity (and there are many of them in engineering) can and will eventually be machine learnt. This will threaten many jobs we currently do and drastically change our industry.
An opportunity, because this inevitable, digital rich future will change the role of the engineer. By embracing and adapting to this digital future, engineers can apply their skills wider and deeper than ever before. Our future will depend on how well we offer our craft, structure our businesses, integrate diverse skills, connect to society and prepare our young professionals to thrive in the digital age.
It is not enough to merely digitise (making information available in digital format). Neither will it be enough to digitalise (using this digital information to automate operations).We should strive for digital transformation – where we holistically change organizational activities, processes, competencies, and models to obtain maximum leverage from the mix of digital technology opportunities and their increasing impact on society. Our deep scientific and mathematical skills place engineers in a unique position to strongly contribute in a digitally rich future
Gustav is a graduate from Stellenbosch where he graduated with a BEng in 1984. He is a professional engineer with a master’s degree and PhD from Texas A&M in the USA.
In his professional career he has been actively involved in highway and rehabilitation design. He specialized in the analysis of non-destructive pavement testing and long-term performance modelling. He led the implementation of several road management systems in sub-Saharan Africa and Asia.
Over the last 18 years he has served on the Executive of Aurecon, an engineering consultancy with 7000 employees operating in Australasia, Africa, Asia, the Middle East. He fulfilled the leadership roles of MD, CEO and the last 10 years as global COO of Aurecon.
Gustav has a very keen interest in digital transformation and the impact of the 4th Industrial revolution on engineering and the societies we serve. He currently serves on the Advisory boards of the engineering faculties of the University of Stellenbosch and Cape Town. He has been a Fellow of the South African Academy of Engineers since 2011.
Stephen is a professional company director and an expert in infrastructure vision, strategy and public policy.
He currently serves as a member of the board of the New Zealand Infrastructure Commission – Te Waihanga, a director of Selwood Infrastructure a providing strategy advice to the infrastructure sector and is managing director of Rapt Ltd an online and bricks and mortar retail gift, decor and fashion business based in Auckland.
In his former role as founding Chief Executive of Infrastructure New Zealand Stephen has a proven record of leading and influencing policy at the highest level from Ministers in Government to industry leaders. This includes galvanising support from disparate public and private sector parties into a common vision centred on national benefit.
Stephen describes himself as a thought leader and change agent and brings deep understanding of integrated urban development and infrastructure planning, funding and delivery.
New Zealand has an aging infrastructure network with many iconic and heavily used bridges. It is commonly assumed by Asset Owners that, at the end of their original design life, bridges are in immediate need of replacement. WSP Opus have developed systems with our clients and industry partners to determine the true remaining structural capacity for current and future loads. By managing corrosion, carrying out detailed condition inspections and structural assessments, we can provide a full health-check of the asset. However, the main question that needs to be answered before assessing the state of an asset owner’s bridge stock is – where to start?
This presentation will outline an answer to this question in the form of a Bridge Risk Prioritisation Tool. The tool uses a scoring system based on a core set of characteristics that are common to all bridges, and another set which is variable.
Kyle is a Bridge Engineer located in Napier, New Zealand, with a Bachelor and master’s in civil engineering. Kyle has developed his astute civil engineering skills since working in the profession. Initially working as a contractor in the UK for 2 years, he expanded his engineering skills to include those of bridge strengthening design and now has 5 years of experience.
Since moving to New Zealand, Kyle has tailored and enhanced these skills primarily in bridge strengthening designs and structural asset management.
The NZ Transport Agency manages the maintenance and renewal of the State Highway Network from a road safety, asset management and value for money perspective. But how well is the Network being managed from a customer point-of-view? This question led the Agency to work with Lonrix Ltd in developing a custom ranking algorithm where the Network was analysed with an emphasis on customer perception, the results for which were to be displayed geo-spatially. In the analysis, road condition and maintenance data was used to approximate the customer experience via three categories: Customer Safety (skid resistance and texture), Customer Comfort (roughness), and Customer Inconvenience (maintenance). The presentation will focus on the mechanics behind the algorithm, ranking and mapping functionality; and we will discuss a few interesting findings…
Philip started his civil engineering career working in the contracting environment, where he was involved in PSMC and NOC contracts. During this time he also studied towards and completed his Diploma in Civil Engineering. Since 2015 he has worked for Lonrix Limited, where he manages projects and customer support for the JunoViewer Asset Management framework. Philip is experienced in data analysis and works with many engineering clients in New Zealand and overseas to design and create software features and developments, some of which are specifically tailored for the NOC contract domain.
Central Otago has come to the realisation that we are finding unexpected early failure of some surfacing types – So we have been busy digging deeper into the data and around the network to better understand the cause, effect on expected life, and potential techniques to prolong the life achieved.
Over the last year we have noticed that certain surfaces have been showing significant signs of distress and early failure, a large portion of our post winter RAPA. A consistent factor recognised early on was that they seemed to fit a time period from approx. 2009-2014. As we dug deeper we also started to recognise that the surfacing types were starting to show some consistencies.
As we continue to delve into the techniques used and the resulting effects we look to the future and what impacts this will have on the network long term including trialling techniques to minimise the chip loss and gain surface life prior to renewal being required.
This study is ongoing and the results are currently unknown however we aim to have the initial research completed this season which times well for the 2020 conference.
Ben has been involved with asset management in some shape or form for the past 14 years. Learning the various disciplines of engineering that support the data driven decision making that asset management uses to form our FWPs.
The pavement deterioration modelling space has been explored for over 20 years now, and there are still advancements being made in the modelling space. The growth of the technical capital in this space has increased dramatically in recent years due to advancements in data and technology. However, how can we ensure that all the useful output from our various models are being delivered effectively to the client?
In recent years, the primary challenge has not been getting the results – it has been ensuring that these results are understood and are being addressed appropriately. It has been about “telling the story”.
This presentation will briefly touch upon the deterioration modelling process but focus on covering a variety of strategies and analyses that WSP has employed to discuss the changes in the bigger picture and facilitate a shift in the overall strategy. Some of these analyses are more complex, such as a base preservation study in dTIMS, while others are straight forward. Every aspect of the data has its own role in the overall story for the network.
Kevin is a Graduate Asset Management Engineer at WSP, coming from an University of Auckland Engineering Science background. He has worked a civil engineering consultancy specialising in land development before joining WSP in the Transport Asset Management field. He has gained experience in Forward Works Programming, dTIMS Modelling, Statistical Models, and Asset Valuation over the past two years.
Robust NZ models were established in 2008, based on 7 years of LTPP data. Demand on our network has dramatically changed over the past 10 years. As part of the 2021 NLTP project, the IDS rutting models have been updated using the latest LTPP data.
The probabilistic accelerated rutting model and linear rut progression models were investigated and updated. New variables and model forms were explored as well as recalibration of the existing formats. The best performing models were chosen for testing on network data. The final models showed a considerable improvement on their predecessors and were coded into the NLTP dTIMS template. These models will be released nationally in the IDS NZ dTIMS template.
The probabilistic crack initiation model for chipseal was also investigated during this project. Ultimately it was decided not to make changes to this model while the country transitions from visual to laser data collection.
Key findings from this projects include:
- Data is an asset and should be maintained as such.
- Simplicity is key.
- SNP is stubborn.
Gemma is the IDS Helpdesk Manager and a Senior Asset Information Engineer at WSP. Gemma is highly regarded for her skills in Asset Management, Project Management, Quality Management, RAMM Management, data analysis and analytics, and dTIMS expertise. With a Bachelor of Engineering in Engineering Science and Masters in Transportation, Gemma has the skills to implement efficient methods to quickly and effectively process, analyse and manage datasets and provide reporting outcomes.
This presentation will describe efforts to utilise machine learning techniques, coupled with high speed condition data to construct a prediction model for future treatments.
The approach adopted has used treatment assignment outcomes from previous field inspections and detailed investigations. These assigned treatments were used as a labelled training set for the machine learning algorithm to test.
Several machine learning techniques are being explored, such as Nearest Neighbour (kNN), Decision Tree and Naïve Bayes models.
At this early stage of development, the Naïve Bayes model is providing the most consistent results.
The work is being carried out within the JunoViewer framework, and will be incorporated into the software after testing and calibration of the findings.
Sean Rainsford works for Fulton Hogan as the Technical Asset Manager within the National Asset Management support team. Sean has been involved with data and pavement modelling for over 15 years, Sean was a part of the implementation of the dTIMS software into NZ. Sean’s passion is data and applicability to the real world. After driving many of the roads of New Zealand for over 20 years, and seeing the results of many forecasting outcomes, Sean has learnt that data is always the key!