Autonomous hot metal carrier: Navigation and manipulation with a 20 tonne industrial vehicle

This paper reports work on the automation of a hot metal carrier, which is a 20 tonne forklift-type vehicle used to move molten metal in aluminium smelters. To achieve efficient vehicle operation, issues of autonomous navigation and materials handling must be addressed. We present our complete system and experiments demonstrating reliable operation. One of the most significant experiments was five-hours of continuous operation where the vehicle travelled over 8 km and conducted 60 load handling operations. Finally, an experiment where the vehicle and autonomous operation were supervised from the other side of the world via a satellite phone network are described.

Catalytic activity evaluation of industrial Pd/C catalyst via gray-box dynamic modeling and simulation of hydropurification reactor

In this paper, dynamic modeling and simulation of the hydropurification reactor in a purified terephthalic acid production plant has been investigated by gray-box technique to evaluate the catalytic activity of palladium supported on carbon (0.5 wt.% Pd/C) catalyst. The reaction kinetics and catalyst deactivation trend have been modeled by employing artificial neural network (ANN). The network output has been incorporated with the reactor first principle model (FPM). The simulation results reveal that the gray-box model (FPM and ANN) is about 32 percent more accurate than FPM. The model demonstrates that the catalyst is deactivated after eleven months. Moreover, the catalyst lifetime decreases about two and half months in case of 7 percent increase of reactor feed flowrate. It is predicted that 10 percent enhancement of hydrogen flowrate promotes catalyst lifetime at the amount of one month. Additionally, the enhancement of 4-carboxybenzaldehyde concentration in the reactor feed improves CO and benzoic acid synthesis. CO is a poison to the catalyst, and benzoic acid might affect the product quality. The model can be applied into actual working plants to analyze the Pd/C catalyst efficient functioning and the catalytic reactor performance.

Destined to design? How and why Australian women choose to study industrial design

Despite over three decades of legislation and initiatives designed to tackle the traditional gender divide in the science, technology and design fields, only a quarter of the registered architects in Australia are women. There are no statistics available for other design disciplines, with little known about why women choose design as a career path and who or what influences this decision. This qualitative research addresses this knowledge gap, through semi-structured in-depth interviews conducted with 19 Australian women who completed an industrial (product) design degree. Thematic analysis revealed three key themes: childhood aptitude and exposure; significant experiences and people; and design as a serendipitous choice. The findings emphasise the importance of early exposure to design as a potential career choice, highlighting the critical role played by parents, teachers, professionals and social networks.

Studying industrial design : Exploring the experience of female students

Despite a significant increase in the number of women enrolling and graduating from design courses, the reality is that women remain ‘invisible’ in the design profession (Bruce, 1985). Over two decades ago, Bruce and Lewis (1990) argued that women were less likely than men to be designers due to three key gendered hurdles: the completion of a design degree, getting a design job and obtaining success in a design job. This paper focuses specifically on Australian women’s experience of hurdle one: the completion of a design degree, utilising industrial design as a case study. Semi-structured interview questions (exploring issues such as experience in class and the workshop, accessibility of the course and content, types of projects etc) were recorded and transcribed verbatim, with a thematic analysis conducted to better understand women’s experiences in completing their industrial design degree. This paper focuses on one key theme “navigating the design studio”, which comprises of three sub-themes: design skill development, the workshop experience and course evaluation. These findings highlight the need to understand the educational experience to ensure female designers remain motivated and eventually employable.

Industrial Designer

A discussion with Dr Rafael Gomez on Industrial Design for the Nelson Senior Graphics for Queensland Schools publication.

Bioaerosols associated with industrial green waste composting facilities and optimal microbiological indicators

This project developed and assessed a standard operating procedure for monitoring microbiological aerosol levels and dispersal from Australian industrial composting facilities. Development occurred via seasonal monitoring of such operations with evaluation of optimal microbial indicator organisms, sampling and analysis logistics. The resultant procedure allows practical end-user assessment of compost-associated bioaerosol levels, and potential health risks to proximal residential populations encroaching on such composting facilities and on-site industrial operations personnel.

Experiments and experiences with dependability for a large autonomous industrial vehicle

This paper describes the experiences gained performing multiple experiments while developing a large autonomous industrial vehicle. Hot Metal Carriers (HMCs) are large forklift-type vehicles used in the light metals industry to move molten or hot metal around a smelter. Autonomous vehicles of this type must be dependable as they are large and potentially hazardous to infrastructure and people. This paper will talk about four aspects of dependability, that of safety, reliability, availability and security and how they have been addressed on our experimental autonomous HMC.

Applying digital product memories in industrial production

Industrial production and supply chains face increased demands for mass customization and tightening regulations on the traceability of goods, leading to higher requirements concerning flexibility, adaptability, and transparency of processes. Technologies for the ’Internet of Things' such as smart products and semantic representations pave the way for future factories and supply chains to fulfill these challenging market demands. In this chapter a backend-independent approach for information exchange in open-loop production processes based on Digital Product Memories DPMs is presented. By storing order-related data directly on the item, relevant lifecycle information is attached to the product itself. In this way, information handover between several stages of the value chain with focus on the manufacturing phase of a product has been realized. In order to report best practices regarding the application of DPM in the domain of industrial production, system prototype implementations focusing on the use case of producing and handling a smart drug case are illustrated.

Wastewater pollution abatement in China: A comparative study of fifteen industrial sectors from 1998 to 2010

This study analyzes the management of wastewater pollutants in a number of Chinese industrial sectors from 1998 to 2010. We use decomposition analysis to calculate changes in wastewater pollutant emissions that result from cleaner production processes, end-of-pipe treatment, structural changes in industry, and changes in the scale of production. We focus on one indicator of water quality and three pollutants: chemical oxygen demand (COD), petroleum, cyanide, and volatile phenols. We find that until 2002, COD emissions were mainly reduced through end-of-pipe treatments. Cleaner production processes didn’t begin contributing to COD emissions reductions until the introduction of a 2003 law that enforced their implementation. Petroleum emissions were primarily lowered through cleaner production mechanisms, which have the added benefit of reducing the input cost of intermediate petroleum. Diverse and effective pollution abatement strategies for cyanide and volatile phenols are emerging among industries in China. It will be important for the government to consider differences between industries should they choose to regulate the emissions of specific chemical substances.

Water use and wastewater discharge of industrial sector in China

Problem of water scarcity has been increasingly severe in China. Though industrial sectors play important role for the rapid economic growth, and they consumes water and discharge wastewater. The purpose of this study is to examine the efficiency of water use and wastewater discharge in comparison with those of other inputs and production output in Chinese industry. Measuring efficiency of each input and output factor from 2002 to 2008, we find the average inefficiencies of industrial water use and industrial wastewater discharge are higher than those of capital, labor, and production output in China. In addition, the productivity levels to save water in the water shortage areas are not higher compared to the others. The water use inefficiency has a high dispersion especially in the regions where the amounts of water resources per capita is less than 3000 cubic meter.

Clustering acoustic events in environmental recordings for species richness surveys

Environmental acoustic recordings can be used to perform avian species richness surveys, whereby a trained ornithologist can observe the species present by listening to the recording. This could be made more efficient by using computational methods for iteratively selecting the richest parts of a long recording for the human observer to listen to, a process known as “smart sampling”. This allows scaling up to much larger ecological datasets. In this paper we explore computational approaches based on information and diversity of selected samples. We propose to use an event detection algorithm to estimate the amount of information present in each sample. We further propose to cluster the detected events for a better estimate of this amount of information. Additionally, we present a time dispersal approach to estimating diversity between iteratively selected samples. Combinations of approaches were evaluated on seven 24-hour recordings that have been manually labeled by bird watchers. The results show that on average all the methods we have explored would allow annotators to observe more new species in fewer minutes compared to a baseline of random sampling at dawn.

A novel experimental method to assess industrial aerosol deposition in idealized porous channels

A novel and economical experimental technique has been developed to assess industrial aerosol deposition in various idealized porous channel configurations. This judicious examination on aerosol penetration in porous channels will assist engineers to better optimize designs for various engineering applications. Deposition patterns differ with porosity due to geometric configurations of the channel and superficial inlet velocities. Interestingly, it is found that two configurations of similar porosity exhibit significantly higher deposition fractions. Inertial impaction is profound at the leading edge of all obstacles, whereas particle build-up is observed at the trailing edge of the obstructions. A qualitative analysis shows that the numerical results are in good agreement with experimental results.

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Assistive classification for improving the efficiency of avian species richness surveys

Avian species richness surveys, which measure the total number of unique avian species, can be conducted via remote acoustic sensors. An immense quantity of data can be collected, which, although rich in useful information, places a great workload on the scientists who manually inspect the audio. To deal with this big data problem, we calculated acoustic indices from audio data at a one-minute resolution and used them to classify one-minute recordings into five classes. By filtering out the non-avian minutes, we can reduce the amount of data by about 50% and improve the efficiency of determining avian species richness. The experimental results show that, given 60 one-minute samples, our approach enables to direct ecologists to find about 10% more avian species.

Frequency and precision of aerial surveys for kangaroo management

The appropriate frequency and precision for surveys of wildlife populations represent a trade-off between survey cost and the risk of making suboptimal management decisions because of poor survey data. The commercial harvest of kangaroos is primarily regulated through annual quotas set as proportions of absolute estimates of population size. Stochastic models were used to explore the effects of varying precision, survey frequency and harvest rate on the risk of quasiextinction for an arid-zone and a more mesic-zone kangaroo population. Quasiextinction probability increases in a sigmoidal fashion as survey frequency is reduced. The risk is greater in more arid regions and is highly sensitive to harvest rate. An appropriate management regime involves regular surveys in the major harvest areas where harvest rate can be set close to the maximum sustained yield. Outside these areas, survey frequency can be reduced in relatively mesic areas and reduced in arid regions when combined with lowered harvest rates. Relative to other factors, quasiextinction risk is only affected by survey precision (standard error/mean × 100) when it is >50%, partly reflecting the safety of the strategy of harvesting a proportion of a population estimate.