Strain sensors with adjustable sensitivity by tailoring the microstructure of graphene aerogel/PDMS nanocomposites

Strain sensors with high elastic limit and high sensitivity are required to meet the rising demand for wearable electronics. Here, we present the fabrication of highly sensitive strain sensors based on nanocomposites consisting of graphene aerogel (GA) and polydimethylsiloxane (PDMS), with the primary focus being to tune the sensitivity of the sensors by tailoring the cellular microstructure through controlling the manufacturing processes. The resultant nanocomposite sensors exhibit a high sensitivity with a gauge factor of up to approximately 61.3. Of significant importance is that the sensitivity of the strain sensors can be readily altered by changing the concentration of the precursor (i.e., an aqueous dispersion of graphene oxide) and the freezing temperature used to process the GA. The results reveal that these two parameters control the cell size and cell-wall thickness of the resultant GA, which may be correlated to the observed variations in the sensitivities of the strain sensors. The higher is the concentration of graphene oxide, then the lower is the sensitivity of the resultant nanocomposite strain sensor. Upon increasing the freezing temperature from −196 to −20 °C, the sensitivity increases and reaches a maximum value of 61.3 at −50 °C and then decreases with a further increase in freezing temperature to −20 °C. Furthermore, the strain sensors offer excellent durability and stability, with their piezoresistivities remaining virtually unchanged even after 10 000 cycles of high-strain loading−unloading. These novel findings pave the way to custom design strain sensors with a desirable piezoresistive behavior.

Industry case study: rapid prototype of mountain bike frame section

The purpose of this study is to detail a virtual and physical prototyping process to overcome a design constraint in the mountain bike industry. Through a series of techniques, 3D scanning, developing detailed CAD models, then through additive manufacturing processes, a solution wasdeveloped. The challenge in the industry is the constant geometrical changes of components; the trend has been that bike cranks are becoming narrower due to biomechanical factors and tyres are becoming wider due to rider preferences and increased grip. This change in geometry results in metal tubes that can no longer be deformed without exceeding the minimum bend radius for the material. As such exceeding the minimum bend radius will induce early performance failure and geometrical (aesthetic) defects. The solution is an additivemanufactured part that can be substituted into the process without disrupting the entire conventional build process of a customised bike build.

Analysing business processes to manage and resolve strategic issues in a manufacturing business

This paper demonstrates the value of applying heuristics to knowledge systems of business processes in a manufacturing company to resolve strategic issues and enable the attainment of strategic business goals. The manufacturing company was losing market share through not being able to get its new products to market quickly enough. The research illustrates the ‘location’ and use of information systems in a manufacturing context. The researchers collected the specific business process knowledge in the company and developed a knowledge management system and then applied heuristics to the ‘AS IS’ manufacturing process to determine better models of manufacturing that would enable faster to market product development and thus enable better strategic alignment between company expectations and realisation of market share. The paper highlights the strategic use of information systems as a means of directly solving business problems.

Simulation of the fastener manufacturing process

Cold forging of steel has been modelled using a physical simulation and the finite element method (FEM) to predict the conditions under which failure occurs. FEM was performed using FORGE2 software, which allows analysis of two-dimensional, axi-symmetric forging processes. Various cold forming processes were modelled. The material model has been validated through wire drawing and bulging experiments. The results will be applied to cold forging of industrial products such as fasteners.

Characterization and analysis of delamination fracture and nanocreep properties in carbon epoxy composites manufactured by different processes

Delamination resistance and nanocreep properties of 2/2 twill weave carbon epoxy composites manufactured by hot press, autoclave, and Quickstep^TM process are characterized and analyzed. Quickstep is a fluid filled, balanced pressure heated floating mold technology, which is recently developed in Perth, Western Australia for the manufacture of advanced composite components. Mode I and Mode II interlaminar fracture toughness tests, and nanoindentation creep tests on matrix materials show that the fast ramp rate of the Quickstep process provides mechanical properties comparable to that of autoclave at a lower cost for composite manufacturing. Low viscosity during ramping process and good fiber wetting are believed to be the reasons that this process produces composites with high delamination and creep-resistant properties. Nanocreep properties are analyzed using a Kelvin–Voigt model.

On-line tool condition monitoring and control system in forging processes

Cold bulk metal forming has made large-scale production of small complex solid parts economically feasible. Tooling used in metal forming poses many uncertainties in the preliminary cost estimation and production process and continual tool replacement and maintenance dramatically reduces productivity and raises manufacturing cost. In order to tackle this, an on-line tool condition monitoring system using artificial neural network (ANN) to integrate information from multiple sensors for forging process has been developed. Together with the force, acoustic emission signals and process conditions, information developed from theoretical models is integrated into the ANN tool monitoring system to predict tool life and provide the maintenance schedule.

Manufacturing process effects on the mode I interlaminar fracture toughness and nanocreep properties of CFRP

Quickstep ™ is a fluid filled floating mould technology which was recently developed by an Australian company of the same name. The Quickstep and conventional autoclave manufacture of composites were compared by investigating the mode I interlaminar fracture toughness and nanocreep propeties of HexPly914 carbon epoxy composites. It was found that composites cured using the Quickstep technology had significantly higher fracture toughness (1.8 times) than the composites cured via autoclave for this system. DMTA (dynamic mechanical thermal analysis) results showed a higher Tg (glass transition temperature) for the material manufactured by the Quickstep than that cured by the autoclave. FTIR (Fourier transform infrared spectroscopy) spectra did not indicate any difference in cure chemistry between the two processes. Nanocreep experiments were performed to explore the viscoelastic properties of the epoxy matrix of composites. The KelvinVoigt three-element model was applied to analyse the indentation creep behaviour of both composites.

Inspection of drop-weight impact damage in woven CFRP laminates fabricated by different processes

The influence of manufacturing process on the drop-weight impact damage in woven carbon/epoxy laminates was inspected by visual observation, dyepenetrant X-ray technique, and optical microscopy observation. The MTM56/ CF0300 woven quasi-isotropic laminates were fabricated by two processes: the autoclave and the Quickstep processes. Quickstep^TM is a novel composite manufacturing process, which was designed for the out-of-autoclave production of high-quality composite parts at lower cost. It utilizes higher heat conduction of fluid other than gas to transfer heat to components, which results in much shorter cure cycles. The laminates cured by this fast heating process showed different impact failure modes from those cured by the conventional autoclave process. The residual indentation in the top side of the Quickstep-cured laminates had a bigger diameter, but a smaller depth at the same impact energy level. Dye-penetrant X-ray revealed more intense and connected impact damage regions in the autoclave-cured laminates. Optical micrography as a supplementary method showed less severe matrix damage in the quickstep-cured laminates indicating a more ductile property of the resin matrix cured at a faster heating rate.

Haptics and virtual reality in modern manufacturing

Product assembly is one of the most studied processes in modern manufacturing. In recent years a number of computer-based virtual reality systems have been proposed, developed and adopted by the manufacturing industries. Such systems have major advantages over conventional training practices for product assembly. Significant cost savings can be realized due to shorter training-scenario development times and reuse of existing engineering math models. In addition, the time span from the product design to full production can be shortened due to non-reliance on actual components and subsystems for training. Such training systems are effective if the knowledge required to be transferred is just process sequence such as assembly sequence. However, knowledge transfer for procedural and cognitive learning as well as skills development is very limited, due to the lack of user interactivity and immersion.

This talk will focus on a research technology platform where haptics and virtual reality are integrated to create an effective environment for production assembly operators’ training. In this system virtual reality provides the grounds for realistic visualization, as well as immersion, whereas haptics enforces physical constraints within the virtual world generating the feelings of realistic interaction, making it accessible for formal learning and better understanding during task performance.

The developed research technology platform imitates real physical training scenarios by providing comprehensive user interaction, constrained within the physical limitations of the real world. Through the utilization of a haptics device, providing realistic force feedback, users are able to engage in product assembly training with a stronger sense of ‘reality’.

The strategic mindset of Australian manufacturing managers : some missing links

Manufacturing managers have a measurable mindset (or frame) that structures their response to the manufacturing environment. Most importantly, this frame represents a set of assumptions about the relative prominence of concepts in the manufacturing domains, about the nature of people, and about the sensemaking processes required to understand the nature of the manufacturing environment as seen through the eyes of manufacturing managers. This paper uses work in the area of text analysis and extends the scope of a methodology that has been approached from two different directions by Carley ( Journal of Organizational Behavior , 18 (51), 533-558, 1997) and Gephart ( Journal of Organizational Behavior , 18 (51), 583-622, 1997). This methodology is termed collocate analysis. Based on the analysis of transcripts of interviews of Australian manufacturing managers mind maps of the concepts used by these managers have been constructed. From an analysis of these mind maps it is argued that strategy plays a minor role in their thinking second only to the improvement domain, whereas design and related concepts play a dominant role in their day-to-day thinking

Simplifying medical additive manufacturing: making the surgeon the designer

Additive Manufacturing, a technology which has been in existence since three decades, is now successfully being transitioned from a research setting to finding technologically and financially viable end-user applications. A key sector in which Additive Manufacturing is being used is the medical devices and healthcare sector. Drivers in this sector include the ability to create customized, patient specific devices and implants with quick turnaround time in a cost-effective manner. Doctors and surgeons are important change agents and innovators in the creation of new healthcare devices as well as surgical methods. Often times, they may find it necessary at first to build devices and plan surgeries which are not even being thought of or acted upon by the major healthcare companies. In this sense, they perform the roles of designers, creating new ideas and improving on them until they can be implemented and adopted by others. However, the scope for performing this creative activity is often limited in their workplaces, with resource, time and financial impediments often being present. Additive Manufacturing can be helpful to speed up the iterative process of designing such medical devices or planning surgeries as well as help convince people outside of the surgery room of the feasibility and business case for such innovations. This paper proposes to introduce a framework of design, processes and tools which will enable non-engineers (specifically surgeons) to create custom-built products. It is hoped that this paper will motivate more surgeons and non-engineers to get involved in the process of designing for additive manufacturing.

A transformation technique to estimate the process capability index for non-normal processes

Estimating the process capability index (PCI) for non-normal processes has been discussed by many researches. There are two basic approaches to estimating the PCI for non-normal processes. The first commonly used approach is to transform the non-normal data into normal data using transformation techniques and then use a conventional normal method to estimate the PCI for transformed data. This is a straightforward approach and is easy to deploy. The alternate approach is to use non-normal percentiles to calculate the PCI. The latter approach is not easy to implement and a deviation in estimating the distribution of the process may affect the efficacy of the estimated PCI. The aim of this paper is to estimate the PCI for non-normal processes using a transformation technique called root transformation. The efficacy of the proposed technique is assessed by conducting a simulation study using gamma, Weibull, and beta distributions. The root transformation technique is used to estimate the PCI for each set of simulated data. These results are then compared with the PCI obtained using exact percentiles and the Box-Cox method. Finally, a case study based on real-world data is presented.