Making the user more efficient: Design for sustainable behaviour

User behaviour is a significant determinant of a product’s environmental impact; while engineering advances permit increased efficiency of product operation, the user’s decisions and habits ultimately have a major effect on the energy or other resources used by the product. There is thus a need to change users’ behaviour. A range of design techniques developed in diverse contexts suggest opportunities for engineers, designers and other stakeholders working in the field of sustainable innovation to affect users’ behaviour at the point of interaction with the product or system, in effect ‘making the user more efficient’. Approaches to changing users’ behaviour from a number of fields are reviewed and discussed, including: strategic design of affordances and behaviour-shaping constraints to control or affect energyor other resource-using interactions; the use of different kinds of feedback and persuasive technology techniques to encourage or guide users to reduce their environmental impact; and context-based systems which use feedback to adjust their behaviour to run at optimum efficiency and reduce the opportunity for user-affected inefficiency. Example implementations in the sustainable engineering and ecodesign field are suggested and discussed

Tissue-Engineered Larynx: Future Applications in Laryngeal Cancer

PURPOSE OF REVIEW: This article reviews the latest developments in tissue engineering for the larynx with a specific focus on the treatment of laryngeal cancer. RECENT FINDINGS: Challenges in tissue engineering a total larynx can be divided into scaffold design, methods of re-mucosalization, and how to restore laryngeal function. The literature described a range of methods to deliver a laryngeal scaffold including examples of synthetic, biomimetic, and biological scaffolds. Methods to regenerate laryngeal mucosa can be divided into examples that use a biological dressing and those that engineer a new mucosal layer de novo. Studies aiming to restore laryngeal function have been reported, but to date, the optimum method for achieving this as part of a total laryngeal transplant is yet to be determined. SUMMARY: There is great potential for tissue engineering to improve the treatments available for laryngeal cancer within the next 10 years. A number of challenges exist however and advances in restoring function must keep pace with developments in scaffold design

Applications of topology optimisation in structural engineering: high-rise buildings & steel components

This study introduces applications of structural topology optimization to buildings and civil engineering structures. Topology optimization problems utilize the firmest mathematical basis, to account for improved weight-to-stiffness ratio and perceived aesthetic appeal of specific structural forms, enabling the solid isotropic material with penalization (SIMP) technique. Structural topology optimization is a technique for finding the optimum number, location and shape of “openings” within a given continuum subject to a series of loads and boundary conditions. Aerospace and automotive engineers routinely employ topology optimization and have reported significant structural performance gains as a result. Recently, designers of buildings and structures have also started investigating the use of topology optimization, for the design of efficient and aesthetically pleasing developments. This paper examines two examples of where topology optimization may be a useful design tool in civil/structural engineering in order to overcome the frontiers between civil engineers and engineers from other disciplines. The first example presents the optimized structural design of a geometrically complex high-rise structure and the optimal design of its architectural building shape. The second one focuses on the optimization and design of a perforated steel I-section beam, since such structural members are widely used nowadays in the vast majority of steel buildings and structures while they provide numerous advances. Conclusions are drawn regarding the potential benefits to the more widespread implementation of topology optimization within the civil/structural engineering industr

Simulation-assisted control in building energy management systems

Technological advances in real-time data collection, data transfer and ever-increasing computational power are bringing simulation-assisted control and on-line fault detection and diagnosis (FDD) closer to reality than was imagined when building energy management systems (BEMSs) were introduced in the 1970s. This paper describes the development and testing of a prototype simulation-assisted controller, in which a detailed simulation program is embedded in real-time control decision making. Results from an experiment in a full-scale environmental test facility demonstrate the feasibility of predictive control using a physically-based thermal simulation program

Energy-efficient through-life smart design, manufacturing and operation of ships in an industry 4.0 environment

Energy efficiency is an important factor in the marine industry to help reduce manufacturing and operational costs as well as the impact on the environment. In the face of global competition and cost-effectiveness, ship builders and operators today require a major overhaul in the entire ship design, manufacturing and operation process to achieve these goals. This paper highlights smart design, manufacturing and operation as the way forward in an industry 4.0 (i4) era from designing for better energy efficiency to more intelligent ships and smart operation through-life. The paper (i) draws parallels between ship design, manufacturing and operation processes, (ii) identifies key challenges facing such a temporal (lifecycle) as opposed to spatial (mass) products, (iii) proposes a closed-loop ship lifecycle framework and (iv) outlines potential future directions in smart design, manufacturing and operation of ships in an industry 4.0 value chain so as to achieve more energy-efficient vessels. Through computational intelligence and cyber-physical integration, we envision that industry 4.0 can revolutionise ship design, manufacturing and operations in a smart product through-life process in the near future

The Investigation of Pump Performance and Evaluation over the Internet

Selection and configuration are widely met tasks in design; this is an example of a web-based selection/configuration tool with embedded optimisation. Pumps inevitably deteriorate over their product lifecycle, in which interaction generally occurs in terms of flow, pressure and electricity consumption. Practical implementations of pump scheduling suggest that a 10% of the annual expenditure on energy costs may be saved. The object is to minimise the energy cost incurred, while selecting the best schedule of legal available pumps. The results illustrate that the recording of pump characteristics over the internet provides an efficient method of pump performance and evaluation

Optimised configuration of sensing elements for control and fault tolerance applied to an electro-magnetic suspension system

New technological advances and the requirements to increasingly abide by new safety laws in engineering design projects highly affects industrial products in areas such as automotive, aerospace and railway industries. The necessity arises to design reduced-cost hi-tech products with minimal complexity, optimal performance, effective parameter robustness properties, and high reliability with fault tolerance. In this context the control system design plays an important role and the impact is crucial relative to the level of cost efficiency of a product. Measurement of required information for the operation of the design control system in any product is a vital issue, and in such cases a number of sensors can be available to select from in order to achieve the desired system properties. However, for a complex engineering system a manual procedure to select the best sensor set subject to the desired system properties can be very complicated, time consuming or even impossible to achieve. This is more evident in the case of large number of sensors and the requirement to comply with optimum performance. The thesis describes a comprehensive study of sensor selection for control and fault tolerance with the particular application of an ElectroMagnetic Levitation system (being an unstable, nonlinear, safety-critical system with non-trivial control performance requirements). The particular aim of the presented work is to identify effective sensor selection frameworks subject to given system properties for controlling (with a level of fault tolerance) the MagLev suspension system. A particular objective of the work is to identify the minimum possible sensors that can be used to cover multiple sensor faults, while maintaining optimum performance with the remaining sensors. The tools employed combine modern control strategies and multiobjective constraint optimisation (for tuning purposes) methods. An important part of the work is the design and construction of a 25kg MagLev suspension to be used for experimental verification of the proposed sensor selection frameworks

Multi-objective optimisation for minimum quantity lubrication assisted milling process based on hybrid response surface methodology and multi-objective genetic algorithm

© 2019 by SAGE Publications Ltd.Parametric modelling and optimisation play an important role in choosing the best or optimal cutting conditions and parameters during machining to achieve the desirable results. However, analysis of optimisation of minimum quantity lubrication–assisted milling process has not been addressed in detail. Minimum quantity lubrication method is very effective for cost reduction and promotes green machining. Hence, this article focuses on minimum quantity lubrication–assisted milling machining parameters on AISI 1045 material surface roughness and power consumption. A novel low-cost power measurement system is developed to measure the power consumption. A predictive mathematical model is developed for surface roughness and power consumption. The effects of minimum quantity lubrication and machining parameters are examined to determine the optimum conditions with minimum surface roughness and minimum power consumption. Empirical models are developed to predict surface roughness and power of machine tool effectively and accurately using response surface methodology and multi-objective optimisation genetic algorithm. Comparison of results obtained from response surface methodology and multi-objective optimisation genetic algorithm depict that both measured and predicted values have a close agreement. This model could be helpful to select the best combination of end-milling machining parameters to save power consumption and time, consequently, increasing both productivity and profitability.Peer reviewedFinal Published versio