CERES :: Browsing by Author "Farnsworth, Michael"

Browsing by Author "Farnsworth, Michael"

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Open Access
Capturing, classification and concept generation for automated maintenance tasks
(Elsevier, 2014-04-24) Farnsworth, Michael; Tomiyama, Tetsuo
Maintenance is an efficient and cost effective way to keep the function of the product available during the product lifecycle. Automating maintenance may drive down costs and improve performance time; however capturing the necessary information required to perform certain maintenance tasks and later building automated platforms to undertake them is very difficult. This paper looks at the creation of a novel methodology tasked with firstly the capture and classification of maintenance tasks and finally conceptual design of platforms for automating maintenance.
Open Access
Designing an AR interface to improve trust in Human-Robots collaboration
(Elsevier, 2018-05-21) Palmarini, Riccardo; Fernández del Amo, Iñigo; Bertolino, Guglielmo; Dini, Gino; Erkoyuncu, John Ahmet; Roy, Rajkumar; Farnsworth, Michael
In a global, e-commerce marketplace, product customisation is driven towards manufacturing flexibility. Conventional caged robots are designed for high volume and low mix production cannot always comply with the increasing low volume and high customisation requirements. In this scenario, the interest in collaborative robots is growing. A critical aspect of Human-Robot Collaboration (HRC) is human trust in robots. This research focuses on increasing the human confidence and trust in robots by designing an Augmented Reality (AR) interface for HRC. The variable affecting the trust involved in HRC have been estimated. These have been utilised for designing the AR-HRC. The proposed design aims to provide situational awareness and spatial dialog. The AR-HRC developed has been tested on 15 participants which have performed a “pick-and-place” task. The results show that the utilisation of AR in the proposed scenario positively affects the human trust in robot. The human-robot collaboration enhanced by AR are more natural and effective. The trust has been measured through an empirical psychometric method also presented in this paper.
Open Access
Modelling, simulation and optimisation of a piezoelectric energy harvester
(Elsevier, 2014-10-31) Farnsworth, Michael; Tiwari, Ashutosh; Dorey, Robert A.
The power generation efficiency of piezoelectric energy harvesters is dependent on the coupling of their resonant frequency with that of the source vibration. The mechanical design of the energy harvester plays an important role in defining the resonant frequency characteristics of the system and therefore in order to maximize power density it is important for a designer to be able to model, simulate and optimise designs to match new target applications. This paper investigates a strategy for the application of soft computing techniques from the field of evolutionary computation towards the design optimisation of piezoelectric energy harvesters that exhibit the targeted resonant frequency response chosen by the designer. The advantages of such evolutionary techniques are their ability to overcome challenges such as multi-modal and discontinuous search spaces which afflict more traditional gradient-based methods. A single case study is demonstrated in this paper, with the coupling of a multi-objective evolutionary algorithm NSGA-II to a multiphysics simulator COMSOL. Experimental results show successful implementation of the schema with all 5 experimental tests producing optimal piezoelectric energy harvester designs that matched the desired frequency response of 250 Hz.
Open Access
Multi-level and multi-objective design optimisation of a MEMS bandpass filter
(Elsevier, 2016-10-11) Farnsworth, Michael; Tiwari, Ashutosh; Meiling, Zhu
Microelectromechanical system (MEMS) design is often complex, containing multiple disciplines but also conflicting objectives. Designers are often faced with the problem of balancing what objectives to focus upon and how to incorporate modeling and simulation tools across multiple levels of abstraction in the design optimization process. In particular due to the computational expense of some of these simulation methods there are restrictions on how much optimization can occur. In this paper we aim to demonstrate the application of multi-objective and multi-level design optimisation strategies to a MEMS bandpass filter. This provides for designers the ability to evolve solutions that can match multiple objectives. In order to address the problem of a computationally expensive design process a novel multi-level evaluation strategy is developed. In addition a new approach for bandpass filter modeling and optimization is presented based up the electrical equivalent circuit method. In order to demonstrate this approach a comparison is made to previous attempts to design similar bandpass filters. Results are comparable in design but at a significant reduction in functional evaluations, needing only 10,000 functional evaluations in comparison to 2.6 million with the previous work.
Open Access
Multi-level and multidisciplinary optimisation of microelectromechanical systems
(Cranfield University, 2012-10) Farnsworth, Michael; Tiwari, Ashutosh; Zhu, Meiling
A comparative investigation into the role multi-level and multidisciplinary design optimisation can play in the automated design synthesis of microelectromechanical systems (MEMS) is presented. Microelectromechanical systems are a field grown out of the integrated circuit industry, with the goal of developing smart micro devices which can interact with the environment in some form. They promise to revolutionise our present day lifestyles as much as the integrated circuit has done in recent decades. The complexity in fabrication, the delicacy in size that each device encompasses and the multidisciplinary nature means design synthesis is a highly complicated process. Current challenges stemming from their design include the high levels of computational cost required in their modeling and analysis, and the often increasing complexity of design through the coupling of multiple components and devices into a functioning system. The development of automated design synthesis tools and methodologies to aid MEMS design is therefore important to overcome these challenges in order to accommodate the growing field of MEMS as it expands into more and more areas and continues opening up to more and more applications. An update of the current state of the art in automated MEMS design synthesis and optimisation is first presented, utilizing state of the art multi-objective evolutionary algorithms over five separate MEMS design optimisation case studies. The field of multilevel and multidisciplinary optimisation is critically reviewed and discussed with respect to their application to MEMS design synthesis and optimisation. The outcome is twofold, with the construction of both a novel multidisciplinary optimisation algorithm tailored towards MEMS design and a set of multi-level design optimisation strategies. This thesis next outlines and develops a novel modular soft computing framework to house the multi-objective, multi-level and multidisciplinary design optimisation strategies. In order to evaluate both the current state of the art in automated MEMS design synthesis and the multi-level and multidisciplinary optimisation strategies outlined a hierarchical MEMS bandpass filter case study has been constructed. Incorporating a novel state of the art electrical equivalent modelling and design synthesis approach, six novel design problems structured around the MEMS bandpass filter were developed and formed the basis for the comparative study to follow. Finally both the current state of the art in automated MEMS design synthesis, multiobjective evolutionary algorithms, and the outlined and developed multi-level and multidisciplinary optimisation strategies are applied to the six design problems developed. Comparative analysis and discussion is then given, showing a marked improvement in MEMS design synthesis for the multi-level and multidisciplinary optimisation strategies over the current state of the art methodology.
Open Access
A multi-objective and multidisciplinary optimisation algorithm for microelectromechanical systems
(2017-09-14) Farnsworth, Michael; Tiwari, Ashutosh; Zhu, Meiling; Benkhelifa, Elhadj
Microelectromechanical systems (MEMS) are a highly multidisciplinary field and this has large implications on their applications and design. Designers are often faced with the task of balancing the modelling, simulation and optimisation that each discipline brings in order to bring about a complete whole system. In order to aid designers, strategies for navigating this multidisciplinary environment are essential, particularly when it comes to automating design synthesis and optimisation. This paper outlines a new multi-objective and multidisciplinary strategy for the application of engineering design problems. It employs a population-based evolutionary approach that looks to overcome the limitations of past work by using a non-hierarchical architecture that allows for interaction across all disciplines during optimisation. Two case studies are presented, the first focusing on a common speed reducer design problem found throughout the literature used to validate the methodology and a more complex example of design optimisation, that of a MEMS bandpass filter. Results show good agreement in terms of performance with past multi-objective multidisciplinary design optimisation methods with respect to the first speed reducer case study, and improved performance for the design of the MEMS bandpass filter case study.
Open Access
New threats for old manufacturing problems: Secure IoT-enabled monitoring of legacy production machinery
(Springer, 2017-08-31) Tedeschi, Stefano; Emmanouilidis, Christos; Farnsworth, Michael; Mehnen, Jorn; Roy, Rajkumar
The digitization of manufacturing through the introduction of Industrie 4.0 technologies creates additional business opportunities and technical challenges. The integration of such technologies on legacy production machinery can upgrade them to become part of the digital and smart manufacturing environment. A typical example is that of industrial monitoring and maintenance, which can benefit from internet of things (IoT) solutions. This paper presents the development of an-IoT-enabled monitoring solution for machine tools as part of a remote maintenance approach. While the technical challenges pertaining to the development and integration of such solutions in a manufacturing environment have been the subject of relevant research in the literature, the corresponding new security challenges arising from the introduction of such technologies have not received equal attention. Failure to adequately handle such issues is a key barrier to the adoption of such solutions by industry. This paper aims to assess and classify the security aspects of integrating IoT technology with monitoring systems in manufacturing environments and propose a systematic view of relevant vulnerabilities and threats by taking an IoT architecture point of view. Our analysis has led to proposing a novel modular approach for secure IoT-enabled monitoring for legacy production machinery. The introduced approach is implemented on a case study of machine tool monitoring, highlighting key findings and issues for further research.
Open Access
A novel approach for No Fault Found decision-making
(Elsevier, 2016-06-20) Khan, Samir; Farnsworth, Michael; Erkoyuncu, John Ahmet
Within aerospace and defence sectors, organisations are adding value to their core corporate offerings through services. These services tend to emphasise the potential to maintain future revenue streams and improved profitability and hence require the establishment of cost effective strategies that can manage uncertainties within value led services e.g. maintenance activities. In large organisations, decision-making is often supported by information processing and decision aiding systems; it is not always apparent whose decision affects the outcome the most. Often, accountability moves away from the designated organisation personnel in unforeseen ways, and depending on the decisions of individual decision makers, the structure of the organisation, or unregulated operating procedures may change. This can have far more effect on the overall system reliability – leading to inadequate troubleshooting, repeated down-time, reduced availability and increased burden on Through-life Engineering Services. This paper focuses on outlining current industrial attitudes regarding the No Fault Found (NFF) phenomena and identifies the drivers that influence the NFF decision-making process. It articulates the contents of tacit knowledge and addresses a knowledge gap by developing NFF management policies. The paper further classifies the NFF phenomenon into five key processes that must be controlled by using the developed policies. In addition to the theoretical developments, a Petri net model is also outlined and discussed based on the captured information regarding NFF decision-making in organisations. Since NFF decision-making is influenced by several factors, Petri nets are sought as a powerful tool to realise a meta-model capability to understand the complexity of situations. Its potential managerial implications can help describe decision problems under conditions of uncertainty. Finally, the conclusions indicate that engineering processes, which allow decision-making at various maintenance echelons, can often obfuscate problems that then require a systems approach to illustrate the impact of the issue.
Open Access
On the requirements of digital twin-driven autonomous maintenance
(Elsevier, 2020-09-10) Khan, Samir; Farnsworth, Michael; McWilliam, Richard; Erkoyuncu, John Ahmet
Autonomy has become a focal point for research and development in many industries. Whilst this was traditionally achieved by modelling self-engineering behaviours at the component-level, efforts are now being focused on the sub-system and system-level through advancements in artificial intelligence. Exploiting its benefits requires some innovative thinking to integrate overarching concepts from big data analysis, digitisation, sensing, optimisation, information technology, and systems engineering. With recent developments in Industry 4.0, machine learning and digital twin, there has been a growing interest in adapting these concepts to achieve autonomous maintenance; the automation of predictive maintenance scheduling directly from operational data and for in-built repair at the systems-level. However, there is still ambiguity whether state-of-the-art developments are truly autonomous or they simply automate a process. In light of this, it is important to present the current perspectives about where the technology stands today and indicate possible routes for the future. As a result, this effort focuses on recent trends in autonomous maintenance before moving on to discuss digital twin as a vehicle for decision making from the viewpoint of requirements, whilst the role of AI in assisting with this process is also explored. A suggested framework for integrating digital twin strategies within maintenance models is also discussed. Finally, the article looks towards future directions on the likely evolution and implications for its development as a sustainable technology
Open Access
A review of optimisation techniques used in the composite recycling area: state-of-the-art and steps towards a research agenda
(Elsevier, 2016-08-11) Liu, Ying; Farnsworth, Michael; Tiwari, Ashutosh
The increased use of carbon fibre and glass fibre reinforced polymer in industry coupled with restrictions on landfill disposal has resulted in a need to develop effective recycling technologies for composites. Currently, mechanical, thermal and chemical approaches have been use to recycle composites. This paper seeks to examine the applications of engineering optimisation techniques in the composite recycling and re-manufacturing processes and their relevant systems, providing an overview of state-of-the-art. This paper is based on a comprehensive review of literature covering nearly all the research papers in this area. These papers are analysed to identify current trends and future research directions. The composite recycling is a relatively new area, and the modelling and optimisation work for composite recycling and re-manufacturing techniques and their relevant systems is still in its infancy. Currently, the optimisation work developed in composite recycling mainly focus on the applications of design of experiments methods. These approaches have been applied to improve the quality of recyclates such as carbon fibres. Some of the soft-computing algorithms have been applied to optimise the re-manufacturing at the system level. Based on the existing research, the area of optimisation for composite recycling and re-manufacturing haven't been well explored despite the fact that many opportunities and requirements for optimisation exist. This means significant amount of modelling and optimisation work is required for the future research. More significantly, considering optimisation at the early stage of a system development is very beneficial in terms of the long term health of the composite recycling industry.
Open Access
Self-repairing design process applied to a 4-bar linkage mechanism
(SAGE, 2015-08-22) Bell, Colin; Farnsworth, Michael; Knowles, James; Tiwari, Ashutosh
Despite significant advances in modelling and design, mechanical systems almost inevitably fail at some point during their operative life. This can be due to a pre-existing design flaw, which is usually overcome in a revision, or more commonly due to some unexpected damage during operation. To overcome a failure during operation, a new method in designing machines or systems is proposed that creates a result, that is, resilient to both expected and unexpected failure. By shifting the focus from a detailed assessment of the underlying cause of failure to how that failure will manifest, a system becomes inherently resilient against a wide range of failure modes. The proposed process involves five steps: cause, detection, diagnosis, confirmation and correction. This is demonstrated with an application to a generic 4 bar linkage mechanism. Through this process, the system is able to return to a near perfect state even after a permanent deformation occurs in the mechanism. These results show the potential that this self-repairing design process has applications including robotics, manufacturing and other systems.
Open Access
Theoretical design of a self-rectifying 4-bar linkage mechanism
(Elsevier, 2013-09-27) Bell, Colin; Farnsworth, Michael; Tiwari, Ashutosh; Dorey, Robert A.
Mechanical systems will almost inevitably fail at some point during operation. This can either be due to a preexisting design flaw or some unexpected damage during usage. No matter how much planning and fault analysis is performed it is impossible to create a perfectly reliable machine. Existing approaches to improving reliability normally involve advances in modeling and detection to include specific mechanisms to overcome a particular failure or mitigate its effect. Whilst this has gone a long way to increasing the operational life of a machine, the overall complexity of systems has improved sharply and it is becoming more and more difficult to predict and account for all possible failure modes. Rather than focusing on mitigating or reducing the probability of failure, a new design philosophy is proposed that allows systems to reconfigure themselves to overcome failure – thus yielding a self-healing design. This approach is demonstrated in the design of a self- rectifying 4-bar linkage mechanism.

Browsing by Author "Farnsworth, Michael"

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