Michael Farnsworth

Design and optimisation of microelectromechanical systems: a review of the state-of-the-art

This article provides an inclusive review on the field of design and optimisation (DO) of microelectromechanical systems (MEMS) since its emergence, about two decades ago. Fundamentals and applications of MEMS are presented herein, followed by a comprehensive review on the conventional tools and practices developed for MEMS DO throughout. The limitations of these techniques are identified, and the necessity for automated DO methods for MEMS technology is therefore justified and evaluated. A recent trend in DO of microsystems is inspired by the natural evolution and the survival of the fittest hypothesises. Motivated by its achievements in other engineering DO problems, evolutionary computation has also been adopted for the DO of MEMS, at different levels. A thorough review of this infant area of research is also presented in this article and highlights of the main challenges facing this field are discussed. Prior to a major research in the area, this article provides an update of the state-of-the-art on MEMS technology with a general interest in the automated DO techniques, particularly, the evolutionary methods.

Autonomous Maintenance for Through-Life Engineering

This chapter looks at the overall theme of automating maintenance practices with a particular focus upon the application of robotics within this field. Covering the current state of the art in automating maintenance processes this chapter also looks at the current challenges to moving beyond simple inspection and diagnosis to the design and construction of fully automated platforms for undertaking maintenance. This includes methodologies for capturing and classifying maintenance task processes so that they can be automated in some way and how to link this task classification with some level of automation. The chapter ends with a discussion on how the design process can be adapted to aid automated maintenance, self-healing and no fault found applications.

A novel approach to multi-level evolutionary design optimization of a MEMS device

This paper introduces a novel approach to the evolutionary design optimisation of an MEMS bandpass filter, incorporating areas of multi-disciplinary, multi-level and multi-objective design optimisation in the process. In order to demonstrate this approach a comparison is made to previous attempts to design similar bandpass filters, providing comparable results at a significant reduction in functional evaluations. In this endeavour, a circuit equivalent of the MEMS bandpass filter is evolved extrinsically using the SPICE Simulator.

Evolutionary Algorithms for Planar MEMS Design Optimisation: A Comparative Study

The evolutionary approach in the design optimisation ofMEMS is a novel and promising research area. The problem is of a multi-objective nature; hence, multi-objective evolutionary algorithms (MOEA) are used. The literature shows that two main classes of MOEA have been used in MEMS evolutionary design Optimisation, NSGA-II and MOGA-II. However, no one has provided a justification for using either NSGA-II or MOGA-II. This paper presents a comparative investigation into the performance of these two MOEA on a number of MEMS design optimisation case studies. MOGA-II proved to be superior to NSGA-II. Experiments are, herein, described and results are discussed.

Multi-level and multi-objective design optimisation of a MEMS bandpass filter

HighlightsElectrical equivalent modelling of a MEMS bandpass filter.Developed into three separate design case studies for experimentation.Two MOEAs (NSGAII and SPEA2) used for design optimisation of MEMS bandpass filters.A multi-level design optimisation strategy tested over three case studies.State of the art performance in design and speed for this particular problem. 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.

A Multi-objective and Multidisciplinary Optimisation Algorithm for Microelectromechanical Systems

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.

Self-repairing design process applied to a 4-bar linkage mechanism

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.

Design for Zero-Maintenance

This chapter looks at the concept of zero-maintenance, in particular how it relates to design. It begins by defining what constitutes zero-maintenance, presenting current research on the themes of autonomous maintenance and self-healing and repair. A wider context of how zero-maintenance affects through-life engineering services is also discussed with a focus on the no-fault found phenomenon. Case studies are then presented for design strategies in self-healing electronics and no-fault found and the failure of design. Finally, a design for zero-maintenance process is outlined and discussed.

New threats for old manufacturing problems: Secure IoT-enabled monitoring of legacy production machinery

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.