3D Printed Flexible Photoplethysmography Sensor Array for Tissue Oximetry

Recently there has been a trend to use the optoelectronic system of pulse oximeters, a photodiode and a pair of light emitting diodes of different wavelengths, to perform elementary tissue oximetry by measuring the changes in oxygenated and deoxygenated haemoglobin concentrations in tissues. This paper presents introductory work into how an affordable flexible array of such tissue oximeters could be manufactured by using direct-write 3D printing and commercial surface mount devices. For this purpose, a flexible printed circuit board was fabricated by printing 30 wt. % silver nanoparticle ink on 60 µm polyimide film. An array of photoplethysmography (PPG) sensors was made by combining the circuit board with two pairs of 660 nm and 940 nm light emitting diodes and six photodiodes. It was demonstrated how this combination of optoelectronic devices results in a 2-by-4 array of PPG sensors with capability to simultaneously measure PPG signals with multiple photodiodes. It was concluded that further work must be completed to evaluate the possibility of this sensor array to be used for tissue oximetry

Optimal microscale water cooled heat sinks for targeted alleviation of hotspot in microprocessors

This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu.Hotspots in microprocessors arise due to non-uniform utilization of the underlying integrated circuits during chip operation. Conventional liquid cooling using microchannels leads to undercooling of the hotspot areas and overcooling of the background area of the chip resulting in excessive temperature gradients across the chip. These in turn adversely affect the chip performance and reliability. This problem becomes even more acute in multi-core processors where most of the processing power is concentrated in specific regions of the chip called as cores. We present a 1-dimensional model for quick design of a microchannel heat sink for targeted, single-phase liquid cooling of hotspots in microprocessors. The method utilizes simplifying assumptions and analytical equations to arrive at the first estimate of a microchannel heat sink design that distributes the cooling capacity of the heat sink by adapting the coolant flow and microchannel size distributions to the microprocessor power map. This distributed cooling in turn minimizes the chip temperature gradient. The method is formulated to generate a heat sink design for an arbitrary chip power map and hence can be readily utilized for different chip architectures. It involves optimization of microchannel widths for various zones of the chip power map under the operational constraints of maximum pressure drop limit for the heat sink. Additionally, it ensures that the coolant flows uninterrupted through its entire travel length consisting of microchannels of varying widths. The resulting first design estimate significantly reduces the computational effort involved in any subsequent CFD analysis required to fine tune the design for more complex flow situations arising, for example, in manifold microchannel heat sinks

A random search approach to the machine loading problem of an FMS

This paper discusses a modelling framework that addresses operational planning, problems of flexible manufacturing systems (FMSs). A generic 0-1 mixed integer programming formulation integrating the part selection and loading problems has been proposed. The constraints considered in the problems are mainly the availability of tool slots and machining time on the machining centres. The above problem is solved using an algorithm based on Simulated Annealing (SA). The potential capability of the approach is demonstrated via a small set of test problems. ©2004 IEEE.published_or_final_versio

Transparent and Robust Amphiphobic Surfaces Exploiting Nanohierarchical Surface-grown Metal-Organic Frameworks.

Highly amphiphobic (repelling both water and low surface tension liquids) and optically transparent surface treatments have widespread demand. By combining a rational growth of metal-organic frameworks (MOFs) with functionalization by environmentally safe, flexible alkyl groups, here we present surfaces with nanohierarchical morphology, comprising two widely differing nanoscale features. These nanohierarchical MOF films show excellent amphiphobicity. We further present three key features. First, we demonstrate the need to use flexible alkyl chains to achieve low drop sliding angles and self-cleaning. Second, our thin (∼200 nm) MOF films display excellent optical transparency and robustness. Third, the nanohierarchical morphology enables a unique combination of additional desirable properties, e.g., resistance to high-speed liquid impact (up to ∼35 m/s, Weber number >4 × 104), thermal stability up to 200 °C, scratch resistance, low ice adhesion for >10 icing/deicing cycles, stability in harsh acidic and basic environments, and capability to remove carcinogenic pollutants from water

Characteristics of redistributed manufacturing systems: a comparative study of emerging industry supply networks

This paper explores the characteristics of redistributed manufacturing systems within the context of emerging industry supply networks (EI SNs), with a particular focus on their structure, operations and reconfiguration dynamics. A number of factors have resulted in the redistribution of manufacturing. Within Emerging Industries, advances in process and information technologies, have changed the physical and information characteristics of components and products, and the viable production economies of scale. Further, the emergence of new specialised companies fulfilling key research, production or service roles have changed industry structure and operations, and the conventional model of value creation. Six industrial systems are examined using an Industrial System mapping methodology providing a basis for cross-case analysis, selected on the basis of representing alternative and novel evolution paths that may provide insights into the characteristics of EI SNs within a redistributed manufacturing context. Cross-case analysis suggests several generic aspects to EI SNs, including the blurring of traditional industry boundaries and the critical requirement to manage uncertainty. Alternative forms of EI SNs are observed supporting particular EI evolution paths. Further, more adaptive SNs support increased product variety, with lower inventory models enabled by enhanced production and distribution flexibility, often located closer to demand.The authors would like to acknowledge UK Research Council EPSRC, the industrial collaborators who provided access to their organisations, and their supply network, industrial and institutional partners.This is the author accepted manuscript. The final version is available from Taylor & Francis via http://dx.doi.org/10.1080/00207543.2016.121476

Next generation smart manufacturing and service systems using big data analytics

© 2018 Elsevier Ltd This special issue explores advancements in the next generation manufacturing and service systems by examining the novel methods, practical challenges and opportunities in the use of big data analytics. The selected articles analyse a range of scenarios where big data analytics and its applications were used for improving decision making in manufacturing and services sector such as online data analytics, sourcing decisions with considerations for big data analytics, barriers in the adoption of big data analytics, maintenance planning, and multi-sensor data for fault pattern extraction. The paper summarises the discussions on the use of big data analytics in manufacturing and service sectors

Solving closed-loop supply chain problems using game theoretic particle swarm optimisation

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. In this paper, we propose a closed-loop supply chain network configuration model and a solution methodology that aim to address several research gaps in the literature. The proposed solution methodology employs a novel metaheuristic algorithm, along with the popular gradient descent search method, to aid location-allocation and pricing-inventory decisions in a two-stage process. In the first stage, we use an improved version of the particle swarm optimisation (PSO) algorithm, which we call improved PSO (IPSO), to solve the location-allocation problem (LAP). The IPSO algorithm is developed by introducing mutation to avoid premature convergence and embedding an evolutionary game-based procedure known as replicator dynamics to increase the rate of convergence. The results obtained through the application of IPSO are used as input in the second stage to solve the inventory-pricing problem. In this stage, we use the gradient descent search method to determine the selling price of new products and the buy-back price of returned products, as well as inventory cycle times for both product types. Numerical evaluations undertaken using problem instances of different scales confirm that the proposed IPSO algorithm performs better than the comparable traditional PSO, simulated annealing (SA) and genetic algorithm (GA) methods

Grain silo location-allocation problem with dwell time for optimization of food grain supply chain network

In the last few decades, production and procurement of food grain in India have steadily increased, however, storage capacity has not increased proportionally. The government of India (GOI) is establishing the various capacitated silos across the country to bridge this storage capacity gap. This paper presents a novel integrated multi-objective, multi-modal and multiperiod mathematical model for grain silo location-allocation problem with Dwell time to support the decision-making process of GOI. Two conflicting objectives- minimization of total supply chain network cost and total lead time (transit and dwell time) are simultaneously optimized using two Pareto based multi-objective algorithms with calibrated parameters

Hybrid integral transform analysis of supercooled droplets solidification

The freezing phenomena in supercooled liquid droplets are important for many engineering applications. For instance, a theoretical model of this phenomenon can offer insights for tailoring surface coatings and for achieving icephobicity to reduce ice adhesion and accretion. In this work, a mathematical model and hybrid numerical–analytical solutions are developed for the freezing of a supercooled droplet immersed in a cold air stream, subjected to the three main transport phenomena at the interface between the droplet and the surroundings: convective heat transfer, convective mass transfer and thermal radiation. Error-controlled hybrid solutions are obtained through the extension of the generalized integral transform technique to the transient partial differential formulation of this moving boundary heat transfer problem. The nonlinear boundary condition for the interface temperature is directly accounted for by the choice of a nonlinear eigenfunction expansion base. Also, the nonlinear equation of motion for the freezing front is solved together with the ordinary differential system for the integral transformed temperatures. After comparisons of the solution with previously reported numerical and experimental results, the influence of the related physical parameters on the droplet temperatures and freezing time is critically analysed

Autonomous transport and splitting of a droplet on an open surface

Pumpless transport of droplets on open surfaces has gained significant attention because of its applications starting from vapor condensation to Lab-on-a-Chip systems. Mixing two droplets on open surfaces can be carried out quickly by using wettability patterning. However, it is quite challenging to split a droplet in the absence of external stimuli because of the interfacial energy of the droplet. Here, we demonstrate a standalone power-free technique for transport and splitting of droplets on open surfaces using continuous wettability gradients. A droplet moves continuously from a low to a high wettability region on the wettability-gradient surface. A Y-shaped wettability-gradient track – laid on a superhydrophobic background – is used to investigate the dynamics of the splitting process. A three-dimensional phase-field Cahn-Hilliard model for interfaces and the Navier-Stokes equations for transport are employed and solved numerically using the finite element method. Numerical results are used to decipher the motion and splitting of droplet at the Y junction using the principle of energy conservation. It is observed that droplet splitting depends on the configuration of the Y junction; droplets split faster for the superhydrophobic wedge angle of 90∘ and the splitting ratio (ratio of the sizes of daughter droplets) depends on the widths of the Y branches. A critical branch-width ratio (w2w1=0.79) is identified below which the droplet does not split and moves towards the branch of higher width and settles there. The present study provides the required theoretical underpinnings to achieve autonomous transport and splitting of droplets on open surfaces, which has clear potential for applications in Lab-on-a-Chip devices