Mode Localization in Two Coupled Nearly Identical MEMS Cantilevers for Mass Sensing

This paper investigates the mass sensing in a mode-localized sensor composed of two weakly coupled MEMS cantilevers with lengths 98μm and 100μm. The two resonators are connected by a coupling beam near the fixed end, and the shortest cantilever is electrostatically actuated with a combined AC-DC voltage. The DC actuation voltage is tuned to compensate the length difference and geometrical imperfections in order to dynamically equilibrate the system. An analytical model of the device using the Euler Bernoulli beam theory is presented and the required DC voltage to reach the balanced state is used. A mass perturbation is then added on the long cantilever and the eigenstate shifts and amplitude ratios in each mode are calculated for different couplings. Results show that the amplitude ratio of the second mode is the best output metric for the mass detection. For the validation of the model, an experimental investigation is carried out by using devices fabricated with the Multi-User MEMS Processes. Three different couplings are considered and the long cantilever is designed with a mass attached at its end. Instead of adding a mass on the device, we remove this part with a probe to introduce the perturbation. When the mass is removed, the experimental frequency responses of the device show localized vibrations, which are in good agreement with the theoretical results.

Feasibility Study of a Capacitive MEMS Filter Using Electrostatic Levitation

We introduce a capacitive MEMS filter that uses electrostatic levitation for actuation and sensing. The advantage of this electrode configuration is that it does not suffer from the pull-in instability and therefore tremendously high voltages can be applied to this system. A large sensing voltage will produce a large output signal, which boosts the signal to noise ratio. The filter outputs about a 110mV peak-to-peak signal when operated at 175V, and can be boosted to 175mV by increasing the voltage to 250V. Because pull-in is eliminated, voltages much higher than 250V can be applied. An outline of the filter design and operating principle is discussed. A model of the filter is derived and analyzed to show the mechanical response and approximate peak-to-peak signal output. This study shows the feasibility of a capacitive sensor that is based on electrostatic levitation, and outlines the advantages it has over traditional parallel-plate electrode configurations. This design is promising for signal signal processing applications where large strokes are important.

Localised Pre-Heating to Improve Inter-Layer Delamination Strength in Fused Deposition Modelling

Additive manufacture, specifically Fused Deposition Modeling (FDM), is an advancing manufacture method opening up new possibilities in design previously impossible to machine, in a relatively affordable way. However, its use in functional products is limited due to anisotropic strength and reduced strength from injection molded components. This paper aims to increase the tensile strength of Acrylonitrile Butadiene Styrene (ABS) in the weakest direction (Z axis), where poor interlayer fusion and air gaps between extruded trails reduce strength. Extra thermal energy was applied to the top surface layer during the printing process (through hot air) to encourage more polymer chain diffusion across the boundary, and spreading out to fill air gaps. Multiple tensile test samples were printed at a variety of heat levels. The ultimate tensile strength σuts was plotted against these temperatures and a weak positive correlation was found. However, only air temperatures above 81°C increased strength past the control to a maximum of 1.4MPa. Heat application has proven to increase tensile strength, but needs to be applied with a more precise method, to the boundary interface, to allow greater thermal energy transfer without sacrificing print quality.

Addressing Information Gaps in Household Waste Sorting Using a Mobile Application

The Danish government has outlined a target of recycling 50% of total household waste by the year 2022. Improving household waste sorting is an important consideration towards achieving this goal. This paper focuses on understanding existing waste sorting practices among Danish residents and exploring whether a mobile application can help address any existing information gaps. We conducted a preliminary survey (N = 180) that assessed preference for sorting strategies and the types of waste sorted. Following this a more detailed survey was conducted (N = 357) that assessed residents’ motivation to sort household waste, knowledge of local sorting requirements, information gaps that prevent effective sorting, and need for specific features in a mobile application. Results show over one-third of respondents felt they needed additional waste sorting information. Respondents had fewer inaccuracies disposing items within a single waste stream (e.g., electronics waste) compared to items with mixed waste streams (e.g., milk carton with a plastic cap). Based on these findings we propose the design of a mobile application that can potentially improve household waste sorting.

Overview of the Development and Enforcement of Process-Driven Manufacturability Constraints in Product Design

Design-for-manufacturing (DFM) concepts have traditionally focused on design simplification; this is highly effective for relatively simple, mass-produced products, but tends to be too restrictive for more complex designs. Effort in recent decades has focused on creating methods for generating and imposing specific, process-derived technical manufacturability constraints for some common problems. This paper presents an overview of the problem and its design implications, a discussion of the nature of the manufacturability constraints, and a survey of the existing approaches and methods for generating/enforcing the minimally restrictive manufacturability constraints within several design domains. Four major design perspectives were included in the study, including the system design (top-down), the product design (bottom-up), the manufacturing process-dominant approach (specific process required), and the part-redesign approach. Manufacturability constraints within four design levels were explored as well, ranging from macro-scale to sub-micro-scale design. Very little previous work was found in many areas but it is clear from the existing literature that the problem and a general solution to it are very important to explore further in future DFM and design automation work.

Integrative Design of Product Architecture and Assembly Process Plan

This paper proposes an integrative design method of product architecture and assembly process plan by introducing a matrix-based modeling and analysis scheme. Design structure matrix (DSM) has been used to analyze and design the conceptual structure of product architecture. An assembly sequence diagram, such as a fishbone diagram, has been used as a representation scheme of the assembly process in the design-for-assembly (DFA) framework. The method of this paper is composed of a DSM-based procedure for generating an assembly sequence plan and its integration with a DSM-based design method of product architecture. In this paper, after general meanings of integration in product design are reviewed, the overall method for integration and mathematical procedure for optimizing an assembly sequence plan by compromising with components modularity are described. The procedure for generating an assembly sequence plan is demonstrated with an example of a desktop stapler, and the integrative design is demonstrated with a case study of air-conditioner units. This paper concludes with some discussion on the role of the proposed framework toward the integrity of product design.

Health State Assessment and Lifetime Prediction Based on Unsupervised State Estimation

Assessment of system health and prediction of remaining useful life can be performed effectively through the evaluation of degradation levels configured by multiple states. Commonly, degradation progression is modeled according to the specific configuration using existing algorithms with assuming numbers and state conditions. However, due to the complexity, especially in the case of a system with multiple hidden states, the proper configuration is hard to assign and to identify. The need for unsupervised state estimation process to assist degradation modeling preventing under or over assumption becomes obvious. Among the existing approaches is the application of clustering methods to classify data and to estimate the number of degradation states might exist. However, integration into the lifetime prediction framework is still infancy and often not considered. Therefore, in this work, a previously developed state machine lifetime model is extended to allow flexibility in configuring state topology based on K-means clustering algorithm and cluster validity index for the optimal number of states identification. Combining unsupervised state estimation process with a new state machine lifetime model has transformed it into a semi-supervised prognostic approach. For validation, hydraulic pressure data from tribology experiment are deployed for training and test the algorithm. Based on the evaluation, this approach demonstrates the ability to improve health state assessment and lifetime prediction in a more flexible way to address the variability in the system.

A Proposed Hybrid Laser Quenching Process, and Investigation of its Three-Dimensional Forming Error

In this research, we focus on heat treatment, specifically during the downsizing of production systems. We devise a method designed to remedy the problem of quenching for thin plates, by using a small semiconductor laser. In this report, we investigated a method to reduce the influence, deformation amount, and three–dimensional (3D) distortion error of residual stress that occurred when a laser test was performed on a metal test piece. Regarding the residual stress, the specimen was burned out by continuous scanning. Its residual stress showed a tendency to fade as the specimen was scanned at lower speeds. We found it was possible to reduce deformation by restraining the specimen with the jig, but that 3D strain error under this constrained state remained of the same order as it was in the unconstrained state. In addition, by restraining the test piece with a jig, it was possible to prevent reverse deformation (Buckling Mechanism).

Manufacturing Processes Re-Engineering for Cost Reduction: The Investment Casting Case Study

The production cost is one of the most important drivers for product competitiveness. For increasing profits, a manufacturing process re-engineering is mandatory. This practice passes through systematic procedures for process selection, cost estimation and results analysis. This paper presents a method for evaluating different manufacturing alternatives for cost reduction. This method, composed of eight steps (most of them retrieved from the scientific literature), permits engineers to consider important aspects, such as the choice of cost estimation tools, the collection of data related to production processes, the impact related to the introduction of new production processes and the interpretation of results. Authors adopted such method for evaluating economic benefits of introducing a new manufacturing technology (i.e. investment casting) for three components of a food packaging machine. The adoption of the proposed method leads to compare investment casting vs. machining. The paper presents a detailed discussion of the economic benefits (return on investment, cash flows and manufacturing cost breakdown) related to the introduction of the investment casting technology.

Development of Three-Dimensional MEMS Biochemical Sensors for Low Concentration Aqueous Solutions

Three-dimensional biochemical sensors are developed that can be used for chemical and biological detection in aqueous solutions and suspensions. The sensors are fabricated using a standard polycrystalline silicon process, PolyMUMPs, and can detect chemicals and biomarkers in low concentrations in near real time. The sensors made of a stack of electrodes allowing the solution to occupy the space between the layers of electrodes and have a larger interface with the electrodes. The sensors use electrochemistry impedance spectroscopy (EIS) for detection and therefore increasing the solution-electrode interface improves the sensitivity of the sensor. To demonstrate the applicability of the proposed sensor design, experimental measurements are used to characterize and compare the 3D sensors with conventional 2D interdigitated sensors. Diethylhexyl phthalate (DEHP) solution is used as the target chemical, and the 2D and 3D biochemical sensors are exposed to different concentrations of DEHP solution. An LCR meter is used to sweep the frequency and determine the impedance of the sensor-solution combination. The test results show that the three-dimensional sensors have higher sensitivity than 2D interdigitated ones verifying the advantage of the new sensor design over existing conventional sensors. The proposed sensors can also be used for detection of biological markers such as cells, proteins and enzymes in aqueous solutions.