In-line Quality Control Research Articles

Predictive quality control of hybrid metal-CFRP components using information fusion

The paper presents an approach to determine the durability of hybrid metal-CFRP components combining the results of non-destructive testing (ndt) and finite element simulation The advantage of hybrid metal-CFRP components lies in the use of the properties of the materials used. CFRP parts with higher specific stiffness and strength are combined with metallic joining points, so that established joining processes for metal components can be applied to these lightweight components. In order to further promote the use of these hybrids in industry, it is necessary to guarantee a high level of component reliability through 100% quality control in order to avoid production-related defects. These defects such as delamination or fibre disorientation however vary in shape, size and position and lead to different effects on the part performance and reliability. Therefore the presented approach includes the application of non-destructive testing methods that are applied as in-line quality control measures in order to determine defect characteristics of the inspected parts. Due to the novelty of the component under test it is necessary to evaluate the individual criticality of detected defects and how they affect part performance during the testing procedure. Therefore the acquired ndt-data is used in finite element simulations where defect characteristics are added to the component model and whose effects on part reliability are evaluated. The generation of additional information combining non-destructive testing and simulation is referred to as data fusion. In order to evaluate the validity of the presented approach the determined part performances are compared to experimental mechanic tests.

In-line metrology for roll-to-roll UV assisted nanoimprint lithography using diffractometry

We describe and discuss the optical design of a diffractometer to carry out in-line quality control during roll-to-roll nanoimprinting. The tool measures diffractograms in reflection geometry, through an aspheric lens to gain fast, non-invasive information of any changes to the critical dimensions of target grating structures. A stepwise tapered linear grating with constant period was fabricated in order to detect the variation in grating linewidth through diffractometry. The minimum feature change detected was ∼40 nm to a precision of 10 nm. The diffractometer was then integrated with a roll-to-roll UV assisted nanoimprint lithography machine to gain dynamic measurements in situ.

Impacts of electrode coating irregularities on polymer electrolyte membrane fuel cell lifetime using quasi in-situ infrared thermography and accelerated stress testing

In-line quality control diagnostics for roll-to-roll (R2R) manufacturing techniques will play a key role in the future commercialization of the polymer electrolyte membrane fuel cell (PEMFC) used in automotive applications. These diagnostics monitor the fabrication of the membrane electrode assembly (MEA), which detect and flag any non-uniformity that may potentially harm PEMFC performance and/or lifetime. This will require quantitative thresholds and a clear distinction between harmful defects and harmless coating irregularities. Thus, novel fuel cell hardware with quasi in-situ infrared (IR) thermography capabilities is utilized to understand how bare spots in the cathode electrode impact MEA lifetime. An accelerated stress test (AST) simulates chemical and mechanical degradation modes seen in vehicular operation. The actual open circuit voltage and rate of change of this voltage are used as in-situ indicators for MEA failure, enabling capture of the progression of failure point development. Bare spot coating irregularities located at the center of the electrode were found to have no impact on MEA lifetime when compared to a pristine MEA. However, MEA lifetime was found to be considerably shortened when these same irregularities are located at the cathode inlet and, especially, the anode inlet regions of the fuel cell.

SelfPaint-A self-programming paint booth

In this paper we present a unique Fraunhofer approach that aims towards a vision to automate the product preparation in paint shops by automatically generating robot paths and process conditions that guarantee a certain wanted paint coverage. This will be accomplished through a combination of state-of-the-art simulation technology, inline quality control by novel terahertz thickness measurement technology, and surface treatment technology. The benefits of the approach are a shortened product preparation time, increased quality and reduced material and energy consumption. The painting of a tractor fender is used to demonstrate the approach.

Vision system in quality control automation

Measurement of surface roughness is one of the quality control processes, usually carried out off line. Contact type surface roughness measurement method is commonly used in quality control. The processes consume lot of time with human interaction. In order to reduce or to eliminate non value added time, effective quality inspection tool and automation of the processes has to be utilized. An attempt has been made to automate the process with integration of vision camera in capturing the image of the component surface. The image process technique has the advantage of analyzing the single captured image for multiple area measurement. Hence, the in-line quality control of each component surface roughness measurement is ensured. The automation process involves component movement, image capturing, image processing, and decision making, using sensors, actuators and microcontroller. The proposed in-line quality control of surface roughness with vision system has been successfully developed. The designed automated system has fulfilled the objectives in respect of the scope of the present work.

Robotic Autoscanning of Highly Skewed Ship Propeller Blades

Abstract This paper presents an approach for a complete scanning of ship propeller blades. Inline quality control for advanced manufacturing or inspection of operational propeller blades requires automated and highly accurate 3D measurement systems. By combining an industrial robot with a high accuracy 3D camera and a laser distance sensor, the task at hand can be fully automated. The integrated system is described in detail, with focus on initial estimation of the propeller blade position and avoiding collisions with the blade while scanning. Validating experiments are performed where a highly skewed ship propeller blade is scanned with a resolution of 0.1 mm.

Smart Manufacturing of Thermoplastic CFRP Skins

High performance aerospace structures often require a combination of innovative materials and new production technologies. Carbon fiber reinforced thermoplastics (CFRTP) have shown their potentials over the last decades especially due to their competitive production rates. Thermoplastic matrix systems allow joining by welding, which is a major advantage for assembly. Production systems for flat thermoplastic organic sheets are readily available on the market, as well as advanced fiber placement and tape laying machines (AFP/ATL). But there is a lack of systems capable of fabricating 3D-curved, near net shaped patch preforms that may serve for mass-customization of standard parts, e.g. for future aerospace panel production. With the composite prepregs being stacked within the mold the fibers will undergo less reshaping during consolidation (i.e. debulking) thus giving a better control over fiber angles. We describe an autonomous smart manufacturing system that is capable of handling unique parts by means of a complete digital workflow from part design over automated cut-piece fabrication, generation of system related meta-information, virtual planning of grip and drop up to the final layup. The system consists of a preprocessing and production planning apps, an industrial robot, a gripper with an ultrasonic welder, a storage system for cut-piece supply, a computer vision system, a collision avoidance app and a logging system for process relevant production parameters for inline quality control. The described system was successfully used for the production of four thermoplastic CFRP skin segments each consisting of 104 cut-pieces.

Vision system in quality control automation

Measurement of surface roughness is one of the quality control processes, usually carried out off line. Contact type surface roughness measurement method is commonly used in quality control. The processes consume lot of time with human interaction. In order to reduce or to eliminate non value added time, effective quality inspection tool and automation of the processes has to be utilized. An attempt has been made to automate the process with integration of vision camera in capturing the image of the component surface. The image process technique has the advantage of analyzing the single captured image for multiple area measurement. Hence, the in-line quality control of each component surface roughness measurement is ensured. The automation process involves component movement, image capturing, image processing, and decision making, using sensors, actuators and microcontroller. The proposed in-line quality control of surface roughness with vision system has been successfully developed. The designed automated system has fulfilled the objectives in respect of the scope of the present work.

In-line stereo-camera assisted robotic spot welding quality control system

PurposeThe purpose of this study is to design a robotic inline measurement system for spot welding quality control to achieve process requirement without any operator during the manufacturing flow.Design/methodology/approachA robot manipulator carries a stereo-camera and an ultrasonic control probe. The center position of the spot welding point is determined by evaluating the results of the edge, gradient and symmetry approaches from the methods proposed up to now in the literature to increase reliability. The center position of the spot welding point, determined in the camera reference plane, is transferred to the robot base plane coordinates with the hand–eye calibration proposed in this manuscript. Weld quality is checked by the ultrasonic test probe located at the spot welding point.FindingsWhile operators can only control welding quality, the developed station can also evaluate the quality based on geometric accuracy by processing the deviation of the position of the spot welding points. The proposed calibration method and the results of other methods in the literature are presented in this study by comparing it with synthetic data in simulations and in practical application.Research limitations/implicationsThe quality control is performed not only for the spot welding made with robots but also for the manual welds as well. Because of vision configuration, and reliability issues, maximum allowable offset by the correct spot position is limited to 20 mm to position the manipulator for testing. The installation and pretest works of the developed robotic welding quality control station are completed in the Body Shop Area of Ford Otosan factory in Kocaeli/Turkey. The results of the robotic control process are monitored by the quality assurance team. Integration of automation with the production line will be completed and an inline measurement will be done.Originality valueIn this paper, a new hand–eye calibration method based on simple and closed-form analytical solutions has been presented. The objective function is defined as reducing the deviation in the point projection, rather than reducing the error in the calibration equation. To increase reliability, combining the results of existing centering algorithms for the detection of the strongly deformed spot welding spot center, although it is normally in a circular form, has been suggested.

Automated Defect Recognition as a Critical Element of a Three Dimensional X-ray Computed Tomography Imaging-Based Smart Non-Destructive Testing Technique in Additive Manufacturing of Near Net-Shape Parts

In this paper, a state of the art automated defect recognition (ADR) system is presented that was developed specifically for Non-Destructive Testing (NDT) of powder metallurgy (PM) parts using three dimensional X-ray Computed Tomography (CT) imaging, towards enabling online quality assurance and enhanced integrity confidence. PM parts exhibit typical defects such as microscopic cracks, porosity, and voids, internal to components that without an effective detection system, limit the growth of industrial applications. Compared to typical testing methods (e.g., destructive such as metallography that is based on sampling, cutting, and polishing of parts), CT provides full coverage of defect detection. This paper establishes the importance and advantages of an automated NDT system for the PM industry applications with particular emphasis on image processing procedures for defect recognition. Moreover, the article describes how to establish a reference library based on real 3D X-ray CT images of net-shape parts. The paper follows the development of the ADR system from processing 2D image slices of a measured 3D X-ray image to processing the complete 3D X-ray image as a whole. The introduced technique is successfully integrated into an automated in-line quality control system highly sought by major industry sectors in Oil and Gas, Automotive, and Aerospace.

Nanomanufacturing through microfluidic-assisted nanoprecipitation: Advanced analytics and structure-activity relationships

We have employed microfluidics (cross-shaped chip) for the preparation of drug-loaded poly(lactic acid-co-glycolic acid) (PLGA) nanoparticles. The polymer precipitates from an acetone solution upon its controlled laminar mixing (flow focusing) with an aqueous solution of a surfactant, allowing for an operator-independent, up-scalable and reproducible preparative process of nanoformulations.Firstly, using PEGylated surfactants we have compared batch and microfluidic processes, and showed the superior reproducibility of the latter and its strong dependency on the acetone/water ratio (flow rate ratio). We have then focused on the issue of purification from free surfactant, and employed advanced characterization techniques such as flow-through dynamic light scattering as the in-line quality control technique, and field flow fractionation (FFF) with dynamic and static light scattering detection, which allowed the detection of surfactant micelles in mixture with nanoparticles (hardly possible with stand-alone dynamic light scattering). Finally, we have shown that the choice of polymer and surfactant affects the release behaviour of a model drug (paclitaxel), with high molecular weight PLGA (RG756) and low molecular weight surfactant (tocopheryl poly(ethylene glycol) 1000 succinate, TPGS) apparently showing higher burst and accelerated release.

Predicting bulk lifetime values by applying wet chemistry H-termination for inline quality control of silicon wafers

The measurement of bulk lifetime values of as-cut wafers is a problematic issue. In this work, a MDPLinescan tool was directly integrated in the last stage of an inline wet chemistry tool. It is shown that running as-cut wafers through a bath of 5% HF solution with an inline transportation speed of 1m/min without rinsing will increase the effective lifetime value from 2µs to more than 100µs. Consequently, it is possible to forecast the bulk lifetime at later stages leading to an approach for early inline quality control. Multicrystalline wafers revealed the best correlation with an average prediction error of 15%. Monocrystalline wafers showed an average prediction error of 32%. Finally, a prediction of the bulk lifetime values for n-type wafers showed preliminary correlations with an error of 3%.

The Effect of Catalyst Layer Coating Irregularities on Fuel Cell Performance Induced By Load Cycling

The polymer electrolyte membrane fuel cell (PEMFC) is capable of high power outputs at low operating temperatures, making it an attractive alternative to the petroleum-based internal combustion engine (ICE) common in vehicular applications [1]. PEMFC commercialization is contingent on future cost reductions and durability improvements. According to the Department of Energy (DOE), fuel cell systems (FCS) will have to surpass annual production levels of 500,000 units at $40/kW in order to compete with current ICEs [2-3]. Roll-to-roll (R2R) methods can achieve high yields at decreased per-area costs, enabling FCS manufacturing and cost targets to be met. Unfortunately coating irregularities that harm the performance and/or durability of PEMFC membrane electrode assemblies (MEAs) can occur during R2R fabrication processing [4-5]. This work studies the effect of a subset of such irregularities on performance when operating the New European Drive Cycle (NEDC). If the MEA experiences statistically significant lower performance as a result of a coating irregularity, then the irregularity should be classified as a defect. Classification of irregularities as defects will ultimately assist the industry by developing threshold detection limits for in-line quality control diagnostics. Samples were made in-house by creating Pt/C electrodes of 5 cm2 area and 0.2/0.2 mg Pt/cm2 loading. These samples were either pristine or contained an intentionally introduced 100% catalyst reduction spot centered on the cathode. Electrode coating irregularities ranged from 0.0625 to 0.125 cm2, or 1.25% and 2.5% of the MEA active area, respectively. Membrane materials were NRE-211 (25 µm) and NRE-212 (50 µm). Operating conditions for all samples were Tcell: 80°C, anode/cathode relative humidity (RH) at 100/100%, 105/350 sccm H2/Air, and 150/150 kPa backpressure. The MEAs were conditioned and subsequently subjected to 1008 repetitions of the NEDC drive cycle. The single drive cycle profile of the NEDC is shown in Figure A. The NEDC combines urban driving conditions, i.e. low engine load and lower speeds similar to busy city driving, and extra-urban driving conditions, i.e. more transient operation and higher speeds similar to highway driving. At the beginning of life and every 72 cycles onwards, a current controlled polarization (VI) curve was performed. Figure B displays polarization data of two MEAs made with NRE-211 membrane: one pristine and one having a 0.0625 cm2 coating irregularity. The figure shows, for each sample, one VI curve taken at beginning of life and one at the end of test. While the performance at beginning of life was comparable for both samples, the sample with the coating irregularity showed a reduced performance after 1008 cycles when compared to the pristine sample. Figure C shows the cell open circuit voltage (OCV) as a function of cycle number. The four samples were made with NRE-211 and NRE-212 membranes: two pristine and two having a 0.125 cm2 coating irregularity. The MEA made with the 25 µm membrane experienced a sharp decline in OCV starting at around 500 cycles. Conversely, the MEA with the same sized irregularity but made with 50 µm membrane, retained its OCV throughout the entirety of the experiment. Figure D displays the performance normalized to the beginning of life at 1 A cm-2 for three MEAs made with 50 µm membrane. One was pristine and the other two had 0.0625 cm2 and 0.125 cm2 coating irregularities. The data indicate that throughout the entirety of the experiment the coating irregularities may have caused increased performance degradation. In this presentation, we will discuss how irregularity location and size can impact PEMFC performance, and how the NEDC drive cycle paired with electrochemical measurements can be potentially used as a defect classification method. References 1) Barbir, Frano. PEM Fuel Cells: Theory and Practice. Academic Press, 2013. 2) Marcinkoski, Jason et al. “Fuel Cell System Cost – 2015”. September 30, 2015. 3) James, Brian et al. “Mass Production Cost Estimation of Direct H2 PEM Fuel Cell Systems for Transportation Applications: 2015 Update”. December 2015. 4) Kundu, S., et al. Journal of Power Sources157.2 (2006): 650-656. 5) Benchmarking and Best Practices Center of Excellence. Manufacturing Fuel Cell Manhattan Project. November 2011. Figure 1

The Effect of Membrane Casting Irregularities on Initial Fuel Cell Performance

The polymer electrolyte membrane fuel cell (PEMFC) is a clean alternative to petroleum-based technologies such as the internal combustion engine (ICE). In order to be competitive with the ICE in transportation applications, fuel cell systems must have less than a 10% performance loss after 5,000 hours of operation while reaching cost targets of $40/kW [1,2]. The membrane electrode assembly (MEA), a proton conducting polymer electrolyte membrane (PEM) with attached platinum-containing catalyst layers and gas diffusion layers (GDLs), may possess non-uniformities in any of its constituent components, which could lead to performance losses [3,4]. This work studies a subset of casting irregularities located within the PEM to understand their potential impacts on PEMFC initial performance. If the MEA experiences statistically significant lower initial performance as a result of a casting irregularity, then this irregularity should be classified as a defect. Classification of irregularities as defects will ultimately assist the industry by developing threshold detection limits for in-line quality control diagnostics. Membrane material was cast on a web-line operating within and at the boundaries of the process window by controlling process parameters such as slot and coating gap, flow rate, and substrate speed. The resulting membrane material was either pristine or contained air bubbles, cracks, and contamination, ranging from 0.6 to 3 mm. Gas-diffusion electrodes (GDEs) were fabricated using an ultrasonic spray system. The active area and nominal loading of these GDEs were 50 cm2 and 0.2/0.2 mg Pt/cm2, respectively. MEAs were assembled in the cell by placing a sheet of fabricated membrane material in between two pristine GDEs. Operating conditions for all samples were Tcell: 80°C, anode/cathode relative humidity (RH) at 32/32 and 100/50%, 1.5/2 stoichiometric flow rates of H2/Air, and 150/150 kPa backpressure. Voltage controlled polarization (VI) curves were conducted using a 121 channel segmented fuel cell system. To quantify performance impacts the VI performance of the MEAs containing casting irregularities was subtracted from that of pristine reference MEAs. Thermal imaging was performed subsequent to the performance experiments to map hydrogen crossover to spatial performance [5]. Figure A shows initial VI curves performed at 32/32% RH for four pristine reference samples as well as two samples with casting irregularities. The VI curve data indicate that the samples with irregularities have statistically lower OCV values than the pristine samples. Figure B illustrates the experimental method using GT118 as a representative sample. Prior to the experiment the morphology and size of the casting irregularities were determined using optical microscopy. Sample GT118 contained two air bubbles with sizes of approximately 660 and 1416 µm as shown on the left of Figure B. Then spatial current density distributions were measured with the segmented cell to determine to what extent the casting irregularities caused localized performance losses. The red regions in the spatial current density distribution, shown in the center of Figure B, indicated the lowest local performances in the cell. Subsequent to the performance experiment, a spatial thermal imaging diagnostic was applied to determine regions of increased hydrogen crossover. In the thermal imaging map for GT118 as shown on the right of Figure B, the red boxes indicate air bubble locations and the white regions denote areas of increased hydrogen crossover. These data show the correlation between casting irregularity location, local performance decrease, and increased local hydrogen crossover. In this presentation, we will discuss the impacts of the various casting irregularities in the membrane, and how certain experimental methodologies can be potentially used as defect classification tools. References Marcinkoski, Jason et al. “Fuel Cell System Cost – 2015”. September 30, 2015.James, Brian et al. “Mass Production Cost Estimation of Direct H2 PEM Fuel Cell Systems for Transportation Applications: 2015 Update”. December 2015.Kundu, S., et al. Journal of Power Sources 157.2 (2006): 650-656.Benchmarking and Best Practices Center of Excellence. Manufacturing Fuel Cell Manhattan Project, November 2011 Bender, Guido, et al. Journal of Power Sources 253 (2014): 224-229. Figure 1

Conceptual approach for an in-line quality control system in Additive Manufacturing Powder Bed Fusion processes

Additive Manufacturing is one of the genuine hopes for the forth industrial revolution since digital data is controlling the whole layered production process. At the same time the geometric freedom and tool-free production assures a high degree of individualisation. But to be the driving force behind a new industrial revolution, a qualification of additive manufacturing processes is necessary so that the resulting products meet the required quality and safety standards in the different fields of application such as in handling technology or medical technology. This paper will discuss a conceptual approach for the development of an in-line quality control system in Additive Manufacturing Powder Bed Fusion processes using the example of the Selective Laser Sintering process.

Electromagnetic Non-Destructive Non-Contact Methods & Device for Evaluation Nanostructured Electrode Materials and Electrode Structure of Li-Ion Batteries.

Proprietary non-destructive non-contact (NDT) electromagnetic, holographic interferometry, gas discharge visualization, and combined methods, developed by Enerize, enable to evaluate properties of nano-structured powder of electrode materials, polymer and solid inorganic electrolytes, and interface of multi-layered electrode structures. Developed non-destructive testing methods & devices enable to optimize the technology, and quality of initial materials, components, and cells, including in-line control during battery production. These methods allow insure the safety and reliability of the batteries and reduce the cost of production Electromagnetic NDT inspection consists in estimation of the level of magnetic fields interaction between the primary and secondary transducers from the currents induced by the primary field in investigated object. Primary transducer creates magnetic field at alternating current passage on it. This magnetic field excites eddy currents in investigated object. Eddy currents create secondary magnetic field, which is directed towards the primary one, and the total field is less by the value of the secondary field. The value of secondary field depends on the value of induced primary eddy currents, and their value directly depends on the quality and controlled object properties. Thus, one can judge about controlled object quality by the value of summary magnetic field. Using these methods we can control without contact the following values: conductivity, defect availability, dielectric permeability, thickness and solve many other problems of non-destructive testing. The non-contact feature of these methods allows in-line quality control during synthesis of component materials as well as during production and final assembly of batteries, supercapacitors, solar cells, etc. Application of these systems results in improved product reliability and safety, while lowering overall manufacturing costs by reducing wastage and preventing defective components from being incorporated into the finished product. A number of mathematical tools are used for process description and modeling, for signal processing, and for generating properties control information based on analysis the dependences between the parameters the fields that are applied and the electro-physical characteristics the test article that measured. These include: mathematical descriptions of elastic waves in isotropic and anisotropic media; Maxwell’s and Laplace’s equations; mathematical tools for spectral transformations in different orthogonal bases; methods of defect identification and the processing and analysis of images using fuzzy logic and artificial neural networks.During presentation will be presented NDT methods and systems developed by Enerize for the following electromagnetic testing: determine specific conductivity, electromagnetic properties and composition of powdered materials, including nano powdered oxides and graphite for Li-ion batteries electrodes ; specific conductivity of thin films (transparent conductive oxides for solar cells, solid and polymer electrolytes, polymer membranes for fuel cells, etc.); non-contact electromagnetic testing to determine the interface resistance between current collector and active electrode mass; nondestructive determination of defects in multilayer structures based on combined ultrasonic and electromagnetic methods (e.g., “jelly-rolls” for batteries and supercapacitors) and other. The developed methods and equipment can be adapted from measurements of test articles or materials under static conditions to dynamic measurements during material synthesis. Enerize owns 14 US patents, 1 Great Britain patent, and numerous US patent applications in the area of Li-ion batteries, solar cells, and non-destructive non-contact testing..

Failure Point Analysis of Membrane Electrode Assemblies with Coating Irregularities

Cost has been one of the primary barriers to the commercialization of polymer electrolyte membrane fuel cells (PEMFCs), clean energy conversion devices used primarily for power generation applications. While system design improvements and the development of novel electrode materials with increased activity have helped lower costs, the primary driver of cost reduction will be manufacturing membrane electrode assemblies (MEAs) at high volume [1]. Recently developed in-line diagnostic tools to monitor quality have successfully detected a variety of electrode coating variations [2]. This work studies a subset of these electrode irregularities fabricated onto MEAs operating under accelerated stress tests (ASTs) to simulate stresses of real-world driving conditions while spatially monitoring the onset and development of failure points with a thermal camera. An understanding of the impact that electrode irregularities have on MEA lifetime will subsequently allow for (i) the potential classification of these irregularities as defects and (ii) the development of threshold detection limits for in-line quality control diagnostics. Catalyst-coated membranes (CCMs) and gas-diffusion electrodes (GDEs) were fabricated with an ExactaCoat Sono-Tek ultrasonic spray system. The active area and nominal loading of these Pt/C electrodes were 50 cm2 and 0.2/0.2 mgPt/cm2, respectively. Membrane material was NRE-212. These layers were laminated into edge-protected MEA structures using a hot-pressing process. The MEA structures were exposed to a combined chemical and mechanical AST by operating the fuel cell at 80°C and 0.5/0.5 SLM H2/Air under open circuit potential (OCV), and cycling between 0 and 80% relative humidity for a 30 second duty cycle. The hydrogen crossover limiting current and the OCV were indicators for a developing failure and the presence of a failure, respectively. A novel cell hardware shown in figure (a) was used to remove the cathode flow-field and conduct a spatial hydrogen crossover measurement. Any hydrogen crossing from the anode to the cathode exothermically reacts at the cathode catalyst with ambient air to produce a heat signature that is detected with the thermal camera [3]. Higher crossover rates at for example discrete failure points become apparent through a significant local temperature rise. Sample results of a pristine MEA tested as described above are shown in the figures. The graph (b) shows the hydrogen crossover limiting current density rapidly increasing after the OCV declined with an increasing rate. This indicated that the MEA developed a failure point. The images show the thermal response during the spatial hydrogen crossover measurements for the pristine MEA (c) prior to and (d) subsequent to aging. The heat signature indicated a failure point developed near the inlet of the cell. Results will include studies on MEA structures with intentionally and systematically introduced coating variations of various sizes and severities. References 1) S. Kamaruzzaman, and W.R. Daud. Renewable Energy 31.5 (2006). 2) M. Ulsh and B. Sopori and N.V. Aieta and G. Bender. ECS Transactions 50.2 (2013). 3) G. Bender and W. Felt, and M. Ulsh. Journal of Power Sources 253 (2014). Figure 1

In-line metrology of nanoscale features in semiconductor manufacturing systems

Quality control and defect monitoring are of great importance to the semiconductor industry. This article presents a system to enable inspection of nanoscale features in-line with nanomanufacturing processes. The ultimate goal of this research is to integrate this metrology system into current semiconductor manufacturing processes to enable true in-line wafer inspection and quality control. In the system presented in this paper, AFMs that have been shrunk down on to a single MEMS chip are used to scan the surface of a sample. A flexure-based mechanism allows the MEMS-based AFM to be positioned over a millimeter range of motion, with nanometer level precision when properly actuated. The performance of the system in areas such as positioning repeatability, AFM stability and measurement resolution are evaluated in this study. Owing to the small size of single-chip AFM (1 million times smaller than a conventional AFM instrument), it is a good candidate for multipoint detection. Overall, the system presented in this paper significantly shortens inspection time and dramatically decreases the setup time required for an AFM to load, approach, and measure a sample making in-line inspection of nanoscale features in semiconductor manufacturing systems feasible.

Multi-sensor approach to improve optical monitoring of papaya shrinkage during drying

This study aimed to assess the feasibility of a multi-sensor approach for predicting shrinkage of papaya during drying using computer vision methods in combination with optical scattering analysis of light at 650 nm. The top-side area and total surface area derived from computer vision were analyzed, while the illuminated area and light intensity from optical scattering images were used to interpret photon migration in the fruit tissue. The relationship between moisture content and shrinkage in terms of volume and area reduction during drying was satisfactorily explained by a linear model. The results demonstrated that the prediction of papaya shrinkage during drying from top and total surface areas of the sample was possible, but can potentially be improved. Multivariate correlations of computer vision parameters and optical scattering properties showed the enhanced performance for shrinkage prediction. This multi-sensor approach could possibly be applied as a fast, accurate and non-invasive technique for in-line quality control to monitor shrinkage in the production of dried fruits.

Continuous Manufacturing of High Quality Pharmaceutical Cocrystals Integrated with Process Analytical Tools for In-Line Process Control

A continuous manufacturing process for pharmaceutical indomethacin–saccharine cocrystals was achieved by extrusion processing with high throughput. Down-stream milling and blending of the extrudates was followed by feeding the formulated cocrystals in a capsule-filling machine. By applying a quality by design approach, the process was optimized and scaled up to produce 3000 capsules/h of pharmaceutical cocrystals. Process analytical tools such as near infrared reflectance and spatial filter velocimetry probes were coupled at various process stages for in-line monitoring and quality control. Further physicochemical characterization of extruded batches confirmed the manufacturing of high quality cocrystals. A fully integrated continuous process starting from raw materials to produce a finished product was assembled with only six unit operations and a small footprint. The study is a paradigm of continuous manufacturing of pharmaceutical cocrystals.