Design of an Integrated Microfluidic Paper-Based Chip and Inspection Machine for the Detection of Mercury in Food with Silver Nanoparticles

For most of the fast screening test papers for detecting Hg2+, the obtained results are qualitative. This study developed an operation for the μPAD and combined it with the chemical colorimetric method. Silver nanoparticle (AgNP) colloids were adopted as the reactive color reagent to combine and react with the Hg standards on the paper-based chip. Then, the RGB values for the color change were used to establish the standard curve (R2 > 0.99). Subsequently, this detection system was employed for the detection tests of actual samples, and the detected RGB values of the samples were substituted back to the formula to calculate the Hg2+ contents in the food. In this study, the Hg2+ content and recovery rate in commercially available packaged water and edible salts were measured. The research results indicate that a swift, economical, and simple detection method for Hg2+ content in food has been successfully developed.

Validation and optimization of a new instrument for measuring the performances of ultrafiltration membranes

In this study, we introduce the current situation of the membrane inspection industry. We have developed a new integrated rapid membrane inspection machine (MIM) to test the performances of nanofiltration or ultrafiltration membranes by measuring Silt Density Index (SDI) value (i.e., the key performance indicator) of the water filtered. This study optimizes many key conditions include temperature, pH value and pressures, then establishes an SDI detection new method of ultrafiltration membranes by using MIM. We set the temperature of the test liquid to 25 °C, pH in the range of 7–8, and pressure to approximately 0.10 MPa. The results reflect that MIM can be used to effectively determine the SDI of ultrafiltration membranes used the new method and the results of the method validation are satisfactory.

A Study on Radiation Imaging Mechanism and Characteristics in Different Inspection Systems

Radiation imaging, as a key issue in nuclear technology, has received considerable attention in the industry. It is widely used in nuclear medicine, Customs supervision, and many other areas. The objective of this investigation is to get insight into the principle, operation characteristics and image characteristics of radiation imaging. In this paper, an investigation on radiation imaging is conducted on three main inspection systems for Customs supervision, including small X-ray inspection machine, CT baggage inspection system, and large container inspection system. The principle, operation characteristics, evaluation indexes, pseudo-color processing and image characteristics are discussed in detail. The results indicate that the spatial resolution of small X-ray inspection machine is much higher than that of CT baggage/goods inspection system and large container/vehicle inspection system. It is a challenge to identify substances and specific shapes in the case of overlapping for small X-ray inspection system. Moreover, the mechanism of X-ray images is discussed as well. The radiation images are divided into three types, including two-dimensional, pseudo-color, high spatial resolution; two-dimensional, gray, high spatial resolution; three-dimensional, pseudo-color, high density resolution. The further investigation on machine inspection images is suggested to focus on the application environment. For some objects with specific characteristics, such as amorphous, explosive, the CT baggage inspection has much better performance than other systems. The research in this paper reveals the mechanism, parametric effect and imaging characteristics. It could provide a necessary foundation for the follow-up intelligent processing, detection, identification and annotation for radiation imaging in nuclear area. The research on inspection devices could lend strong experience to medical treatment, industry and many other fields.

TECHNOLOGICAL CAPACITY UPDATING OF CONTINUOUS RUN-IN GEAR GRINDING METHOD

The work purpose consists in the technological capacity updating of the method for cog-wheel continuous run-in gear grinding based on the purpose of efficient modes and characteristics of the worm disk. The investigation methods are based on mathematical modeling and planning experiments. Machining aircraft cylindrical cog-wheels and special samples was carried out on modern NC machines, benches and plants with the use of up-to-date test equipment: coordinate inspection machine KIM R-100 “Klingelnberg”, profile meter MarSurf M300S “Mahr”, optical microscope Axiovert 400MAT “Zeiss”, electronic scanning microscope Tescan Mira3 “Tescan”, micro-hardness gage Micro Met 5104 “Buehler”, X-ray diffractometer Xstress Robot “Stresstech OY”, Barkhausen digital nose analyzer Rollscan 350 “StresstechOY”, plant APOON on the well-known and developed techniques. The research results and novelty. Special strategy and cutting modes at the required characteristics of the combined polish-grinding worm allow ensuring gear profile roughness Ra=0.089 mkm keeping high accuracy of a ring gear (gear profile error Fa=1.6mkm) without gear honing thereby increasing productivity. The quality researches of gear surface layer give grounds for the application of the method for aircraft cog wheels.

Demystifying data and AI for manufacturing: case studies from a major computer maker

In this article, we discuss the backgrounds and technical details about several smart manufacturing projects in a tier-one electronics manufacturing facility. We devise a process to manage logistic forecast and inventory preparation for electronic parts using historical data and a recurrent neural network to achieve significant improvement over current methods. We present a system for automatically qualifying laptop software for mass production through computer vision and automation technology. The result is a reliable system that can save hundreds of man-years in the qualification process. Finally, we create a deep learning-based algorithm for visual inspection of product appearances, which requires significantly less defect training data compared to traditional approaches. For production needs, we design an automatic optical inspection machine suitable for our algorithm and process. We also discuss the issues for data collection and enabling smart manufacturing projects in a factory setting, where the projects operate on a delicate balance between process innovations and cost-saving measures.