Process Improvement by Lean Thinking in Trucking Industry

Manufacturing industries with complex production systems are struggling with designing optimal process to increase throughput. Companies will require high amount of labor and process improvement resources to sustain growth and delivery quality products to its customers. A chain of value added activities when designed and deployed with help of lean based methodologies can create high efficiency process. In this paper we have studies and implemented value added process based on the lean manufacturing methodologies which was adapted on the shop floor. In many traditional truck body production industries have facing many problems like low production rate, big lead times, material flow issues, nonlinear layout, late customer delivery and low quality. To address this problems, a mythology has been designed with implementing process techniques for low efficiency work stations. This study and implementation is conducted in crucial bottle neck areas. Tools used to conduct this study are time analysis, motion analysis, Standard working procedure (SWP), value stream analysis, 5S, Value layout, and bottleneck analysis. The value process implementation has converted production of two truck per day to three truck per day. Increase in production rate, quality and customer delivery have been witness when process is implemented and sustained

Moving social networking applications into the cloud

Social networking applications that are developed using traditional software and architecture have scalability issues. One way to overcome the high cost of scaling social applications is to use Cloud Computing (CC). There are various cloud computing platforms available. One very interesting CC platform is Google App Engine (GAE). This research focuses on using the “free” GAE as a way to re-implement existing social networking applications. The research focuses on how to move social applications into the cloud and on the evaluation of their performance. The thesis investigates the GAE platform, and its features. The study shows how to re-implement a social networking application using GAE cloud with limited code approximately 600 lines and evaluates the scalability of the applications

Effects of Chemically Characterized Fractions from Aerial Parts of Echinacea purpurea and E. angustifolia on Myelopoiesis in Rats

Echinacea species are used for beneficial effects on immune function, and various prevalent phytochemicals have immunomodulatory effects. Using a commercial E. purpurea (L.) Moench product, we have evaluated the myelopoietic effect on bone marrow of rats treated with various extracts and correlated this with their chemical class composition. Granulocyte/macrophage-colony forming cells (GM-CFCs) from femurs of female Sprague-Dawley rats were assessed at 24 h after 7 daily oral treatments. A 75 % ethanolic extract at 50 mg dried weight (derived from 227 mg aerial parts) per kg body weight increased GM-CFCs by 70 % but at 100 mg/kg was without effect. Ethanolic extracts from aerial parts of E. angustifolia DC. var. angustifolia andE. purpurea from the USDA North Central Regional Plant Introduction Station increased GM-CFCs by 3- and 2-fold, respectively, at 200 mg/kg (∼ 1400 mg/kg plant material). Extract from another USDA E. angustifoliawas inactive. Proton and APT NMR, MS, and TLC indicated alkylamides and caffeic-acid derivatives (CADs) present in ethanolic extracts of both the commercial and USDA-derived material. Cichoric and caftaric acids were prominent in both E. purpurea ethanolic extracts but absent in E. angustifolia. Aqueous extract of the commercial material exhibited polysaccharide and CAD signatures and was without effect on GM-CFCs. A methanol-CHCl3 fraction of commercial source, also inactive, was almost exclusively 1 : 4 nonanoic : decanoic acids, which were also abundant in commercial ethanolic extract but absent from USDA material. In conclusion, we have demonstrated an ethanol-extractable myelostimulatory activity in Echinacea aerial parts that, when obtained from commercial herbal supplements, may be antagonized by medium-chain fatty acids presumably derived from a non-plant additive

Enhancement of EPIR Switching Characteristics of PCMO RRAM Using Oxygen Deficient Al2Ox Diffusion Barrier

Resistive random access memory has gained lots of interest in the last decade as a promising replacement for non-volatile memory. Device retention stability and electric pulse induced resistance switching (EPIR) ratio (percent of change in resistance between the low and high resistance states) are very important characteristics of any resistive memory devices. Pr0.7Ca0.3MnO3 (PCMO) is one of the most promising materials which exhibit EPIR switching, however it suffers some short comings as low retention stability and low EPIR ratio. This work investigated the effect of oxygen ion/vacancy buffer layer of Al2Ox in metal/buffer layer/PCMO/Metal heterostructure prepared by RF sputtering in Ar only and Ar:O2 atmosphere. The diffusion barrier of the same is integrated into Pr0.7Ca0.3MnO3 (PCMO) to study the resistance switching and retention properties of this heterostructure. The internal Al2Ox barrier is placed between the “bulk” PCMO region of the sample and a top PCMO active interface region. The Al2Ox layer is believed to reduce/prevent change in the ion/vacancy concentration in the interface region after a certain concentration is set by the application of a short electric pulse, and also enhances the EPIR switching ratio. The switching performance of the buffer layer heterostructure has indicated that the buffer layer combined with top 10nm is active region in resistance switching. This work also addressed a model for the enhancement of the switching.Electrical and Computer Engineering, Department o

Revolutionizing aircraft maintenance: The role of predictive maintenance in aviation

This literature review synthesizes existing knowledge on the crucial role of data in predictive maintenance (PdM) within the aviation sector, examining its significance, benefits, and technological foundations. The review also investigates the broader relevance of PdM across various industries, drawing upon case studies related to PdM in aviation as practical examples. Through an extensive analysis of academic papers, industry reports, and empirical evidence, this review offers a comprehensive overview of the current state of research and practice in data-driven PdM, emphasizing its impact on reliability, safety, cost-efficiency, and the adoption of advanced data analytics and predictive models. This research investigates the pivotal role of data in predictive maintenance (PdM) within the aviation sector, elucidating its significance and benefits. Three primary research questions guide this study: Why is PdM important for aviation? This question highlights the unique challenges faced by airlines in maintaining a fleet of aircraft, emphasizing the criticality of PdM in ensuring safety, reliability, and cost-efficiency. What technologies are used in conducting PdM? This question delves into the technological foundations of PdM, elucidating the data sources, analytics tools, and predictive models employed in proactive maintenance practices. Is PdM relevant in other industries? This inquiry explores the transferability of PdM principles and methodologies to diverse industries beyond aviation, shedding light on the broader implications of data-driven maintenance strategies. The research draws upon an array of case studies related to PdM in the aviation industry and other industries, providing empirical evidence of its effectiveness and showcasing real-world applications. These case studies serve as valuable sources of practical insights and examples

Chemometric regression techniques as emerging, powerful tools in genetic association studies

The field of chemometrics has its origin in chemistry and has been widely applied to the evaluation of analytical chemical data and quantitative structure-activity relationships. Chemometric techniques apply statistical and algorithmic methods to extract information from analytical multivariate data, including fused, heterogeneous data. These techniques are now widely applied across fields as varied as food technology, environmental chemistry, process control, medical diagnostics, and metabolomics. In the mid-1980s, cross-disciplinary interaction between genetics and epidemiology led to the emergence of genetic epidemiology as a new discipline. Chemometric techniques are extremely appropriate for, and have been widely applied to, this discipline. Here, we present a broad review of the application of chemometric techniques to the fields of genetic epidemiology and statistical genetics. We also consider some future directions. We focus on chemometrics-based regression methodologies in genetic association studies

Thiamine-Based Nitrogen, Phosphorus, and Silicon Tri-doped Carbon for Supercapacitor Applications

This paper reports the synthesis of N, P, and Si tri-doped C (NPSiDC) using thiamine (a renewable resource material), silicone fluid, and ammonium polyphosphate. A one-pot microwave assisted method was utilized in synthesizing NPSiDC. The method is simple, rapid, and economical which does not employ any inert or reducing gases. Three variants of NPSiDCs were synthesized by varying the proportions of the precursor materials. NPSiDC-1 was found to have high specific surface area of 471 m² g^–1 and a single point total pore volume of 0.25 cm³ g^–1. Raman spectroscopy results revealed the presence of defects in an sp² C lattice. XPS analysis revealed the presence of N, P, Si, and O in C. NPSiDC-1 and NPSiDC-2 exhibited tremendous potential for supercapacitor applications with NPSiDC-1 recording highest specific capacitance value of 318 F g^–1 in 6 M KOH. NPSiDCs were discovered to be electrochemically stable after 2000 cycles in 6 M KOH

COVID‐19 vaccine hesitancy linked to increased internet search queries for side effects on fertility potential in the initial rollout phase following Emergency Use Authorization

The Emergency Use Authorization (EUA) of the COVID‐19 vaccine on December 11, 2020 has been met with hesitancy for uptake with some citing potential impacts on future fertility. We hypothesised that irrespective of sex, fertility‐related queries would markedly increase during the 48 days following EUA of the coronavirus vaccine. We sought to objectively identify trends in internet search queries on public concerns regarding COVID‐19 vaccine side effects on fertility that might impact vaccine uptake. We used Google Trends to investigate queries in Google's Search Engine relating to the coronavirus vaccine and fertility between 10/24/2020 and 1/27/2021. The five most queried terms were identified as: ‘COVID Vaccine Fertility’, ‘COVID Vaccine and Infertility’, ‘COVID Vaccine Infertility’, ‘COVID Vaccine Fertility CDC’, and ‘COVID 19 Vaccine Infertility’ with an increase of 710.47%, 207.56%, 264.35%, 2,943.7%, and 529.26%, respectively, all p < .001. This study indicates that there was an increase in online COVID‐19 vaccine‐related queries regarding fertility side effects coinciding with the Emergency Use Authorization (EUA) on December 11, 2020. Our results objectively evidence the increased concern regarding the vaccine and likely demonstrate a major cause for hesitancy in vaccine uptake. Future studies and counselling with patients should be undertaken to help mitigate these concerns