Design and fabrication of composite blades for the Mod-1 wind turbine generator

The design, tooling, fabrication, quality control, and testing phases carried out to date, as well as testing still planned are described. Differences from the 150 foot blade which were introduced for cost and manufacturing improvement purposes are discussed as well as the lightning protection system installed in the blades. Actual costs and manhours expended for Blade No. 2 are provided as a base, along with a projection of costs for the blade in production

An Incentive System for Salmonella Control in the Pork Supply Chain

This paper presents a dynamic principal-agent analysis of an incentive system for Salmonella control in the pork supply chain. The incentive system determines quality premiums to the producer, testing frequencies for hogs delivered, as well as charges to the producer for testing and penalties. Using cost estimates and technical parameters, we evaluate the cost effectiveness of plant and farm control measures and trade-offs between prevalence reduction and related costs and gains. We also assess the impact of ownership structure on incentive system parameters and performance for a wide range of prevalence threshold levels. Differences in control actions, bacteriological prevalence and the overall welfare gain for the chain are very small across ownership structures. Changes in the prevalence threshold level lead to substantial changes in the use of farm and plant control packages and performance measures.dynamic programming, food quality, principal-agent, Food Consumption/Nutrition/Food Safety, Livestock Production/Industries,

Integrated Computer Control of a Paper Machine: Quality Control

The integrated system is subdivided into five systems -- production planning, production supervising, process control, quality control and reporting. This report deals with quality control and presents the system for sampling and testing and the mathematical models used to describe the variations in quality variables. The design of estimators, predictors and interpolators using Kalman’s method is discussed. In conclusion, the implementation of the quality control system including its various programs is presented

The Mechanical Testing of Materials Using the Method of Digital Image Correlation

The mechanical testing of materials is regulated by standards, which established requirements for samples, test equipment, testing conditions and methods of processing the results. When performing tests, it is important to control the quality of the sample surface, its geometric dimensions and deviations from a predeterminedshape. Not less important stage of the testing is to control the fixing of the test specimen in the test equipment and the need to render its stress-strain state in the process of loading.Using the method of digital image correlation when conducting mechanical testing allows you to successfully control all phases of mechanical testing, from the quality of specimen production, testing equipment, to visualize the stress-strain state and its compliance with the adopted design scheme

Traceability requirements for information systems in the agro-food sector

Food safety and quality are keys to companies' business survival and great effort and resources are devoted to them. The food production chain, from the farms and feed mills to the finished products leaving the processing plants, is subject to independent examination and auditing either under the sector's own assurance schemes under official regulatory inspection and testing programmes with published results. For farmers and the agro-food industry, this means new market opportunities – and continual change. Food safety is an on-going challenge, demanding the best control systems and day-to-day vigilance on farms, in processing plants and throughout the distribution system. In order to enable consumers to make the right choice when buying their food and in order to build up markets for quality products, labelling has to provide all relevant information about the production process. Besides complete information about its ingredients, food labels should bear information about its place of origin and the way in which it was produced

Three Rs Approaches in the Production and Quality Control of Fish Vaccines

The workshop on Three Rs Approaches in the Production and Quality Control of Fish Vaccines aimed a) to identify animal tests currently stipulated for the production and quality control of fish vaccines and to highlight animal welfare concerns associated with these tests; b) to identify viable options to replace, reduce, and refine animal use for fish vaccine testing; and c) to discuss the way forward and set out how the Three Rs may be implemented without jeopardizing the quality of the vaccines. The workshop participants -- experts from academia, regulatory authorities, a scientific animal welfare organization, and the fish vaccine industry -- agreed that efforts should be undertaken to replace the vaccination challenge batch potency testing with tests based on antigen quantification or antibody response tests. Regulatory requirements of questionable scientific value and relevance for the quality of fish vaccines, such as the re-testing of batches produced outside Europe, or the double-dose batch safety test, should be re-considered. As an immediate measure the design of the current animal tests should be evaluated and modified in the light of refinement and reduction, for example, the number of unprotected control fish in vaccination-challenge tests should be reduced to the minimum

Pengambilan Keputusan Pemilihan HPLC (Alat Instrumen) Pada Lab. QC Dengan Metode Analitycal Hierarchy Process (AHP)

PT Bio Kusuma Pharmaceutical is a manufacturing company for pharmaceuticals, cosmetics and dietary supplements that was founded in 2003. The company is more engaged in topical medicines and creams for beauty. Increasing the existing market and productivity makes the company prioritize the success of production to increase the company's competitiveness. The increasing demand for products in the market has made PT Bio Kusuma Pharmaceutical have to increase its productivity. However, due to limited testing equipment in the laboratory, it is less effective in meeting the market. From August-October 2019, it showed a delay in testing due to too many batches of production but only one instrument in the laboratory. Production results that are not balanced with demand make the company unable to maximize its productivity due to inadequate testing equipment at the Quality Control laboratory. Based on data on comparison of production and testing in the laboratory where there is a delay in testing due to the inadequacy of the HPLC (High Performance Liquid Chromatography) testing instrument in the Quality Control (QC) laboratory, from this data the company requires additional HPLC (High Performance Liquid Chromatography) instrument tools. From the results of calculations using the AHP (Analytical Hierarchy Process) method, the HPLC (High Performance Liquid Chromatography) instrument from Acquity Arc (Waters) is obtained with a score of 0.46933 with evaluation factors for all criteria and 0.46932 with the ratio of benefits from alternatives.Keywords: Laboratory, HPLC (High Performance Liquid Chromatography), AHP (Analytical Hierarchy Process

PENGENDALIAN MUTU PRODUK PUPUK ORGANIK DAN ANALISIS KEUNTUNGAN DI GAPPPURO (GABUNGAN PETANI PENGELOLA PUPUK ORGANIK PONOROGO) KABUPATEN PONOROGO

Research purposes to determine the implementation of product quality control and analyze the advantages of organic fertilizer and organic fertilizer products in GAPPPURO for implementing quality control. Analysis used to answer the first objective is descriptive qualitative. And to answer the second goal by using statistical quality control techniques according to K. Ishikawa (1989). The results indicate the implementation of quality control of organic fertilizer products in GAPPPURO done by monitoring the start of the raw materials, to the production process, GAPPPURO also perform quality testing laboratory. The production of organic fertilizer according to Indonesia's National Standard menerapkam Quality Management System at the time of supervision in the process of packaging and marketing of organic fertilizer. Gains derived from the production of organic fertilizers obtained GAPPPURO for one year in the amount of Rp. 73,066,050, - with a total production of 799 500 Kg. Thus revenue Fee GAPPPURO of organic fertilizer after the sale of Farmers Group of Rp. 150/kg. HR in charge of controlling the quality of organic fertilizers assessed less than the maximum because GAPPPURO fairly broad scope. To overcome this GAPPPURO should add to the quality of human resources that are able to control the production process so that the quality of organic manure fertilizer to stay awake and avoid negative things, such as reducing the size of the formulation, not in accordance with the specified SOP etc. Keywords: Organic Fertilizer, Quality Control, Benefits, And GAPPPURO

Synthetic Data-Enhanced Deep Learning For Quality Control Of Automated Welding Processes

Automotive production systems are designed to produce large quantities in high quality and short throughput times and are therefore organized as line production. This places high quality requirements on the joining processes in automotive body shops, in which automated, robot-guided welding is a key process. The quality of these thermal joining processes depends on various physical and chemical influencing factors, whose interactions cannot be explicitly modelled. This leads to enormous quality assurance efforts in several quality control loops, which may include visual inspections, non-destructive testing of samples to assess the internal structure and destructive testing of samples for the assessment of mechanical properties such as tensile strength. Due to the increasing availability of data in automated processes and the complexity of welding processes, the application of Deep Learning has a great potential to reduce quality control efforts in automotive body shops. Using Deep Learning to leverage process data and accurately predict quality parameters in welding processes is investigated in research, yet model training requires a large, balanced and annotated dataset, whose generation is time and cost intensive, particularly for production data. However, there are generative AI methods such as Generative Adversarial Networks (GANs) that are able to generate synthetic data and thus offer the potential to generate a large amount of annotated production data with relatively little effort. This paper presents a systematic approach to evaluate the potential of incorporating synthetic data in a real-world production dataset to improve quality control using Deep Learning. The approach is validated for the analysis of real-world ultrasound images of resistance spot welding (RSW) processes from the automotive industry. Different Deep Learning architectures to generate synthetic data are compared. Results show that adding synthetic data to the training dataset can improve the accuracy of Deep Learning models for quality monitoring in welding processes

Best Management Practices to Enhance Water Quality: Who is Adopting Them?

This study investigates the determinants affecting producers’ adoption of some Best Management Practices (BMPs). Priors about the signs of certain variables are explicitly accounted for by testing for inequality restrictions through importance sampling. Education, gender, age, and on-farm residence are found to have significant effects on the adoption of some BMPs. Farms with larger animal production are more apt to implement manure management practices, crop rotation, and riparian buffer strips. Also, farms with larger cultivated acres are more inclined to implement herbicide control practices, crop rotation, and riparian buffer strips. Belonging to an agro-environment club has a positive impact for most BMPs.adoption, Bayesian analysis, best management practices, priors, runoff, water quality, Agribusiness, Agricultural and Food Policy, Crop Production/Industries, Farm Management, Food Consumption/Nutrition/Food Safety, Land Economics/Use, Livestock Production/Industries, Q12, Q25, C11,