This document discusses how big data analytics can be used to analyze process data and optimize processes in various industries. It provides examples of how latent variable methods like principal component analysis and projection to latent structures have been used with large process data sets to 1) troubleshoot problems, 2) optimize processes and product quality, and 3) monitor and control processes. Specific case studies describe how these methods helped identify causes of low yields in drying an agrochemical, optimized blending of raw materials in pharmaceutical manufacturing, and improved monitoring and control of batch and continuous processes.
The document presents a project report on biodiesel. It begins by acknowledging contributors to the project. It then lists the objectives of studying biodiesel as an alternative fuel and its comparative properties with petrodiesel. Several production techniques for biodiesel are described, including transesterification, the most common method. Test results from a case study of a biodiesel company show properties and production process. Comparative results from engine tests burning biodiesel-diesel blends show impacts on performance and emissions. The presentation evaluates biodiesel's potential as a sustainable fuel for India.
The document provides information on Teikoku, the world's largest manufacturer of canned motor pumps. It describes key features of Teikoku canned motor pumps including their sealless and leak-proof design, compact size requiring no alignment, ability to handle toxic and hazardous fluids, quiet operation, and field repairability. The pumps are suitable for applications involving vacuum, high pressure, high temperatures, and hazardous materials.
The document discusses various tools used in a fitting shop for assembling manufactured parts. It describes holding, cutting, striking, and measuring tools. Specific tools covered include bench vices, hacksaws, files, chisels, drills, reamers, taps, dies, hammers, scribers, and micrometers. The document provides details on the parts and types of each tool.
Horizontal CNC milling refers to CNC milling operations that use horizontally oriented tooling that can move along five axes. A horizontal milling machine consists of a base, table, column, knee, saddle, spindle, overhanging arm, arbor support, and arbor. A CNC system includes a part program, machine control unit, and machine tool. Common CNC machine tools are horizontal lathes, machining centers, and boring mills. CNC milling involves CAD model design, CAM conversion to a CNC program, machine setup, and machining operation execution.
The document discusses two methods for underwater welding: wet welding and dry welding. Wet welding involves welding directly in water and has advantages such as being the cheapest and fastest method, but disadvantages such as poor visibility and risk of hydrogen embrittlement. Dry welding involves welding in a pressurized chamber and has advantages like better weld quality and worker safety, but higher costs associated with the complex equipment required. The document compares the pros and cons of each welding method.
This presentation provides an overview of biodiesel. It discusses that biodiesel is made from renewable bio products like vegetable oils and animal fats. It can be used in pure form or blended with petroleum diesel. The document then covers biodiesel blends, origins, applications including use in trains and aircraft, production levels, feedstocks used, the food vs fuel debate, and the biodiesel manufacturing process.
Lubricants are materials that are applied between moving parts to reduce friction and dissipate heat. They can be solid, semi-solid, or liquid. Greases are commonly used semi-solid lubricants that are applied between parts using grease guns. Oils are widely used liquid lubricants, with mineral oils being the most common. Solid lubricants like graphite are used in high temperature applications over 200°C. Relubrication intervals for grease lubricated roller bearings can range from 20 hours to over 20,000 hours depending on factors like bearing size, speed, and temperature.
The document presents a project report on biodiesel. It begins by acknowledging contributors to the project. It then lists the objectives of studying biodiesel as an alternative fuel and its comparative properties with petrodiesel. Several production techniques for biodiesel are described, including transesterification, the most common method. Test results from a case study of a biodiesel company show properties and production process. Comparative results from engine tests burning biodiesel-diesel blends show impacts on performance and emissions. The presentation evaluates biodiesel's potential as a sustainable fuel for India.
The document provides information on Teikoku, the world's largest manufacturer of canned motor pumps. It describes key features of Teikoku canned motor pumps including their sealless and leak-proof design, compact size requiring no alignment, ability to handle toxic and hazardous fluids, quiet operation, and field repairability. The pumps are suitable for applications involving vacuum, high pressure, high temperatures, and hazardous materials.
The document discusses various tools used in a fitting shop for assembling manufactured parts. It describes holding, cutting, striking, and measuring tools. Specific tools covered include bench vices, hacksaws, files, chisels, drills, reamers, taps, dies, hammers, scribers, and micrometers. The document provides details on the parts and types of each tool.
Horizontal CNC milling refers to CNC milling operations that use horizontally oriented tooling that can move along five axes. A horizontal milling machine consists of a base, table, column, knee, saddle, spindle, overhanging arm, arbor support, and arbor. A CNC system includes a part program, machine control unit, and machine tool. Common CNC machine tools are horizontal lathes, machining centers, and boring mills. CNC milling involves CAD model design, CAM conversion to a CNC program, machine setup, and machining operation execution.
The document discusses two methods for underwater welding: wet welding and dry welding. Wet welding involves welding directly in water and has advantages such as being the cheapest and fastest method, but disadvantages such as poor visibility and risk of hydrogen embrittlement. Dry welding involves welding in a pressurized chamber and has advantages like better weld quality and worker safety, but higher costs associated with the complex equipment required. The document compares the pros and cons of each welding method.
This presentation provides an overview of biodiesel. It discusses that biodiesel is made from renewable bio products like vegetable oils and animal fats. It can be used in pure form or blended with petroleum diesel. The document then covers biodiesel blends, origins, applications including use in trains and aircraft, production levels, feedstocks used, the food vs fuel debate, and the biodiesel manufacturing process.
Lubricants are materials that are applied between moving parts to reduce friction and dissipate heat. They can be solid, semi-solid, or liquid. Greases are commonly used semi-solid lubricants that are applied between parts using grease guns. Oils are widely used liquid lubricants, with mineral oils being the most common. Solid lubricants like graphite are used in high temperature applications over 200°C. Relubrication intervals for grease lubricated roller bearings can range from 20 hours to over 20,000 hours depending on factors like bearing size, speed, and temperature.
The document discusses a fuel nano-additive technology that uses cerium oxide nanoparticles as a fuel borne catalyst. It provides background on nanotechnology and describes how cerium oxide improves fuel combustion efficiency and reduces emissions when mixed into fuel at the nanoscale. Laboratory tests conducted on a diesel engine in Vietnam found that the nano-additive reduced fuel consumption and particulate emissions while increasing combustion pressure over 56 hours of operation with no adverse effects.
The document outlines a workshop theory and practice course, including its objectives, requirements, schedule and grading. The course covers workshop safety, tools, measuring instruments, fitting work, welding processes and machine operation. Students will complete individual and group exercises applying these skills. They will also design and fabricate two group projects - a tool box and wheelbarrow wheel - to further develop their workshop abilities. Evaluation is based on exams, exercises, projects and class participation.
This document discusses various types of biofuels including ethanol, biodiesel, biogas, and algal biofuel. It provides information on their production processes and advantages and disadvantages. Some key points include:
- Biofuels are fuels produced from biomass such as plants and algae. Common types include ethanol, biodiesel, and biogas.
- Ethanol is typically produced from sugars and starches through fermentation. Biodiesel is made through a chemical process called transesterification of vegetable oils.
- Biogas is produced through anaerobic digestion of organic waste to produce a methane-rich gas.
- Algal biofuel is in research and development with
The document provides an overview of Rittal's PS 4000s enclosure system, including:
- The PS profile offers maximum stability using a 9-fold profile design with a 24-row 25mm grid hole pattern for universal assembly without manual machining.
- The enclosures are tested to international standards to guarantee high quality and come in various sizes, configurations, and options.
- Product details are provided like materials, finishes, included components, and protection ratings for the different PS 4000s enclosure models.
- Specification tables list the technical details and product codes for the enclosures.
John Crane gas seals provide maximum reliability through ensuring a clean and dry seal environment. Key factors include filtering the gas to 1 micron, using coalescing filters to remove liquids, heating the gas above hydrate and liquid formation points, and using an SEPro system to provide heated filtered gas to the seals during shutdown periods. It is also important to properly monitor the outer barrier seal, ensure adequate separation from bearing oil, and have the OEM test the job seal system to validate performance matches duty conditions.
The document discusses jig boring machines. It provides information on:
1) The need for jig boring machines to achieve high accuracy of hole positions and sizes that is demanded for applications like dies and fixtures.
2) The working principle of jig boring, which involves moving either the rotating tool or stationary workpiece to bore holes into the workpiece.
3) The typical construction of jig boring machines, including features like the table, saddle, column, and spindle head that provide movement capabilities.
Automated well test analysis ii using ‘well test auto’Alexander Decker
This document describes an automated computer program called WELL TEST AUTO that was developed to fully automate well test analysis and interpretation. The program selects reservoir models and estimates parameter values. It was tested on 10 datasets, including simulated and actual field data. Selected results from 3 of the datasets are presented, showing that the program correctly identified the reservoir model and provided acceptable estimates of parameters like permeability and skin. The program implements an artificial intelligence approach to automate the entire well test interpretation workflow in a visual basic program.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
The document presents a study that compares five methods for estimating missing values in building sensor data: linear regression, weighted k-nearest neighbors, support vector machines, mean imputation, and replacing missing values with zero. The methods were evaluated using data from sensors in an office building in Japan, with the amount of missing data varied from 5% to 20%. Feature selection and inclusion of lagged variables as predictors were also examined to determine their effect on the methods' performance.
Kelly zyngier oil&gasbookchapter_july2013Jeffrey Kelly
This document discusses modeling unit operations for production flowsheets in process industries. It describes six basic unit operation models - blenders, splitters, separators, reactors, fractionators, and black boxes. Blenders are modeled using recipes that specify the fraction of each inlet stream in the outlet stream. Splitters are modeled using split ratios that specify the fraction of the inlet stream in each outlet stream. The models allow representing both continuous and batch processes at steady-state.
Unit-Operation Nonlinear Modeling for Planning and Scheduling ApplicationsAlkis Vazacopoulos
The focus of this chapter is to detail the quantity and quality modeling aspects of production flowsheets found in all process industries. Production flowsheets are typically at a higher-level than process flowsheets given that in many cases more direct business or economic related decisions are being made such as maximizing profit and performance for the overall plant and/or for several integrated plants together with shared resources. These decisions are usually planning and scheduling related, often referred to as production control, which require a larger spatial and temporal scope compared to more myopic process flowsheets which detail the steady or unsteady-state material, energy and momentum balances of a particular process unit-operation over a relatively short time horizon. This implies that simpler but still representative mathematical models of the individual processes are necessary in order to solve the multi time-period nonlinear system using nonlinear optimizers such as successive linear programming (SLP) and sequential quadratic programming (SQP). In this chapter we describe six types of unit-operation models which can be used as fundamental building blocks or objects to formulate large production flowsheets. In addition, we articulate the differences between continuous and batch processes while also discussing several other important implementation issues regarding the use of these unit-operation models within a decision-making system. It is useful to also note that the quantity and quality modeling system described in this chapter complements the quantity and logic modeling used to describe production and inventory systems outlined in Zyngier and Kelly (2009).
This document summarizes a research article that develops two multi-stage stochastic linear programming models to determine an optimal aggregate production plan for a furniture manufacturing company with uncertain demand and production capacity. The models consider these factors as random variables. Model I uses a continuous probability distribution and can only solve problems for up to 3 periods due to complexity. Model II uses a discrete distribution and can solve for up to 4 periods. Both models generate scenario trees. The article compares the models' efficiency in solving time, iterations, expected value, wait-and-see value, and expected value of perfect information. An extensive sensitivity analysis varying costs, service level, and probability distribution parameters provides interesting results. The novelty includes considering a service level constraint, reporting multiple
Supply chain design under uncertainty using sample average approximation and ...SSA KPI
This document summarizes a study on supply chain design under uncertainty. The authors present a two-stage stochastic programming model of a supply chain consisting of splitting and combining production processes. The first stage involves strategic decisions about facility locations and capacities. The second stage models operational decisions over multiple time periods to satisfy uncertain demand. Short-term demand uncertainty is modeled using forecasting and scenario generation methods. The authors solve the problem using sample average approximation combined with dual decomposition and present computational results for different sample sizes and levels of data aggregation in the second stage.
This document discusses and compares five predictive data mining techniques: principal component analysis, correlation coefficient analysis, principal component regression, nonlinear partial least squares, and linear regression. It first provides background on data acquisition, preparation, and preprocessing techniques. It then describes each predictive technique, including how they handle issues like collinearity in datasets. Finally, it discusses how these techniques will be applied to four different datasets and the results compared to determine which technique best predicts the response variable while reducing variables.
This document discusses quality of service management. It provides an overview of Oracle Database Quality of Service Management which allows administrators to manage service levels on Oracle RAC, RAC One Node databases, and Exadata. It ensures predictable performance, dynamically allocates resources to meet SLAs, and reduces costs by optimizing resource use. Several quality management tools are also described, including check sheets, control charts, Pareto charts, scatter plots, Ishikawa diagrams, histograms. Additional related topics like quality management systems and standards are listed.
Stochastic behavior analysis of complex repairable industrial systemsISA Interchange
The document presents a novel technique called particle swarm optimization-based Lambda-Tau (PSOBLT) for analyzing the stochastic behavior of complex repairable industrial systems using uncertain data. PSOBLT combines Lambda-Tau methodology and particle swarm optimization to model system interactions using Petri nets and optimize the membership functions of reliability indices like failure rate and repair time. The technique reduces uncertainty in behavior analysis results compared to existing methods. The document demonstrates PSOBLT on a paper mill feeding unit to analyze system performance and help managers improve profit through maintenance strategies.
The document proposes streaming algorithms for performing Pearson's chi-square goodness-of-fit test in a streaming setting with minimal assumptions. It presents algorithms for the one-sample and two-sample continuous chi-square tests that use O(K^2log(N)√N) space, where K is the number of bins and N is the stream length. It also shows that no sublinear solution exists for the categorical chi-square test and provides a heuristic algorithm. The algorithms are validated on real and synthetic data and can detect deviations from distributions or differences between streams with low memory requirements.
Analytical engineering uses both theoretical and empirical methods to inform product design decisions. Theoretical methods include mathematical modeling and simulation, while empirical methods involve physical testing and measurement. Early in design, theoretical tolerance analysis is used, while later empirical metrology data from prototypes is combined with simulation to validate models. For complex issues like component deflection under load, a hybrid approach using initial modeling followed by targeted physical testing and model validation is most effective. Combining methods alleviates limitations of any single approach and ensures high quality data at all stages of design.
This document summarizes the analysis of data from a pharmaceutical company to model and predict the output variable (titer) from input variables in a biochemical drug production process. Several statistical models were evaluated including linear regression, random forest, and MARS. The analysis involved developing blackbox models using only controlled input variables, snapshot models using all input variables at each time point, and history models incorporating changes in input variables over time to predict titer values. Model performance was compared using cross-validation.
This document evaluates the MATLAB toolbox MATCONT for constructing bifurcation diagrams of chemical process systems. MATCONT is a relatively new software that allows for the continuation of static and dynamic equilibria of nonlinear systems. The document demonstrates MATCONT's capabilities using a well-studied example of a nonlinear ethanol fermentation process that exhibits rich dynamic behavior including multiplicity, oscillations, and chaos. The document concludes that MATCONT is a robust, flexible, and user-friendly tool recommended for bifurcation analysis of nonlinear systems in both research and teaching.
The document discusses a fuel nano-additive technology that uses cerium oxide nanoparticles as a fuel borne catalyst. It provides background on nanotechnology and describes how cerium oxide improves fuel combustion efficiency and reduces emissions when mixed into fuel at the nanoscale. Laboratory tests conducted on a diesel engine in Vietnam found that the nano-additive reduced fuel consumption and particulate emissions while increasing combustion pressure over 56 hours of operation with no adverse effects.
The document outlines a workshop theory and practice course, including its objectives, requirements, schedule and grading. The course covers workshop safety, tools, measuring instruments, fitting work, welding processes and machine operation. Students will complete individual and group exercises applying these skills. They will also design and fabricate two group projects - a tool box and wheelbarrow wheel - to further develop their workshop abilities. Evaluation is based on exams, exercises, projects and class participation.
This document discusses various types of biofuels including ethanol, biodiesel, biogas, and algal biofuel. It provides information on their production processes and advantages and disadvantages. Some key points include:
- Biofuels are fuels produced from biomass such as plants and algae. Common types include ethanol, biodiesel, and biogas.
- Ethanol is typically produced from sugars and starches through fermentation. Biodiesel is made through a chemical process called transesterification of vegetable oils.
- Biogas is produced through anaerobic digestion of organic waste to produce a methane-rich gas.
- Algal biofuel is in research and development with
The document provides an overview of Rittal's PS 4000s enclosure system, including:
- The PS profile offers maximum stability using a 9-fold profile design with a 24-row 25mm grid hole pattern for universal assembly without manual machining.
- The enclosures are tested to international standards to guarantee high quality and come in various sizes, configurations, and options.
- Product details are provided like materials, finishes, included components, and protection ratings for the different PS 4000s enclosure models.
- Specification tables list the technical details and product codes for the enclosures.
John Crane gas seals provide maximum reliability through ensuring a clean and dry seal environment. Key factors include filtering the gas to 1 micron, using coalescing filters to remove liquids, heating the gas above hydrate and liquid formation points, and using an SEPro system to provide heated filtered gas to the seals during shutdown periods. It is also important to properly monitor the outer barrier seal, ensure adequate separation from bearing oil, and have the OEM test the job seal system to validate performance matches duty conditions.
The document discusses jig boring machines. It provides information on:
1) The need for jig boring machines to achieve high accuracy of hole positions and sizes that is demanded for applications like dies and fixtures.
2) The working principle of jig boring, which involves moving either the rotating tool or stationary workpiece to bore holes into the workpiece.
3) The typical construction of jig boring machines, including features like the table, saddle, column, and spindle head that provide movement capabilities.
Automated well test analysis ii using ‘well test auto’Alexander Decker
This document describes an automated computer program called WELL TEST AUTO that was developed to fully automate well test analysis and interpretation. The program selects reservoir models and estimates parameter values. It was tested on 10 datasets, including simulated and actual field data. Selected results from 3 of the datasets are presented, showing that the program correctly identified the reservoir model and provided acceptable estimates of parameters like permeability and skin. The program implements an artificial intelligence approach to automate the entire well test interpretation workflow in a visual basic program.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
The document presents a study that compares five methods for estimating missing values in building sensor data: linear regression, weighted k-nearest neighbors, support vector machines, mean imputation, and replacing missing values with zero. The methods were evaluated using data from sensors in an office building in Japan, with the amount of missing data varied from 5% to 20%. Feature selection and inclusion of lagged variables as predictors were also examined to determine their effect on the methods' performance.
Kelly zyngier oil&gasbookchapter_july2013Jeffrey Kelly
This document discusses modeling unit operations for production flowsheets in process industries. It describes six basic unit operation models - blenders, splitters, separators, reactors, fractionators, and black boxes. Blenders are modeled using recipes that specify the fraction of each inlet stream in the outlet stream. Splitters are modeled using split ratios that specify the fraction of the inlet stream in each outlet stream. The models allow representing both continuous and batch processes at steady-state.
Unit-Operation Nonlinear Modeling for Planning and Scheduling ApplicationsAlkis Vazacopoulos
The focus of this chapter is to detail the quantity and quality modeling aspects of production flowsheets found in all process industries. Production flowsheets are typically at a higher-level than process flowsheets given that in many cases more direct business or economic related decisions are being made such as maximizing profit and performance for the overall plant and/or for several integrated plants together with shared resources. These decisions are usually planning and scheduling related, often referred to as production control, which require a larger spatial and temporal scope compared to more myopic process flowsheets which detail the steady or unsteady-state material, energy and momentum balances of a particular process unit-operation over a relatively short time horizon. This implies that simpler but still representative mathematical models of the individual processes are necessary in order to solve the multi time-period nonlinear system using nonlinear optimizers such as successive linear programming (SLP) and sequential quadratic programming (SQP). In this chapter we describe six types of unit-operation models which can be used as fundamental building blocks or objects to formulate large production flowsheets. In addition, we articulate the differences between continuous and batch processes while also discussing several other important implementation issues regarding the use of these unit-operation models within a decision-making system. It is useful to also note that the quantity and quality modeling system described in this chapter complements the quantity and logic modeling used to describe production and inventory systems outlined in Zyngier and Kelly (2009).
This document summarizes a research article that develops two multi-stage stochastic linear programming models to determine an optimal aggregate production plan for a furniture manufacturing company with uncertain demand and production capacity. The models consider these factors as random variables. Model I uses a continuous probability distribution and can only solve problems for up to 3 periods due to complexity. Model II uses a discrete distribution and can solve for up to 4 periods. Both models generate scenario trees. The article compares the models' efficiency in solving time, iterations, expected value, wait-and-see value, and expected value of perfect information. An extensive sensitivity analysis varying costs, service level, and probability distribution parameters provides interesting results. The novelty includes considering a service level constraint, reporting multiple
Supply chain design under uncertainty using sample average approximation and ...SSA KPI
This document summarizes a study on supply chain design under uncertainty. The authors present a two-stage stochastic programming model of a supply chain consisting of splitting and combining production processes. The first stage involves strategic decisions about facility locations and capacities. The second stage models operational decisions over multiple time periods to satisfy uncertain demand. Short-term demand uncertainty is modeled using forecasting and scenario generation methods. The authors solve the problem using sample average approximation combined with dual decomposition and present computational results for different sample sizes and levels of data aggregation in the second stage.
This document discusses and compares five predictive data mining techniques: principal component analysis, correlation coefficient analysis, principal component regression, nonlinear partial least squares, and linear regression. It first provides background on data acquisition, preparation, and preprocessing techniques. It then describes each predictive technique, including how they handle issues like collinearity in datasets. Finally, it discusses how these techniques will be applied to four different datasets and the results compared to determine which technique best predicts the response variable while reducing variables.
This document discusses quality of service management. It provides an overview of Oracle Database Quality of Service Management which allows administrators to manage service levels on Oracle RAC, RAC One Node databases, and Exadata. It ensures predictable performance, dynamically allocates resources to meet SLAs, and reduces costs by optimizing resource use. Several quality management tools are also described, including check sheets, control charts, Pareto charts, scatter plots, Ishikawa diagrams, histograms. Additional related topics like quality management systems and standards are listed.
Stochastic behavior analysis of complex repairable industrial systemsISA Interchange
The document presents a novel technique called particle swarm optimization-based Lambda-Tau (PSOBLT) for analyzing the stochastic behavior of complex repairable industrial systems using uncertain data. PSOBLT combines Lambda-Tau methodology and particle swarm optimization to model system interactions using Petri nets and optimize the membership functions of reliability indices like failure rate and repair time. The technique reduces uncertainty in behavior analysis results compared to existing methods. The document demonstrates PSOBLT on a paper mill feeding unit to analyze system performance and help managers improve profit through maintenance strategies.
The document proposes streaming algorithms for performing Pearson's chi-square goodness-of-fit test in a streaming setting with minimal assumptions. It presents algorithms for the one-sample and two-sample continuous chi-square tests that use O(K^2log(N)√N) space, where K is the number of bins and N is the stream length. It also shows that no sublinear solution exists for the categorical chi-square test and provides a heuristic algorithm. The algorithms are validated on real and synthetic data and can detect deviations from distributions or differences between streams with low memory requirements.
Analytical engineering uses both theoretical and empirical methods to inform product design decisions. Theoretical methods include mathematical modeling and simulation, while empirical methods involve physical testing and measurement. Early in design, theoretical tolerance analysis is used, while later empirical metrology data from prototypes is combined with simulation to validate models. For complex issues like component deflection under load, a hybrid approach using initial modeling followed by targeted physical testing and model validation is most effective. Combining methods alleviates limitations of any single approach and ensures high quality data at all stages of design.
This document summarizes the analysis of data from a pharmaceutical company to model and predict the output variable (titer) from input variables in a biochemical drug production process. Several statistical models were evaluated including linear regression, random forest, and MARS. The analysis involved developing blackbox models using only controlled input variables, snapshot models using all input variables at each time point, and history models incorporating changes in input variables over time to predict titer values. Model performance was compared using cross-validation.
This document evaluates the MATLAB toolbox MATCONT for constructing bifurcation diagrams of chemical process systems. MATCONT is a relatively new software that allows for the continuation of static and dynamic equilibria of nonlinear systems. The document demonstrates MATCONT's capabilities using a well-studied example of a nonlinear ethanol fermentation process that exhibits rich dynamic behavior including multiplicity, oscillations, and chaos. The document concludes that MATCONT is a robust, flexible, and user-friendly tool recommended for bifurcation analysis of nonlinear systems in both research and teaching.
The document introduces a new data management system called Metadata Event Log (MEL) to store inconsistent metadata entries from a large-scale landslide monitoring project. MEL uses a tabular format to record sensor node metadata and events over time without a rigid data structure. Functions are written to query MEL and infer missing data, returning relevant entries within the specified time period. The system provides a flexible way to track dynamic sensor node updates compared to traditional rigid data management systems.
Ying hua, c. (2010): adopting co-evolution and constraint-satisfaction concep...ArchiLab 7
This document summarizes a research paper that proposes using genetic algorithms combined with co-evolution and constraint-satisfaction concepts to solve supply chain network design problems. The paper first reviews supply chain integration models, genetic algorithms, co-evolutionary modes, and constraint-satisfaction modes from previous literature. It then presents a supply chain network model with multiple levels and costs. The model aims to minimize total costs while meeting demand and resource constraints. Finally, the paper proposes a genetic algorithm approach that uses co-evolution to consider multiple criteria dynamically and constraint-satisfaction to narrow the search space, helping find optimal solutions to complex supply chain network design problems.
LINEAR REGRESSION MODEL FOR KNOWLEDGE DISCOVERY IN ENGINEERING MATERIALScscpconf
Nowadays numerous interestingness measures have been proposed to disclose the relationships
of attributes in engineering materials database. However, it is still not clear when a measure is
truly elective in large data sets. So there is a need for a logically simple, systematic and
scientific method or mathematical tool to guide designers in selecting proper materials while
designing the new materials. In this paper, linear regression model is being proposed for
measuring correlated data and predicating the continues attribute values from the large
materials database. This method helps to find the relationships between two sub properties of
mechanical property of different types of materials and helps to predict the properties of
unknown materials. The method presenting here effectively satisfies for engineering materials
database, and shows the knowledge discovery from large volume of materials database.
Studying on regression analysis suggests that data mining techniques can contribute to the
investigation on materials informatics, and for discovering the knowledge in the materials
database, which make the manufacturing industries to hoard the waste of sampling the newly
materials
SIMULATION-BASED OPTIMIZATION USING SIMULATED ANNEALING FOR OPTIMAL EQUIPMENT...Sudhendu Rai
The paper describes a software toolkit that enables the data-driven simulation-based optimization of print shops It enables quick modeling of complex print production environments under the cellular production framework. The software toolkit automates several steps of the modeling process by taking declarative inputs from the end-user and then automatically generating complex simulation models that are used to determine improved design and operating points. This paper describes the addition of another layer of automation consisting of simulation-based optimization using simulated-annealing that enables automated search of a large number of design alternatives in the presence of operational constraints to determine a cost-optimal solution. The results of the application of this approach to a real-world problem are also described.
This document provides an overview of quotes on quality management and lists several quality management tools including check sheets, control charts, Pareto charts, scatter plots, Ishikawa diagrams, and histograms. It also lists additional topics related to quality management such as quality management systems, courses, techniques, standards, policies, and strategies. The document contains information on defining and using several common quality management tools.
Similar to Data science in chemical manufacturing (20)
06-20-2024-AI Camp Meetup-Unstructured Data and Vector DatabasesTimothy Spann
Tech Talk: Unstructured Data and Vector Databases
Speaker: Tim Spann (Zilliz)
Abstract: In this session, I will discuss the unstructured data and the world of vector databases, we will see how they different from traditional databases. In which cases you need one and in which you probably don’t. I will also go over Similarity Search, where do you get vectors from and an example of a Vector Database Architecture. Wrapping up with an overview of Milvus.
Introduction
Unstructured data, vector databases, traditional databases, similarity search
Vectors
Where, What, How, Why Vectors? We’ll cover a Vector Database Architecture
Introducing Milvus
What drives Milvus' Emergence as the most widely adopted vector database
Hi Unstructured Data Friends!
I hope this video had all the unstructured data processing, AI and Vector Database demo you needed for now. If not, there’s a ton more linked below.
My source code is available here
https://github.com/tspannhw/
Let me know in the comments if you liked what you saw, how I can improve and what should I show next? Thanks, hope to see you soon at a Meetup in Princeton, Philadelphia, New York City or here in the Youtube Matrix.
Get Milvused!
https://milvus.io/
Read my Newsletter every week!
https://github.com/tspannhw/FLiPStackWeekly/blob/main/141-10June2024.md
For more cool Unstructured Data, AI and Vector Database videos check out the Milvus vector database videos here
https://www.youtube.com/@MilvusVectorDatabase/videos
Unstructured Data Meetups -
https://www.meetup.com/unstructured-data-meetup-new-york/
https://lu.ma/calendar/manage/cal-VNT79trvj0jS8S7
https://www.meetup.com/pro/unstructureddata/
https://zilliz.com/community/unstructured-data-meetup
https://zilliz.com/event
Twitter/X: https://x.com/milvusio https://x.com/paasdev
LinkedIn: https://www.linkedin.com/company/zilliz/ https://www.linkedin.com/in/timothyspann/
GitHub: https://github.com/milvus-io/milvus https://github.com/tspannhw
Invitation to join Discord: https://discord.com/invite/FjCMmaJng6
Blogs: https://milvusio.medium.com/ https://www.opensourcevectordb.cloud/ https://medium.com/@tspann
https://www.meetup.com/unstructured-data-meetup-new-york/events/301383476/?slug=unstructured-data-meetup-new-york&eventId=301383476
https://www.aicamp.ai/event/eventdetails/W2024062014
Discover the cutting-edge telemetry solution implemented for Alan Wake 2 by Remedy Entertainment in collaboration with AWS. This comprehensive presentation dives into our objectives, detailing how we utilized advanced analytics to drive gameplay improvements and player engagement.
Key highlights include:
Primary Goals: Implementing gameplay and technical telemetry to capture detailed player behavior and game performance data, fostering data-driven decision-making.
Tech Stack: Leveraging AWS services such as EKS for hosting, WAF for security, Karpenter for instance optimization, S3 for data storage, and OpenTelemetry Collector for data collection. EventBridge and Lambda were used for data compression, while Glue ETL and Athena facilitated data transformation and preparation.
Data Utilization: Transforming raw data into actionable insights with technologies like Glue ETL (PySpark scripts), Glue Crawler, and Athena, culminating in detailed visualizations with Tableau.
Achievements: Successfully managing 700 million to 1 billion events per month at a cost-effective rate, with significant savings compared to commercial solutions. This approach has enabled simplified scaling and substantial improvements in game design, reducing player churn through targeted adjustments.
Community Engagement: Enhanced ability to engage with player communities by leveraging precise data insights, despite having a small community management team.
This presentation is an invaluable resource for professionals in game development, data analytics, and cloud computing, offering insights into how telemetry and analytics can revolutionize player experience and game performance optimization.
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of May 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
Generative Classifiers: Classifying with Bayesian decision theory, Bayes’ rule, Naïve Bayes classifier.
Discriminative Classifiers: Logistic Regression, Decision Trees: Training and Visualizing a Decision Tree, Making Predictions, Estimating Class Probabilities, The CART Training Algorithm, Attribute selection measures- Gini impurity; Entropy, Regularization Hyperparameters, Regression Trees, Linear Support vector machines.
PyData London 2024: Mistakes were made (Dr. Rebecca Bilbro)Rebecca Bilbro
To honor ten years of PyData London, join Dr. Rebecca Bilbro as she takes us back in time to reflect on a little over ten years working as a data scientist. One of the many renegade PhDs who joined the fledgling field of data science of the 2010's, Rebecca will share lessons learned the hard way, often from watching data science projects go sideways and learning to fix broken things. Through the lens of these canon events, she'll identify some of the anti-patterns and red flags she's learned to steer around.