organizes a large number of ideas into their natural relationships, shows cause-and-effect relationships and helps you analyze the natural links between different aspects of a complex situation.
Seven Quality management & control toolsPMC Mentor
Some insights into 7 quality management tools as stated in PMBOK quality management knowledge area.
Learn to practice the 7 Quality management & control tools with real examples.
Assists in the solving of common business problems by using a step-by-step methodology for problem identification, analysis, planning of corrective actions to solve a problem and preventive actions to address risks. More http://www.conceptdraw.com/solution-park/seven-management-and-planning-tools
Seven Quality management & control toolsPMC Mentor
Some insights into 7 quality management tools as stated in PMBOK quality management knowledge area.
Learn to practice the 7 Quality management & control tools with real examples.
Assists in the solving of common business problems by using a step-by-step methodology for problem identification, analysis, planning of corrective actions to solve a problem and preventive actions to address risks. More http://www.conceptdraw.com/solution-park/seven-management-and-planning-tools
QUALITY MANAGEMENT- SEVEN BASIC TOOLS OF QUALITY CONTROLHelanJenifer
QUALITY MANAGEMENT- SEVEN BASIC TOOLS OF QUALITY CONTROL
This helps to know about the basic tools to be used by a HR professional from a social work background to quality control easily
Explanation of the seven basic tools used to solve a variety of quality-related issues. They are suitable for people with little formal training in statistics.
QUALITY MANAGEMENT- SEVEN BASIC TOOLS OF QUALITY CONTROLHelanJenifer
QUALITY MANAGEMENT- SEVEN BASIC TOOLS OF QUALITY CONTROL
This helps to know about the basic tools to be used by a HR professional from a social work background to quality control easily
Explanation of the seven basic tools used to solve a variety of quality-related issues. They are suitable for people with little formal training in statistics.
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
The seven basic quality tools are effective for data analysis, process control, and quality improvement (numerical data). However, these basic tools cannot be used for non-numerical or verbal data. To organize verbal data into useful information, you would require the advanced quality tools.
The Seven Advanced Tools of Quality (a.k.a Seven New Tools or Seven Management & Planning Tools) were developed with a design approach to organize verbal data diagramatically. These tools work in conjunction with the basic quality tools and can be used by management and staff to develop ideas, solve problems and formulate plans for improved project management.
The Seven Advanced Tools are:
1) Affinity Diagram: Organizes a large number of ideas into their natural relationships.
2) Relations Diagram: Shows cause-and-effect relationships and helps analyze the natural links between different aspects of a complex situation.
3) Tree Diagram: Breaks down broad categories into finer and finer levels of detail, helping to move step-by-step thinking from generalities to specifics.
4) Matrix Diagram: Shows the relationship between two, three, or four groups of information and can give information about the relationship, such as its strength, the roles played by various individuals, or measurements.
5) Matrix Data Analysis Chart: A complex mathematical technique for analyzing matrices, often replaced by the similar prioritization matrix. A prioritization matrix is an L-shaped matrix that uses pairwise comparisons of a list of options to a set of criteria in order to choose the best option(s).
6) Arrow Diagram: Shows the required order of tasks in a project or process, the best schedule for the entire project, and potential scheduling and resource problems and their solutions.
7) Process Decision Program Chart: Systematically identifies what might go wrong in a plan under development.
LEARNING OBJECTIVES
1. Acquire knowledge on the seven advanced quality tools for project planning and management.
2. Learn how to apply the seven management and planning tools to problem solving, projects, communication and daily management work.
CONTENTS
1. PDCA Problem Solving
2. Affinity Diagram (KJ Method)
3. Relations Diagram (Interrelationship Diagram)
4. Tree Diagram
5. Matrix Diagram
6. Matrix Data Analysis Chart
7. Arrow Diagram
8. Process Decision Program Chart (PDPC)
Reflective Journal 9 Benefits and Dangers of Social NetworksW.docxcarlt3
Reflective Journal 9: Benefits and Dangers of Social Networks
Write a 3/4 to 1 page journal entry (300 to 500 words) in which you:
1. Discuss two or three (2-3) benefits you or others have experienced with social networks.
2. Discuss one or two (1-2) dangers you or others have experienced with social networks.
3. Complete the page requirement.
4. Write with clarity, following mechanics and formatting requirements.
The specific course learning outcome(s) associated with this assignment are:
· Apply critical thinking skills to the analysis of issues involving mass media and society.
· Analyze ways in which different types of media content reflect and / or influence society’s attitudes and behaviors.
· Analyze various issues affecting the media business.
· Evaluate the effects of new forms of media (e.g., online services) on social interactions.
· Write clearly and concisely about media and society using proper writing mechanics.
Grading for this assignment will be based on answer quality, and language and writing skills, using the following rubric.
Click here to view the grading rubric.
Data Analysis and Reporting
Chapter 15
Data ManagementIncludes coding, cleaning, and organizing data into a usable format (preparing for analysis)
Coding – assigning labels so data can be read and understood by a computer (e.g., 1=yes, 2=no)
Cleaning – values are valid and consistent (e.g., 1=true, 2=false, there should be no 3s); Also, need to deal with missing data
Data AnalysisBegins with being able to identify the variables
Variables – a characteristic or attribute that can be measured or observed (Creswell, 2002)
Types of variables: independent (controlled or cause or exert some influence) and dependent (are outcome variables that are being studied)
Also, the level(s) of data collected are importantNominal OrdinalNumerical (interval and ratio)
Data Analysis (cont.)Descriptive statistics – used to organize, summarize and describe characteristics
Inferential statistics – concerned with relationships and causality to make generalizations about a population based on a sample
AnalysesUnivariate (1 variable) Bivariate (2 variables)Multivariate (More than 2 variables)
Examples of Evaluation Questions Answered
Univariate Data AnalysesOne variable at a time
Summary counts (frequency distributions)
Measures of central tendency – e.g., mean, median, and mode
Measures of spread or variation – e.g., range, standard deviation, variance
Bivariate AnalysesCan be non-statistical comparisonsExample of non-statistical comparisons (eyeballing the data)
Male Female
Yes 35 62
No 50 46
Bivariate Analyses (cont.)HypothesesNull: statement of no significant difference Type I error – rejecting the null hypothesis when it is trueType II error – failing to reject the null hypothesis when it is not true (accepting a false null hypothesis)Level of significance (alpha level) – probability of making a type I error; e.g., p<.01A.
BA is used to gain insights that inform business decisions and can be used to automate and optimize business processes. Data-driven companies treat their data as a corporate asset and leverage it for a competitive advantage. Successful business analytics depends on data quality, skilled analysts who understand the technologies and the business, and an organizational commitment to data-driven decision-making.
Business analytics examples
Business analytics techniques break down into two main areas. The first is basic business intelligence. This involves examining historical data to get a sense of how a business department, team or staff member performed over a particular time. This is a mature practice that most enterprises are fairly accomplished at using.
DAT 520 Final Project Guidelines and Rubric Overview .docxsimonithomas47935
DAT 520 Final Project Guidelines and Rubric
Overview
You must complete a decision analysis research project as your final project for this course. Your research project will focus on a real-world topic of your choice,
as approved by your instructor. You will pick a topic from the list provided or with approval from your instructor, and create a data analysis plan and decision
tree model based on a real-world scenario. This assessment will provide you with the opportunity to employ highly valued decision support skills and concepts
for data within a real-world context. You can use the Final Project Notes document, found in the Assignment Guidelines and Rubrics section of the course.
The project is divided into three milestones, which will be submitted at various points throughout the course to scaffold learning and ensure quality final
submissions. These milestones will be submitted in Modules Two, Five, and Seven. The final submission will occur in Module Nine.
This project will address the following course outcomes:
Appraise data in context according to industry-standard methods and techniques for its utility in supporting decision making
Determine suitable data manipulation and modeling methods for decision support
Articulate data frameworks for organizational decision support by applying data manipulation, modeling, and management concepts
Evaluate the ethical issues surrounding organizational use of decision-oriented data based on industry standards and one’s personal ethical criteria
Create and assess the agility of solutions through application of data-mining procedures for decision support in various industries
Prompt
Your decision analysis model and report should answer the following prompt: How does your model and evaluation resolve uncertainty in making a decision? In
order to produce your analytic report, you will need to choose and investigate a data set using the decision analysis techniques you learned in class. Then you
will formulate a research question, write an analytic plan, and implement it. Your report should not solely consist of descriptions of what you did. It should also
contain detailed explorations into the meaning behind your model and the implications of its results. You will also be testing your model’s fitness and evaluating
its strengths and weaknesses.
The project in a nutshell:
1. Choose a data set (get ideas from the source list in the spreadsheet Final Project Topics and Sources.xls)
2. Formulate your decision analysis research question
3. Write an analytic plan
4. Perform the top-down or bottom-up modeling
5. Perform model diagnostics
6. Evaluate
These activities are broken up into milestones so that the work is spread throughout the term and you can get early assistance with any obstacles.
A decision analysis report is similar to any other analytic report. These reports introduce a problem, state a line of inquiry, explain a model th.
The seven traditional tools of quality – New management tools – Six-sigma: Concepts, methodology, applications
to manufacturing, service sector including IT – Bench marking– Reason to bench mark, Bench marking process –
FMEA – Stages, Types
Quality control is a process that is used to ensure a certain level of quality in a product or service. It might include whatever actions a business deems necessary to provide for the control and verification of certain characteristics of a product or service. Most often, it involves thoroughly examining and testing the quality of products or the results of services. The basic goal of this process is to ensure that the products or services that are provided meet specific requirements and characteristics, such as being dependable, satisfactory, safe and fiscally sound.
Check sheet
Control chart
Histogram
Ishikawa Diagram
Pareto Chart
Scatter diagram
Flow chart
The boiler system comprises a feed-water system, steam system, and fuel system. The feed-water system supplies treated water to the boiler and regulate it automatically to meet the steam demand. Various valves and controls are provided to access for maintenance and monitoring.
the water that reaches the surface is not hot enough to produce steam, it can still be used to produce electricity by feeding it into a Binary Power Plant. The hot water is fed into a heat exchanger. The heat from the water is absorbed by a liquid such as isopentane which boils at a lower temperature. The isopentane steam is used to drive turbines, producing electricity. The isopentane then condenses back to its liquid state and is used again.
In Thermal Power Plant’s coal is generally used as fuel and hence the ash is produced as the byproduct of Combustion. Ash generated in power plant is about 30-40% of total coal consumption and hence the system is required to handle Ash for its proper utilization or disposal.
roducing quality work (the first time) means quality is built into the processes for producing products or providing services, and continual improvement measures are taken to ensure the processes work every time. Employees are empowered to make decisions to improve a process and are provided with continual training to develop their skills.
Failure modes and effects analysis also documents current knowledge and actions about the risks of failures, for use in continuous improvement. FMEA is used during design to prevent failures. Later it’s used for control, before and during ongoing operation of the process. Ideally, FMEA begins during the earliest conceptual stages of design and continues throughout the life of the product or service.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
3. The Seven New Quality Tools
■ Affinity Diagrams
■ Interrelationship Diagrams
■ Tree Diagrams
■ Matrix Diagrams
■ Matrix Data Analysis
■ Process Decision Program Charts
■ Arrow Diagrams
4. Relations to “Old” Tools
■ Similarities:
– Both are graphics rather than language based
■ Whole first, then elements analyzed
■ Universal understanding (pictures)
■ Differences:
– New tools are more relational and network oriented
– New tools may take more practice to develop proficiency
■ They can and should be used together
5. Affinity Diagrams
■ Organizes a large amount of verbal data related to
a broad problem or subject
– Ideas, opinions, facts
■ Usage example: Establishing a new QC policy
■ Steps:
– Gather a large number of ideas
– Put individual ideas on cards or sticky notes
– As a team, group the ideas according to natural
“affinity” or relationship to each other
– These natural groups become “strategic factors”
6. Affinity Diagram Example
Your team has been brainstorming to develop a list
of ideas to incorporate into the vision. They have
come up with the following list. Develop an affinity
diagram and name each strategic factor.
•Low product maintenance
•Satisfied employees
•Courteous order entry
•Low prices
•Quick delivery
•Growth in shareholder value
•Teamwork
•Responsive technical support
•Personal employee growth
•Low production costs
•Innovative product features
•High return on investment
•Constant technology
innovation
•High quality
•Motivated employees
•Unique products
•Small, lightweight designs
8. Interrelationship Diagrams
■ Identifies and explores causal relationships among related
concepts or ideas. Can address problems with a complex
network of causes and effects.
– Identifies key drivers and bottlenecks
■ Usage examples: design steps to counter market
complaints, or reform administrative departments
■ Steps:
– Write each concept or idea on a piece of paper in a circular
pattern (allow room between concepts)
– Number them to make comparison process easier to track
– Use pairwise comparisons (1-2, 1-3, 1-4…2-3, 2,4…3,4)
■ If there is a relationship draw arrow to effect
■ If there is no relationship leave blank
■ The can be no 2-way relationships
9. Interrelationship Diagrams Cont.
■ Steps (Cont.)
– Analyze the diagram
■ Count the arrows (# out - # in)
– Highest out are primary drivers
■ Resources here can produce pronounced change
– Lowest are key bottlenecks
■ Affected by many other options
■ May be inhibiting other options from proceeding as
required
■ Highlight primary drivers and key bottlenecks
■ Note: examine only cause and effect
relationships. Likely will have arrows on only 50%
of relationships.
10. Interrelationship Diagram Example
■ Use the strategic factors derived from your affinity
diagram to develop an interrelationship diagram.
If you were unsuccessful in developing your own
strategic factors use the following:
– Customer Value
– Work Environment
– Customer Service
– ROI
– Technology
– Product Innovation
12. Tree Diagrams
■ Expands a purpose into the tasks required to accomplish it.
■ Usage examples: deploy a quality plan, or develop objectives, policies
and implementation steps.
13. Tree Diagrams (cont.)
■ Steps:
– Work from left to right
– Start with the purpose to be accomplished
– Generate the high level targets or goals that must be completed
to accomplish the purpose
– Link each goal to the purpose (these are the first branches of the
tree)
– Expand on each target to identify and define subordinate tasks to
accomplish each target
– Link each to their target
– Continue expansion process until final level is implementable.
– Review logic of completed tree (perhaps with larger group)
14. Tree Diagram Example
■ Refer to the key strategic factors (primary driver or key
bottleneck) identified from your interrelationship diagram
– this will be your purpose. Refer to ideas associated with
that factor on your affinity diagram – these will be your
primary target or goals. Develop a tree diagram including
this information, and expand it into several next level
strategies to meet these targets.
■ If you are unable to gather the required information, use
“Customer Service” as your purpose, and “improving the
order entry process”, “reducing delivery time” and
“improving technical support” as your primary goals.
16. Matrix Diagrams
■ S.M.A.R.T. Plan Matrices
– Technique for structuring the task details when planning the
implementation of a project.
– May use the final output of a tree diagram
– For each implementable task:
■ Specific (activity or task)
■ Measurable (outcome or process)
■ Assignment (who will perform)
■ Resources (what is needed)
■ Time (anticipated duration)
■ Predecessors (what must must be done first)
– Consensus should be reached among all parties on the SMART
matrix
■ Correlation Matrices
– Shows the relationship between one list of variables and another.
Relationships are usually based on experience.
– Such a matrix forms the body of a “house of quality”
18. Matrix Diagram S.M.A.R.T. Plan Example
Specific Measurable Assignment Resources Time
(Weeks)
Predecessors
A Evaluate
Needs
Deliverable Steve 8 hours 1 -
B Schedule
Training
Deliverable Doug 4 hours 1 -
C Evaluate
Software
Deliverable Morgan 10 hrs,
copies of
software
2 A
D Training
Materials
Deliverable Doug 20 hrs,
software
manuals
3 C
E Purchase Deliverable Ted 2 hours 2 C
F Install # systems Ted 50 hours 2 E
G Train
Users
# trained Doug 20 hours 1 B, D, F
19. Matrix Data Analysis
■ Arranges a large array of numbers so that they may
be visualized and comprehended easily
■ Usage example: evaluate the desired quality level
from the results of a market survey
■ Steps:
– Begin with numerical matrix relating goals or
requirements to actions or performance
– Assign weights to each goal or requirement
■ Subjective
■ Objective (principle component analysis)
– Calculate weighted importance of actions or
performance level
20. Matrix Data Analysis Example
Requirement Importance
Weight
Best
Competitor
Evaluation
Own
Evaluation
Weighted
Gap
Price .2 6 7
Speed of
Delivery
.3 7 6
Reliability .4 5 6
Customizability .1 8 7
21. Process Decision Program Charts
■ Maps out all contingencies when moving from
statement of purpose to its realization
■ Usage example: establishing an implementation
plan for improvement project
■ Steps:
– Another form of a tree diagram
– First level: purpose
– Second level: activities to be undertaken
– Third level: steps in these activities
– Fourth level: what ifs? (contingencies)
– Fifth level: countermeasures (contingency plans)
22. Process Decision Program Chart Example
■ Choose one of the strategies that you came up with in your tree diagram. Expand
on the actions necessary to implement this strategy. Select one action and expand
on the necessary steps. Continue expanding along a single branch until you can
develop at least one contingency and possible countermeasure.
23. Arrow Diagrams
■ Also utilized by PERT and CPM, establishes the most
suitable daily plan. It is a network of lines that connects
all of the elements related to plan execution.
■ Steps: (working on the nodes)
– All of your activities that have no predecessors can be placed
along the left of the page
– Activities that immediately follow are drawn to the right of the
first activities
– Arrows are drawn from each activity to all those activities that
immediately follow that activity
– Continue adding activities until the process is finished
– Time estimates can be easily added to schedule and control the
project