Scene 1

By: Palacio, Jhon Henry   Reyes,  Alizza  Ann         Rodriguez,  Daisserry         Sumiwan ,  Merribeth

Scene 2

Scene 3

Scene 4

Scene 5

Fishbone Diagrams (also known as Ishikawa Diagrams and The Cause-and-Effect Diagram) is used to answer the following questions in problem solving: What are the possible root causes of a problem? What are the things complicating the process? In 1943, at the University of Tokyo, Dr. Kaoru Ishikawa created the "Fishbone Diagram” The diagram looks just like a fish’s skeleton with the problem at its head and the causes for the problem feeding into the spine. Once all the causes that underlie the problem have been identified, managers can start looking for solutions to ensure that the problem doesn’t become a recurring one. It can also be used in product development. Having a problem-solving product will ensure that your new development will be popular – provided people care about the problem you’re trying to solve. The fishbone diagram strives to pinpoint everything that’s wrong with current market offerings so that you can develop an innovation that doesn’t have these problems. Finally, the fishbone diagram is also a great way to look for and prevent quality problems before they ever arise. Use it to troubleshoot before there is trouble, and you can overcome all or most of your teething troubles when introducing something new.

Scene 6

Scene 7

Scene 8

The Pareto chart analysis is a statistical graphical technique used to map and rank business process problems starting from the most frequent to the least frequent with the ultimate goal of focusing efforts on the factors that produce the greatest impact overall. To do this effectively, it utilizes the Pareto Principle, which is most predominantly known as the 80/20 rule. The Pareto chart is sometimes also referred to as the Pareto analysis or Pareto diagram. The Pareto chart is derived from the Pareto principle, which was suggested by a Romanian-born American management consultant, Joseph  Juran , during WWII. The name of principle, however, is derived from the Italian economist Vilfredo Pareto.

Scene 9

Scene 10

Scene 11

Scene 12

What is a  check sheet  in Total Quality Management? A  check sheet  is a structured, prepared form for collecting and analyzing data. This is a generic data collection and analysis tool that can be adapted for a wide variety of purposes and is considered one of the seven basic quality tools.

Scene 13

Telephone Interruptions
Day
Reason
Info request
12
Tues
6
Wed
10
Thurs
8
Fri
Hll
13
Total
20
10
19
49

Scene 14

What is the importance of  check sheet  in Quality Management?

Check sheets  help to systematically collect and organize data and is useful in the all phases of the Lean Six Sigma DMAIC (define, measure, analyze, improve and  control ) framework.

Scene 15

Classification check sheet : A trait such as a defect must be classified into a category.

Morday
Wrong
orders
Reworked
orders
Late ut///
deliveries
Shipping
damage
payrnents
Totals
11
Tuesday
8
WftWtt//
27
Thursday
6
Friday
2
Saturday
28
Sunday
19

Scene 16

2.   Defect location check sheet : The physical location of a trait is indicated on a picture, or illustration of a part or item being evaluated.

Scene 17

3.   Frequency check sheet:  The presence or absence of a trait or combination of traits is indicated .

Reason
Label mismatch
Label missing
Incorrect label
Wrong color
Damaged label
Other
Frequency
Comments
Blue

Scene 18

4.   Measurement scale check sheet : A measurement scale is divided into intervals and measurements are indicated by checking an appropriate interval.

Scene 19

5.  Check List : The items to be performed for a task are listed so that as each is accomplished it can be marked as having been completed.

Scene 20

Scene 21

A  histogram  is a graphical display of data using bars of different heights. In a  histogram , each bar groups numbers into ranges. Taller bars show that more data falls in that range. A  histogram  displays the shape and spread of continuous sample data. Example of a Histogram Chart:

Scene 22

A  histogram  is the most used graph to show frequency distributions. It looks very much like a bar chart, but there are important differences between them. This helpful data collection and analysis tool is considered one of the seven basic quality tools.

Scene 23

What is the difference between a  Bar Graph  and  Histogram ?

Histogram vs. Bar Chart
No gaps
gaps
2 4 6 8 10 12 14 16 18 20 22 24 2
e— Number Ranges —-9
Histogram
Jan
Feb
Mar
Apr
May
Bar Chart

Scene 24

Histograms  are used to show distributions of variables while  bar  charts are used to  compare  variables.  Histograms  plot quantitative data with ranges of the data grouped into bins or intervals while  bar  charts plot categorical data. ... Note that it does not make sense to rearrange the  bars  of a  histogram.

Scene 25

Scene 26

Scene 27

WHO INVENTED CONTROL CHART? Invented by  Walter A. Shewhart  while he was working for Bell Labs in the ’20s, control charts have been used in a variety of industries as part of a process improvement methodology. Shewhart understood that, no matter how well a process was designed, there will always be variation within that process—and the effect can become negative if the variation keeps you from meeting deadlines or quotas.

Scene 28

What is control chart A control chart—sometimes called a Shewhart chart, a statistical process control chart, or an SPC chart—is one of several graphical tools typically used in quality control analysis to understand how a process changes over time.

Scene 29

The main elements of a control chart include: •	A visual time series graph that illustrates data points collected at specific time intervals. •	A horizontal control line to more easily visualize variations and trends. •	Horizontal lines, representing upper and lower control limits, placed at equal distances above and below the control line. These upper and lower limits are calculated from the data that is recorded on the time series graph over a specified period of time.

Scene 30

Benefits •	Understand the variations that are always present in processes. Variations within your control limits indicate that the process is working. Variations that spike outside of your control limits indicate problems that need to be corrected.   •	See when something is going wrong or may go wrong. These problem indicators let you know that corrective action needs to be taken. •	Notice patterns within plotted points. The patterns indicate possible causes, which can help you find possible solutions. •	Predict future performance. •	Generate new ideas for improving quality based on your analysis.

Scene 31

2 Types Of Variation Common cause variations Common cause variations are predictable and always present in your processes.  As a simple example, consider how long it takes you to commute to work every morning. You may drive the same route every morning, but the drive is never the same. Perhaps it takes you an average of 20 minutes from the time you leave your house until you pull into the parking lot. Due to common cause variations—such as stop lights and traffic congestion—some days it will take less time and other days it will take more time.  Even though you don’t know exactly when you will get to work tomorrow, you know that it will fall within an acceptable time frame and you will arrive on time. When variations stay within your upper and lower limits, there is no urgent need to change your process because everything is working within predictable parameters .

Scene 32

Special cause variations Special cause variations are usually sporadic and unpredictable. For example, running out of gas, engine failure, or a flat tire could extend your commute by an hour or more, but these types of special causes will not happen every day. When special cause variations occur, it’s still a good idea to analyze what went wrong to see if these anomalies can be prevented in the future. In our commuting example, you could make sure you stop at a gas station when you’re running low on gas and make sure your vehicle is well maintained to ensure proper operation.

Scene 33

How to make a control chart Control charts are a great way to separate common cause variations from special cause variations. With a control chart, you can monitor a process variable over time.

Scene 34

Follow these steps to get started: Decide on a time period, typically noted on the X-axis of the control chart, to collect the necessary data and establish your control limits. Collect your data and plot it on the control chart. Calculate the average of your data and add a control line. Calculate upper and lower control limits and add these lines in your chart, ideally in a different color or style. Note any “out-of-control signals,” or places where your data falls outside of your control limits. Investigate the cause and adjust your process to minimize risk of these abnormalities. With your control limits in mind, continue to track your process.

Scene 35

Scene 36

Scatter Diagrams  are used to visualize how a change in one variable affects another. A Scatter Diagram displays the data as a set of points in a coordinate system. It combines these values into single data points and displays them in uneven intervals. A Scatter Diagram can be very useful for identifying relationships between variables, for example, the relationship between price and quality rating. Making a Scatter Diagram involves many different elements that can be managed using Concept Draw Scatter Diagram solution. Scatter Diagram  involves many different elements that can be managed using Concept Draw Scatter Diagram solution.

Scene 37

Scatter Diagrams  are used to show the “cause-and-effect” relationship between two kinds of data, and to provide more useful information about a production process. •	When you have paired numerical data •	When your dependent variable may have multiple values for each value of your independent variable •	When trying to determine whether the two variables are related, such as: When trying to identify potential root causes of problems 	After brainstorming causes and effects using a fishbone diagram to determine objectively whether a particular cause and effect are related When determining whether two effects that appear to be related both occur with the same cause When testing for autocorrelation before constructing a control chart

Scene 38

Scene 39

Scene 40

WHAT IS A FLOWCHART?  A flowchart is a diagram that depicts a process, system or computer algorithm. They are widely used in multiple fields to document, study, plan, improve and communicate often complex processes in clear, easy-to-understand diagrams. Flowcharts are sometimes called by more specialized names such as Process Flowchart, Process Map, Functional Flowchart, Business Process Mapping, Business Process Modeling and Notation (BPMN),  or Process Flow Diagram (PFD).

Scene 41

To develop understanding of how a process is done. To study a process for improvement. To communicate to others how a process is done. When better communication is needed between people involved with the same process. To document a process. When planning a project.

Scene 42

Scene 43

Scene 44

PERT ( Programme  Evaluation and Review Technique) CPM (Cost Per Mille)

Scene 45

A PERT chart is a network diagram used in the Program Evaluation Review Technique (PERT) to represent a project’s timeline. It allows project managers to estimate the duration of projects based on the analysis of task sequences.

Scene 46

As stated, the use of the PERT chart gives project managers a tool to estimate the time and resources needed to complete their project tasks, which is crucial during the initiation and planning phases. When it comes to starting a project, the early steps involve taking all those tasks you collected that lead to your final deliverable and organizing them in a schedule. Knowing the amount of time it’ll take to complete each task, especially the riskier ones, is fundamental for project managers.

Scene 47

How to Make a PERT Chart Use a PERT chart in the planning phase of your project. Begin by identifying the project milestones and then break those down into individual tasks. Figure out the sequence of the tasks and their dependencies. Make the PERT diagram. Do an estimate for each task and the time it will take to complete it. Calculate the critical path and identify any possible slack. You have your PERT chart! Remember, the PERT chart is a living document that must be returned to and revised as needed as the project progresses.

Scene 48

A PERT chart relies on the weighted average of three numbers that are based on the most pessimistic (P), the most optimistic (O) and the most likely (M) estimates for the project’s length. Optimistic Time: The least amount of time to accomplish a task or activity.. Pessimistic Time: The maximum amount of time to accomplish a task or activity. This is the worst-case scenario, anything that can go wrong does. Most Likely Time: The best estimate of how long it will take to accomplish the task or activity, assuming there are no problems. Expected Time: The best estimate of how long it will take to accomplish the task or activity, assuming there will be problems. This would be the more realistic duration.

TQM AND PLANNING TOOLS

Page 1 (0s)

Page 2 (3s)

Page 3 (10s)

Page 4 (14s)

Page 5 (18s)

Page 6 (1m 20s)

Page 7 (1m 23s)

Page 8 (1m 26s)

Page 9 (2m 5s)

Page 10 (5m 46s)

Page 11 (6m 2s)

Page 12 (6m 6s)

Page 13 (6m 32s)

Page 14 (6m 44s)

Page 15 (7m 4s)

Page 16 (7m 17s)

Page 17 (7m 30s)

Page 18 (7m 39s)

Page 19 (7m 53s)

Page 20 (8m 7s)

Page 21 (8m 10s)

Page 22 (8m 42s)

Page 23 (9m 5s)

Page 24 (9m 36s)

Page 25 (9m 39s)

Page 26 (9m 52s)

Page 27 (9m 55s)

Page 28 (10m 18s)

Page 29 (10m 40s)

Page 30 (11m 13s)

Page 31 (12m 4s)

Page 32 (13m 17s)

Page 33 (14m 16s)

Page 34 (14m 49s)

Page 35 (15m 42s)

Page 36 (15m 48s)

Page 37 (16m 46s)

Page 38 (17m 53s)

Page 39 (18m 11s)

Page 40 (18m 17s)

Page 41 (18m 42s)

Page 42 (20m 24s)

Page 43 (25m 16s)

Page 44 (26m 33s)

Page 45 (26m 43s)

Page 46 (27m 40s)

Page 47 (30m 9s)

Page 48 (31m 57s)

Page 49 (34m 44s)

Page 50 (34m 54s)