3. DIAGNOSTICO INTERNO Y EXTERNO DE FULL-SAFE
3.1. ANÁLISIS DE LA SITUACIÓN EXTERNA
3.3.6. ANÁLISIS DE LA DOFA
Total Quality Management
Quality Specification and Quality Costs Developing Quality Specifications Cost of Quality
ISO 9000 and ISO 14000 Six-Sigma Quality
Six-Sigma Methodology Analytical Tools for Six Sigma Statistical Quality Control
Variation Around Us Process Capability Process Control Procedures
Process Control with Attribute Measurements: Using p-Charts Process Control with Attribute Measurements: Using c-Charts Process Control with Variable Measurements: X-bar and R Charts How to Construct X-bar and R Charts
Acceptance Sampling
Design of a Single Sampling Plan for Attributes Operating Characteristics Curves
Case: Hang Kolb, Director of Quality Assurance
Overview
This chapter introduces concepts that are essential for every business student. It is good to point out that employers are seeking prospects that understand and can apply quality principles. The chapter emphasis is now on Six-Sigma due to the growing focus in many large companies. This chapter covers the Six-sigma methodology, the elements of quality management at a firm, and ISO 9000. The chapter covers the important subject of statistical quality control.
Teaching Tips
Many working students have had some recent training related to Six-Sigma programs. A good discussion topic relates to what they have learned in these programs and how the concepts are being applied at their company.
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An easy in-class acceptance sampling exercise can be run using some candy. You can tell the students that you just received this big bag of candy from your supplier, but you are concerned that it may be defective. Ask them to help you inspect it.
You can indicate that you do not want to do 100% inspection, since then there would not be any candy left to eat! First set up an acceptance sampling plan. You need to set up an AQL and LTPD so that the sample size is about 6 (you can have 6 people on each team doing the sampling). If you set LTPD to .2 and AQL to .01 you will find that the sample size is 6, and that the lot will be rejected if any defects are found. It is fun to put plenty of defects in the bag. You can do this by breaking or melting some of the pieces. Have each team get their sample and inspect their candy. Tell them that they cannot eat it until the lot is accepted. Poll each team to find out if they accept or reject their lot. Ask for the candy to be returned from each team that rejects their lot! This can lead into a quick discussion the dimensions of quality (see exhibit 6.8 from chapter 6). This is a fun exercise that will wake your students up with a shot of sugar.
Students seem to have a lot of trouble understanding what the capability index is.
The exercise with M&Ms included at the end of this section works very well demonstrating the concept.
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CASE: Hank Kolb - Director of Quality Assurance – Teaching Note
2. The greatest barrier facing Kolb is the lack of quality awareness at the company. Although Morganthol stresses the importance of quality, he sends the message that cost reduction and reduced delivery time are top priorities.
The first step should be to form a quality council headed by Morganthol and comprised of top management. The purpose of this council is to develop the quality mission and objectives for the company.
Kolb can immediately contribute to the council by providing in-depth training in quality practices. Top management must possess both commitment and knowledge in order to lead by example. Next, a limited number of quality improvement teams can be formed to address specific quality problems.
These teams might be cross-functional or from a single functional area. The composition of the team will depend on the nature of the problem. If the process being examined crosses functional boundaries, then the membership should include participants from all affected areas. As with the councils, the teams should receive thorough training before beginning their quality improvement efforts.
Morganthol should not describe the focus on quality as a program. Rather, the quality emphasis is a new way of managing the business. The new management process itself should be subject to periodic quality audits and improvement.
Extra Classroom Exercise
M&M’s – Process Capability for the Halloween Packs
This exercise is designed to demonstrate the concept of process capability. We use the M&M’s “Holiday Pack” and evaluate the capability of Mars to produce to the weight advertised on the package. Each holiday season (Christmas and Halloween), Mars produces what they call a “Holiday Pack” consisting of 18 mini-packs of M&Ms. On the front of the package, Mars advertises that there are 377.1 grams of M&Ms in each pack (if you look at other similar packs, Skittles for example, they advertise the same weight). In the exercise we evaluate the ability of Mars to produce to plus or minus one percent of this weight. We need to make a few assumptions in order to do the calculation, but this is fine. We find that the exercise is good in that students understand how tolerances can be dependent on one another and how scoping a project requires some assumptions to be made.
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This is an M&M mini pack. 18 of these are included in each holiday pack.
Begin the exercise by passing out the mini-packs of M&Ms. Ask the students to not open their package but to just think about how these must be made. Show the students how their mini-pack came from the “Holiday Pack” and show the 377.1 grams weight on the front of the package. Indicate that there are 18 mini-packs in each “Holiday Pack” and that you have looked at many of these and there are always 18 mini-packs in each package. Mars has great control of the part of the process that puts the mini-packs in the “Holiday Pack”. This keeps all the school teachers happy and ensures that they have enough mini-packs for each student in their class.
Ask your students to tell you how Mars makes the “Holiday Pack”. What does the process look like? How many major steps are in the process? How is the process buffered?
Work with the students to get a simple three-step process like the following on the board. The first step involves making the actual M&Ms. If you have the time you can go to the M&M website (m-ms.com) and see how this process works. Mars claims that they make about 400 million M&M each day! The second step is where the M&Ms are placed in the mini-packs. Finally, the mini-packs are placed in holiday packs.
Get the students to think about what the weight of the holiday packs is dependent on. Here they should see that it depends on the weight of each M&M, the number of
M&Ms 400M/day (P1)
Mini-Packs (P2)
Holiday Packs (P3)
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M&M in each mini-pack, and finally the number of mini-packs in each holiday pack.
You can indicate that you know that there are exactly 18 mini-packs in each holiday pack so there is no variability there. Also, indicate that the M&M production process (P1) is highly automated and there is very little variability in the weight of each M&M.
Indicate that you have done some research and know that M&Ms weight exactly .883605 grams each and that for the purpose of the exercise assume there is no variability. It is important that you use this much precision in the number to get the capability calculations to come out correctly.
You then need to get the students to realize that the only other source of variation is in how many M&Ms are actually in each mini-pack. If there were no variation in the number of M&Ms in each mini-pack, then there would be no variation in the process at all. Well since each student has a pack of M&Ms it is certainly possible to do an experiment to see if there is any variation in the number of M&Ms in each mini-pack.
Have the students open their package of M&Ms and count how many are there. You need a good sample of packages here of about 25 or 30 packages. You can tease the students about not eating any M&Ms since that would bias the sample results.
It’s interesting but you will find that there is indeed some variation in the number of M&Ms in each mini-pack. Data from a recent class indicated that the mean was 23.70968 M&Ms with a standard deviation of .937854. I have run this in a half dozen classes and these numbers are pretty consistent. Bring up a spreadsheet after the students have counted their M&Ms and enter the number of M&Ms in each sample and calculate the mean and standard deviation. You can joke about some students winning the lottery when they have 27 M&Ms and others being short changed with only 21. When doing your calculation, but sure to not round the numbers and use as much precision as the spreadsheet allows.
At this point ask the students to tell you how these numbers relate to the ability of Mars to hit the 377.1 gram weight on the front of the holiday pack. You should review the concept of process capability as part of this discussion. What you will need is for students to realize that Mars is going to need some type of tolerance on the 377.1 gram weight in order to measure the capability of the process.
For a tolerance, I have used plus or minus one percent of the advertised weight.
Assuming the process is centered at 377.1 grams the upper tolerance limit would be 380.871 grams and the lower tolerance limit 373.329 grams. As you will see, this works pretty well for the exercise. Now, the big leap that you need to make is that we need to convert these tolerances to a number of M&Ms in each holiday pack.
There are probably other ways to do the calculation, but the easiest is based on the number of M&Ms in the package.
Given our know weight of each M&M (.883605, this includes the weight of the packaging material), we can then state that the mean number of M&M in the holiday pack should be 426.7742 (377.1/.883605) with an upper tolerance limit of 431.0421 and lower tolerance limit of 422.5065 M&Ms.
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Next, we need to calculate the mean and standard deviation of the number of M&Ms in each holiday pack. Since there are exactly 18 mini-packs, the mean is simply 18 times the mean for each pack. Using the data for the class I cited above this is 18 x 23.70968 = 426.77424. This is right in the middle, but your actual data may be a little skewed right or left. Given that the standard deviation for each mini-pack is .937854 we know that the standard deviation for a sample of 18 mini-packs is .937854 x √18 = 3.979147. Finally, the Cpk is the MIN((upper tolerance – mean)/(3 x standard deviation), (mean – lower tolerance)/(3 x standard deviation)) which for our example is (431.0421 – 426.7782)/(3 x 3.979147) = .357. This corresponds to a z-score of 1.071 (3 x .357) with a probability of the package not meeting the weight tolerance of approximately 28 percent (2 x (1 – NORMSDIST(1.071)). Theoretically 28 out of 100 packages would not meet the weight tolerance.
At this point, you can go back and review what you did in the analysis. Be sure and go over the following main points:
The multi-step process for making the holiday packs.
Assumptions concerning the weight of the individual M&Ms and the number of mini-packs in each holiday pack.
The experiment that was conducted to determine the number of M&Ms in each mini-pack.
The calculation of the mean and standard deviation for the number of M&Ms and the standard deviation of the number of M&Ms in a holiday pack. Note the standard deviation calculation in particular. Consider the key assumption with this calculation (i.e. that the number of M&Ms in each mini-pack is not correlated to the number of M&Ms in each other mini-pack).
The calculation of the capability index.
As a follow up (homework) exercise, you can ask them to calculate the capability if the tolerances were based on plus or minus 2 percent instead of 1 percent.
This exercise can be done in about 45 minutes of class time.
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Chapter 7 - Projects
National Aeronautics and Space Administration’s Constellation Program What is Project Management?
CPM with Three Activity Time Estimates Time-Cost Models
Managing Resources Tracking Progress
Case: Cell Phone Design Project Overview
Project management skills are needed in today’s working environment. Workers find themselves increasingly involved in a variety of simultaneous projects. After discussing project management and how it differs from traditional management, in purpose, structure and operation, this chapter deals with the critical path method and project crashing.
You may not see this initially, but we are really trying to sneak some material about product design in this chapter. Given that we wanted this book to be short and
If you are interested in using Microsoft Project in class, take a look at the following hyperlink: http://www.microsoft.com/office/project/default.asp. A 120 day student version of Project is available free of change from Microsoft and information for ordering the disks are available here. One problem with the demo version is that after the 120 day trial period the program can no longer be used, nor can it be reinstalled on that computer without purchasing the full version from Microsoft. This can create some major problems if you intend to use Project in an elective course with your students. This is the reason that we elected not to include the trial version on the student CD.
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CASE: Cell Phone Design – Teaching Note Solution to the Cell Phone Design Project 1.
2. and 3.
Dependency Duration Early Start Late Start Early Finish Late Finish Slack
P1-Product Specs - 4 0 0 4 4 0
P2-Hardware Specs P1 5 4 8 9 13 4
P3-Software Specs P1 5 4 4 9 9 0
P4-Market Research P2,P3 2 9 15 11 17 6
S1-Supplier Hardware Specs P2 5 9 13 14 18 4
S2-Software Supplier Specs P3 6 9 9 15 15 0
S3-Market research P4 1 11 17 12 18 6
D1-Circuit Design S1,D7 3 23 23 26 26 0
D2-Battery Design S1 1 14 25 15 26 11
D3-Display Design S1 2 14 24 16 26 10
D4-Outer Cover Design S3 4 12 22 16 26 10
D5-User Interface Design S2 4 15 15 19 19 0
D6-Camera Design S1,S2,S3 1 15 18 16 19 3
D7-Functionality D5,D6 4 19 19 23 23 0
I1-Hardware Integration D1,D2,D3,D4,D6 3 26 26 29 29 0
I2-Software Integration D7 5 23 24 28 29 1
I3-Prototype Testing I1,I2 5 29 29 34 34 0
V1-Vendor Selection D7 10 23 24 33 34 1
V2-Contract Negotiation V1,I3 2 34 34 36 36 0
P1(4
4. It would be very desirable to change activity D1 (Circuit Design) so that it is not dependent on the completion of D7 (Functionality). In addition, if D7 could be changed so that it is dependent on S1, S2 and S3 this would help as well. If someway all of the “D” activities could be done simultaneously, this could shorten the project significantly.
The following spreadsheet shows the impact of changing D1 so that it is not dependent on D7.
Dependency Duration Early Start Late Start Early Finish Late Finish Slack
P1-Product Specs - 4 0 0 4 4 0
P2-Hardware Specs P1 5 4 8 9 13 4
P3-Software Specs P1 5 4 4 9 9 0
P4-Market Research P2,P3 2 9 15 11 17 6
S1-Supplier Hardware Specs P2 5 9 13 14 18 4
S2-Software Supplier Specs P3 6 9 9 15 15 0
S3-Market research P4 1 11 17 12 18 6
D1-Circuit Design S1 3 14 22 17 25 8
D2-Battery Design S1 1 14 24 15 25 10
D3-Display Design S1 2 14 23 16 25 9
D4-Outer Cover Design S3 4 12 21 16 25 9
D5-User Interface Design S2 4 15 15 19 19 0
D6-Camera Design S1,S2,S3 1 15 18 16 19 3
D7-Functionality D5,D6 4 19 19 23 23 0
I1-Hardware Integration D1,D2,D3,D4,D6 3 17 25 20 28 8
I2-Software Integration D7 5 23 23 28 28 0
I3-Prototype Testing I1,I2 5 28 28 33 33 0
V1-Vendor Selection D7 10 23 23 33 33 0
V2-Contract Negotiation V1,I3 2 33 33 35 35 0
Here the impact of making D7 dependent on S1, S2 and S3 rather than D5 and D6 is shown.
Dependency Duration Early Start Late Start Early Finish Late Finish Slack
P1-Product Specs - 4 0 0 4 4 0
P2-Hardware Specs P1 5 4 8 9 13 4
P3-Software Specs P1 5 4 4 9 9 0
P4-Market Research P2,P3 2 9 14 11 16 5
S1-Supplier Hardware Specs P2 5 9 13 14 18 4
S2-Software Supplier Specs P3 6 9 9 15 15 0
S3-Market research P4 1 11 16 12 17 5
D1-Circuit Design S1 3 14 18 17 21 4
D2-Battery Design S1 1 14 20 15 21 6
D3-Display Design S1 2 14 19 16 21 5
D4-Outer Cover Design S3 4 12 17 16 21 5
D5-User Interface Design S2 4 15 15 19 19 0
D6-Camera Design S1,S2,S3 1 15 20 16 21 5
D7-Functionality S1, S2, S3 4 15 15 19 19 0
I1-Hardware Integration D1,D2,D3,D4,D6 3 17 21 20 24 4
I2-Software Integration D5,D7 5 19 19 24 24 0
I3-Prototype Testing I1,I2 5 24 24 29 29 0
V1-Vendor Selection D7 10 19 19 29 29 0
V2-Contract Negotiation V1,I3 2 29 29 31 31 0
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Chapter 8 – Global Sourcing and Procurement