Stewart Anderson’s picture

By: Stewart Anderson

An excellent article by Donald Wheeler on the economic cost of quality, “What Is the Zone of Economic Production?” gave me pause to consider the strategic implications of reducing the costs associated with poor quality. As Wheeler pointed out in his article, there is an economic zone of production in which firms should strive to operate. His insights highlighted the key reason why firms should strive to improve quality and reduce the incidence of scrap and rework: Poor quality consumes resources and increases costs.

Although there can be no dispute about a firm reducing or eliminating the costs associated with poor quality, the question arises whether cost reduction per se can be used by a firm to create a competitive advantage. To answer this question, I draw the distinction between cost reduction and cost advantage.

Competitive advantage is obtained when a firm achieves the highest rates of profitability in its industry. It is industry structure that ultimately determines the profitability of a firm because the forces that shape industry structure are the chief determinants of profitability.

Bruce Hamilton’s picture

By: Bruce Hamilton

I was asked about 15 years ago to give a short presentation about poka-yoke to an association of engineering professors from different U.S. universities. I brought with me several devices that employees from my plant had developed, and I began to tell the story: The technique is not so difficult, but creating an environment in which employees are comfortable surfacing these opportunities is challenging. Poka-yoke, the invention of Shigeo Shingo, is one of my favorite tools because more than any other it taps employee creativity and problem-solving talent.

Steve Moore’s picture

By: Steve Moore

During the late 1990s, Marilyn vos Savant, holder of the Guinness Book of Records’ highest recorded IQ of 228, received an avalanche of hostile responses, many from Ph.D.s in math and statistics, when she correctly solved the controversial “Monty Hall Problem.” This concerns whether a contestant on Monty Hall’s game show, Let’s Make a Deal, who has chosen one of three doors, should or should not switch doors after Hall has revealed that one of the doors not chosen does not hide the car. Most people intuitively declare that there’s no advantage to switching because the chances are 50/50 between the two remaining doors.

However, in her “Ask Marilyn” column in Parade Magazine, vos Savant said that there is a two-thirds probability the car is behind the remaining door and a one-third probability the contestant is correct on his initial choice. The contestant should always switch.

Throughout the years, there have been many articles and even books written about the Monty Hall Problem. Most analyses include Bayes Theorem and other complex mathematical approaches. I learned a few years ago from Donald J. Wheeler that the simplest analysis that gives you insight is the best analysis. So I offer a simple analysis of the Monty Hall Problem as follows.

Bruce Hamilton’s picture

By: Bruce Hamilton

I was asked about 15 years ago to give a short presentation about poka-yoke to an association of engineering professors from different U.S. universities. I brought with me several devices that employees from my plant had developed, and I began to tell the story: The technique is not so difficult, but creating an environment in which employees are comfortable surfacing these opportunities is challenging. Poka-yoke, the invention of Shigeo Shingo, is one of my favorite tools because more than any other it taps employee creativity and problem-solving talent.

Steve Moore’s picture

By: Steve Moore

During the late 1990s, Marilyn vos Savant, holder of the Guinness Book of Records’ highest recorded IQ of 228, received an avalanche of hostile responses, many from Ph.D.s in math and statistics, when she correctly solved the controversial “Monty Hall Problem.” This concerns whether a contestant on Monty Hall’s game show, Let’s Make a Deal, who has chosen one of three doors, should or should not switch doors after Hall has revealed that one of the doors not chosen does not hide the car. Most people intuitively declare that there’s no advantage to switching because the chances are 50/50 between the two remaining doors.

However, in her “Ask Marilyn” column in Parade Magazine, vos Savant said that there is a two-thirds probability the car is behind the remaining door and a one-third probability the contestant is correct on his initial choice. The contestant should always switch.

Throughout the years, there have been many articles and even books written about the Monty Hall Problem. Most analyses include Bayes Theorem and other complex mathematical approaches. I learned a few years ago from Donald J. Wheeler that the simplest analysis that gives you insight is the best analysis. So I offer a simple analysis of the Monty Hall Problem as follows.

Davis Balestracci’s picture

By: Davis Balestracci

When teaching the I-chart, I’m barely done describing the technique (never mind teaching it) when, as if on cue, someone will ask, “When and how often should I recalculate my limits?” I’m at the point where this triggers an internal “fingernails on the blackboard” reaction. So, I smile and once again say, “It depends.” By the way…

… Wrong question!

I made a point in Part 1 of this article that I feel is so important, I’m going to make it again: Do not bog down in calculation minutiae. If you feel the instinct to ask that question, pause and think of how you would answer these from me instead:

1. Could you please show me the data (or describe an actual situation) that are making you ask me this question?

2. Please tell me why this situation is important.

3. Please show me a run chart of these data plotted over time.

4. What ultimate actions would you like to take with these data?

 

And since writing Part 1, I’ve thought of a fifth question I’d like to add:

5. What “big dot” in the board room are these data and chart going to affect? Or less tactfully,

Michelle LaBrosse’s picture

By: Michelle LaBrosse

Imagine you are sitting in your car, wondering, “What shall I do for dinner? Shall I pick up Chinese food to go, meet my friend Sally, or go home and cook dinner myself while watching American Idol?” All of a sudden you’re sitting there, frozen in time, unable to make a decision about what to do for dinner. And this is one of the easier choices in life.

Don’t be upset. Indecision can happen to anyone and often occurs when you least expect it. The pause that takes place when you are in the midst of making any important (or not so important) decision is like a comma in your life, separating one idea from the next, and one task from another. As anyone who has passed the third grade knows, the comma rule states: “When in doubt, leave it out.” This rule can be applied similarly to life’s frozen moments of indecision. When it doubt, leave that pause out.

Now, I’m not encouraging you to stop making decisions altogether. I’m talking about decisions that take an inordinately long time to process. Some of the reasons we succumb to prolonged indecision are the following.

American National Standards Institute ANSI’s picture

By: American National Standards Institute ANSI

(ANSI: Washington) -- The Internet as we know it is about to max out. Within the next 12 to 18 months, every one of the 4.3 billion internet protocol (IP) addresses will have been exhausted.

When the Internet was created more than 30 years ago, 4.3 billion unique addresses seemed more than enough. But what started as an “experiment” within the U.S. Department of Defense’s Advanced Research Projects Agency (DARPA) has morphed into the mega global communications network we know today.

Since 1981, Internet protocol version 4, or IP v. 4, has formed the backbone upon which the Internet is based. IP v. 4 uses 32-bit addresses to uniquely identify every computer, smart phone, or other device connected to the internet. The entities responsible for allocating IP address space are the Internet Corporation for Assigned Names and Numbers (ICANN) and the Internet Assigned Numbers Authority (IANA). IANA allocates IP addresses to five regional registries, which in turn distribute the addresses to Internet service providers. The last block of the remaining addresses was allocated to the registries earlier this month.

European Space Agency ESA’s picture

By: European Space Agency ESA

A key technical challenge of the joint European Space Agency (ESA) and National Aeronautics and Space Administration (NASA) LISA mission has been solved: how to maintain precise pointing of a laser beam across 5 million km of space (figure 1).

The next-decade Laser Interferometer Space Antenna (LISA) mission will look for ripples in space-time—their existence predicted by Albert Einstein—known as “gravitational waves.” To do this, a trio of identical spacecraft will fly 5 million km apart in an equilateral triangle formation, linked by laser beams (figure 2).


Figure 1: LISA satellite connected by laser


A precision-measuring method called interferometry can combine these laser beams to identify the slightest movement between free-floating metallic cubes within each spacecraft. Motion within a set frequency range will be scrutinized to search out gravitational waves emitted by massive black holes and similarly energetic cosmic objects.

Georgia Institute of Technology’s picture

By: Georgia Institute of Technology

The Georgia Tech Research Institute (GTRI) may possess the secret to baking perfect buns every time. Its researchers have developed a production-line system that automatically inspects the quality of sandwich buns exiting the oven and adjusts oven temperatures if it detects unacceptable buns.

"We have closed the loop between the quality inspection of buns and the oven controls to meet the specifications required by food service and fast-food customers," says GTRI senior research engineer Douglas Britton. "By creating a more accurate, uniform, and faster assessment process, we are able to minimize waste and lost product."

During existing inspection processes, workers remove a sample of buns each hour to inspect their color. Based on this assessment, they manually adjust the oven temperature if the buns appear too light or too dark. But with more than 1,000 buns leaving a bakery production line every minute, there is a great need for automated control to make more rapid corrections to produce buns of consistent color, size, shape, and seed coverage.

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