14-08-2012, 02:16 PM
QUALITY AND PRODUCTIVITY
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INTRODUCTION
Taguchi methods are statistical methods developed by Genichi Taguchi to improve the quality of manufactured goods, and more recently also applied to, engineering, biotechnology, marketing and advertising.
The concept of quality should be clear for better understanding the Taguchi method.
QUALITY AND PRODUCTIVITY
QUALITY:-
Quality in business, engineering and manufacturing has a pragmatic interpretation as the non-inferiority or superiority of something. Quality is a perceptual, conditional and somewhat subjective attribute and may be understood differently by different people. Consumers may focus on the specification quality of a product/service, or how it compares to competitors in the marketplace. Producers might measure the conformance quality, or degree to which the product/service was produced correctly.
DEFINATIONS
The common element of the business definitions is that the quality of a product or service refers to the perception of the degree to which the product or service meets the customer's expectations. Quality has no specific meaning unless related to a specific function and/or object. Quality is a perceptual, conditional and somewhat subjective attribute.
The business meanings of quality have developed over time. Various interpretations are given below:
1. ISO 9000: "Degree to which a set of inherent characteristics fulfills requirements." The standard defines requirement as need or expectation.
2. Six Sigma: "Number of defects per million opportunities."
3. SUBIR CHOWDHURY: "Quality combines people power and process power."
4. PHILIP B. CROSBY: "Conformance to requirements." The requirements may not fully represent customer expectations; Crosby treats this as a separate problem.
5. JOSEPH M. JURAN: "Fitness for use." Fitness is defined by the customer.
6. NORIAKI KANO and others, present a two-dimensional model of quality: "must-be quality" and "attractive quality." The former is near to "fitness for use" and the latter is what the customer would love, but has not yet thought about. Supporters characterize this model more succinctly as: "Products and services that meet or exceed customers' expectations."
7. ROBERT PIRSIG: "The result of care."
8. GENICHI TAGUCHI, with two definitions:
a. "Uniformity around a target value." The idea is to lower the standard deviation in outcomes, and to keep the range of outcomes to a certain number of standard deviations, with rare exceptions.
b. "The loss a product imposes on society after it is shipped." This definition of quality is based on a more comprehensive view of the production system.
9. AMERICAN SOCIETY FOR QUALITY: "A subjective term for which each person has his or her own definition. In technical usage, quality can have two meanings:
a. The characteristics of a product or service that bear on its ability to satisfy
b. A product or service free of deficiencies."
10. PETER DRUCKER: "Quality in a product or service is not what the supplier puts in. It is what the customer gets out and is willing to pay for."
11. W. EDWARDS DEMING: concentrating on "the efficient production of the quality that the market expects," and he linked quality and management: "Costs go down and productivity goes up as improvement of quality is accomplished by better management of design, engineering, testing and by improvement of processes."
GERALD M. WEINBERG:."Value to some person".
Why quality is important in customer driven organization?
Because without high quality product and/or service, there is no reason for the customer to buy from you. Or if they did, they probably would not be satisfied with what they receive and would not buy from you again.
PRODUCTIVITY
Importance of productivity:
– Keeps costs down to improve profits and/or reduce prices.
– Enables firms to spend more on improving customer service and supplementary services.
Productivity is a measure of output resulting from a given input.
Productivity = (Output) / (Input).
Productivity may be designated in many ways such as output per workers, direct labor or group of workers, or unit of material or unit of energy or Rupee of capital investment etc.
One must keep in mind that productivity is influenced by many factors such as worker skill, motivation and effort, job methods used, quality of workmanship, employee innovation, the machines used and effectiveness of management. Productivity is the backbone of economic progress of any nation. Higher productivity leads to higher standard of living. Higher productivity results if more output can be got from same input or same output can be got from less input or more increase in output with correspondingly lesser increase in input.
Higher productivity results in reduction of costs as well as increased sales potential, more responsive customer service, increased cash flow and profits. Greater success in existing business can lead to expansion of operations and increase in number of jobs. If wage increases without accompanying productivity increase, then it will lead to increased product cost and contribute to inflation.
It has been established that an increase in productivity can be caused by five different relationships of input and output:
• Output and input increases, but the increase in input is proportionally less than increase in output;
• Output increases while input stays the same;
• Output increases while input is reduced;
• Output stays the same while input decreases;
• Output decreases while input decreases even more.
Now Taguchi method is purposed to improve the quality
Professional statisticians have welcomed the goals and improvements brought about by Taguchi methods, particularly by Taguchi's development of designs for studying variation, but have criticized the inefficiency of some of Taguchi's proposals.[5]
Taguchi's work includes three principal contributions to statistics:
• A specific loss function — see Taguchi loss function;
• The philosophy of off-line quality control; and
• Innovations in the design of experiments
LOSS FUNCTIONS
Loss Functions In Statistical Theory:-
Traditionally, statistical methods have relied on mean-unbiased estimators of treatment effects: Under the conditions of the Gauss-Markov theorem, least squares estimators have minimum variance among all mean-unbiased estimators. The emphasis on comparisons of means also draws (limiting) comfort from the law of large numbers, according to which the sample means converge to the true mean. Fisher's textbook on the design of experiments emphasized comparisons of treatment means.
Taguchi's use of loss functions:-
Taguchi knew statistical theory mainly from the followers of Ronald A. Fisher, who also avoided loss functions. Reacting to Fisher's methods in the design of experiments, Taguchi interpreted Fisher's methods as being adapted for seeking to improve the mean outcome of a process. Indeed, Fisher's work had been largely motivated by programmes to compare agricultural yields under different treatments and blocks, and such experiments were done as part of a long-term programme to improve harvests.
Taguchi specified three situations:
1. Larger the better (for example, agricultural yield);
2. Smaller the better (for example, carbon dioxide emissions); and
3. On-target, minimum-variation (for example, a mating part in an assembly).
The first two cases are represented by simple monotonic loss functions. In the third case, Taguchi adopted a squared-error loss function for several reasons:
• It is the first "symmetric" term in the Taylor series expansion of real analytic loss-functions.
• Total loss is measured by the variance. For uncorrelated random variables, as variance is additive the total loss is an additive measurement of cost.
• The squared-error loss function is widely used in statistics, following Gauss's use of the squared-error loss function in justifying the method of least squares.
1.2.3 Reception of Taguchi's ideas by statisticians:-
Though many of Taguchi's concerns and conclusions are welcomed by statisticians and economists, some ideas have been especially criticized. For example, Taguchi's recommendation that industrial experiments maximise some signal-to-noise ratio (representing the magnitude of the mean of a process compared to its variation) has been criticized widely
OFF-LINE QUALITY CONTROL
Taguchi's rule for manufacturing
Taguchi realized that the best opportunity to eliminate variation is during the design of a product and its manufacturing process. Consequently, he developed a strategy for quality engineering that can be used in both contexts. The process has three stages:
1. System design
2. Parameter (measure) design
3. Tolerance design
Let us discuss these terms one by one
SYSTEM DESIGN:-
In the system design by using the scientific methods and principal the prototypes are made. This includes design at the conceptual level by involving creativity & innovation.
PARAMETER DESIGN:-
Once the concept is established, the nominal values of the various dimensions and design parameters need to be set, the detail design phase of conventional engineering. Taguchi's radical insight was that the exact choice of values required is under-specified by the performance requirements of the system. In many circumstances, this allows the parameters to be chosen so as to minimize the effects on performance arising from variation in manufacture, environment and cumulative damage. This is sometimes called robustification.