04-01-2013, 04:14 PM
ROBUST DESIGN Seminar Report
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ABSTRACT
The underlying principles, techniques & methodology of robust design are
discussed in detail in this report with a case study presented to appreciate the
effectiveness of robust design. The importance of Parameter design & Tolerance
design as the major elements in Quality engineering are described. The Quadratic loss
functions for different quality characteristics are narrated, highlighting the fraction
defective fallacy. The aim of the robust design technique is to minimize the variance
of the response and orthogonal arrays are an effective simulation aid to evaluate the
relative effects of variation in different parameters on the response with the minimum
number of experiments. Statistical techniques like ANOM (analysis of means) and
ANOVA (analysis of variance) are the tools for analyzing the data obtained from the
orthogonal array based experiments. Using this technique of robust design the quality
of a product or process can be improved through minimizing the effect of the causes
of variation without eliminating the causes. Fundamental ways of improving the
reliability of a product are discussed highlighting the importance of robust design on
this. Based on the classification of uncertainties in design, the role of robust design
optimization & reliability based design optimization are discussed. The mathematical
formulations for these types of optimization strategies are explained. Based on this
study, it can be concluded that the robust design methodology based on Taguchi’s
principles will take care of the entirety of the noise factors which can cause
underperformance and failures, but it will be advantageous to do a robust & reliability
based design optimization because apart from making the design insensitive to noises,
it will enable the designer to predict the reliability of the product. The current research
activities in the application of robust design techniques in the aerospace systems are
also discussed, one with respect to relaxing manufacturing tolerances on an aircraft
nacelle to reduce cost and the other, tackling uncertainties in Mach number in the
design optimization of an airfoil for a transport aircraft.
Introduction
The knowledge of scientific phenomena and past experience with similar
product designs and manufacturing processes form the basis of the engineering design
activity. However, a number of new decisions related to the particular product must
be made regarding product architecture, parameters of the product design, the process
architecture and parameters of the manufacturing process. A large amount of
engineering effort is consumed in conducting experiments (either with hardware or by
simulation) to generate the information needed to guide these decisions. Efficiency in
generating such information is the key to meeting market windows, keeping
development and manufacturing cost low and having high-quality products. Robust
Design is an engineering methodology for improving productivity during design &
development so that high quality products can be produced at low cost.
Designing high quality product and processes at low cost is an economic and
technological challenge to the engineer.
Historical perspective.
When Japan began its reconstruction efforts after World War II, it faced an acute
shortage of good quality raw materials, high quality manufacturing equipment and
skilled engineers. The challenge was to produce high quality products and continue to
improve the quality under those circumstances. The task of developing a methodology
to meet the challenge was assigned to Dr. Genichi Taguchi, who at that time was a
manager in Nippon Telephone & Telegraph Company. Through his research in the
1950s and early 1960s, Dr.Taguchi developed the foundations of Robust Design and
validated its basic philosophies by applying them in the development of many
products. In recognition of this contribution, he received the Individual Deming
Award in 1962, which is one of the highest recognition in the quality field. [3]
Quality Engineering using Robust Design
Quality Engineering Principles
Though “Quality” can be defined as “Conformance to specification” and
fitness for use” etc in the general concept, these definitions do not cover the entire
implied meaning of Quality. The Ideal Quality a customer can expect is that the
product delivers the target performance each time the product is used, under all
intended operating conditions and throughout its intended life, with no harmful side
effects.
Dr. Taguchi brought out the fallacy in the fraction defective definition for
quality, in which the number of defectives based on the principle depicted in Fig-1
was the only concern. As per his theory [2], the measure of quality of a product is in
terms of the total loss to society due to functional variation and harmful side effects.
Under ideal quality, this loss is equal to zero. Greater the loss, lower the quality. As
per this the total cost of a product is the sum of the operating cost including
maintenance & inventory, the manufacturing cost, the R & D cost (the time,
Laboratory charges, resources etc) and the cost incurred by its breakdown and thereby
the losses caused to the society. The product life cycle cost is divided into the cost
incurred before sale to the customer and after sale to the customer. Quality
engineering is concerned with reducing both of these costs and thus is an
interdisciplinary science involving engineering design, manufacturing operations and
economics.
Identification of control & noise factors
As explained earlier control factors are those factors that a manufacturer can
control in the design of a product, the design of a process, or during a process. Examples:
design variables (widths, heights), assembly method, cooling temperature, cycle time,
materials, speeds, feeds. So according to the design problem, the control factors are to be
identified. Similarly, the noise factors, which a designer or a manufacturer can not or
wishes not to control (because of cost reasons) are also to be identified. Examples:
material inconsistencies, supplier variation, machine operators, ambient temperature,
ambient humidity.
A Case Study
Now a specific case study[3] is addressed here to understand the different steps &
aspects of robust design. The robust design is applied on a process of polysilicon
deposition on thin wafers. The process set up schematic is shown in fig-16 . Saline &
Nitrogen gas are introduced at one end and pumped out at the other. The Saline gas
pyrolizes and a polysilicon layer is deposited on top of the oxide layer on the wafers.
Two carriers each carrying 25 wafers can be placed inside the reactor at a time so that
polysilicon is simultaneously deposited on 50 wafers. The problems observed were (i) too
many surface defects and (ii) too large a thickness variation. So robust design
methodology is adopted to improve the performance or quality of the process.