1. Explain robust design, quality loss function, system design, parameter design, tolerance design
Answer:
1.1. Robust design:
Though robust design can be explained in different way, it can be generalized to: one step/stage of product design development process at which design experiment is made on multiple factors so that to minimize the effects of variation without avoiding the causes (since they are too difficult or too expensive to control).
1.2. Quality loss function:
It is an equation developed by Japanese business statistician Dr. Genichi Taguchi for estimating the loss of quality resulting from the deviation of a product characteristics from its intended condition (target value). Mainly quality loss is expressed in terms of money lost.
Generally, it is known that the loss progressively increases as variation increases, more precisely, Dr. Genichi Taguchi, suggests that the losses increases geometrically as the square of the deviation from the target.
1.3. System design:
System level design is the conceptualization stage of the product design. At this stage new ideas or concepts and the knowledge at which the team members gained from their education and experience will be utilized to determine the right selection of materials, geometry of parts, processes to be followed and design factors that will satisfy functional and economical specifications. To achieve an increase in quality at this level requires innovation, and therefore improvements are not always made.
1.4. Parameter design:
In parameter design stage the system variables are experimentally analyzed to determine how the product or process reacts to uncontrollable “noise” in the system; Parameter design is related to finding the appropriate ...
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...ane M. and Taguchi, Shin “The Taguchi Approach to Parameter Design” Quality Progress, Dec 1987. (http://www2.isye.gatech.edu/~roshan/publications/Taguchi.pdf)
4. Phadke, Madhav S. Quality Engineering Using Robust Design Prentice Hall, Englewood Cliffs, 1989. (http://www.e-formacion.com.mx/public_msalas/mis_docs_laptop/My%20eBooks/PDF/Estad%C3%ADstica/Quality%20Engineering%20Using%20Robust%20Design.pdf )
5. http://www.businessdictionary.com/definition/quality-loss-function.html#ixzz31zDnGln0
6. http://cs.anu.edu.au/courses/ENGN8101/Loss%20functions-lecture%205.pdf
7. https://controls.engin.umich.edu/wiki/index.php/Taguchi_quality_loss_function_and_specification_tolerance_design
8. http://documentation.statsoft.com/STATISTICAHelp.aspx?path=Experimental/Doe/Overview/TaguchiMethodsSignaltoNoiseSNRatios
9. https://onlinecourses.science.psu.edu/stat503/node/74
Lawson, Bryan. How Designers Think: The Design Process Demystified. 4th ed. Oxford: Architectural Press, 2006.
4. "Failure Mode Effects Analysis (FMEA)." - ASQ. N.p., n.d. Web. 21 Apr. 2014. .
There is a business notion that is related to this aspect in quality achievement called the Six Sigma. Bruce (2002), defined it as “A term used is statistics to represent standard deviation, an indicator of the degree of variation in a set of measurements or a process.” (p. 182) It cannot be readily said which organizations in industrial laundry follow the Six Sigma, but it can be inferred that most of them execute such technique. In Sex Sigma, the general rule is that the defect or mistake done in a product or service must not exceed 3.4 standard deviation. That is 3.4 defects per million opportunities. (Bruce, 2002, p. 2)
The phrase “design of experiments” refers to any orderly plan, or design, that describes four key features of an experiment, as summarized by Finney [1]:
In order for an experiment to be considered a true experimental design, the design must fit specific criteria. The researcher must have a hypothesis for a cause and effect relationship between variables, the treatment group, the control group, random selection for the treatment group, and random assignment for the control group. In a simple experiment, the researcher forms two groups that are similar or equivalent, through probability, to each other in every way possible appropriate to the concept of experiment. The treatment group receives the procedure for the experiment and the control group does not. Therefore, the only difference between the groups will be that one group receives the treatment for the experiment and one group does note. After the experiment is conducted the researcher analysis the results in both groups.
Materials go to the factory → products come out and go to customers → companies do consumer research → companies do design of product + service and re-design → then it will affects three parts 1) materials; 2) processes; 3) product. As a result, it will improve the process.
The design was a laboratory experiment, which allows the experimenter to establish a cause-effect relationship between the independent and the dependent variable.
Juran, J.M., "Japanese and Western Quality A Contrast," Quality, January 1979, pages 8 12; and February 1979, pp. 12-15. Juran, J. M., "The QC Circle Phenomenon," Industrial Quality Control, January 1967, pp. 329-36.
In conclusion, aesthetic and function play a significant part when it comes to industrial design. Although some believe design should be purely focus on aesthetic meanwhile the others believe design should be functional while has an appealing appearance. The research material clearly support the idea that design being function while visually appealing. To achieve that which requires involvement in various stages of design process and requires enormous amount of design thinking processes as well.
In the system, design analysis and other additional analysis are used to reduce product cost by analyzing the trade-offs between product functionality and total product cost. Review and revision are carried out throughout the process. Moreover, the continuous improvement and operational control are also used to further reduce costs. However, the functionality reduction during the process will adversely affect the differentiation strategy as what we mentioned
One of the common designing techniques using in Architecture is parametric design. The term of parametric Design “is a methodology of using advanced visualization technology and mathematical algorithms to optimize structure and material form to advance resource efficiency and innovative solutions within the area of built environment” . However, the boundary line between Parametric design and the current computer-aided drafting or modelling approach is not very clear (Monedero, 2000) . However, it provides a precise formulation instead of complex relation between elements and subsystems. According to Schumacher 2008, there are three significant agendas could be beneficial to consider through this process. Firstly, move from single system differentiation to the scripted association of mutable subsystems. Secondly, the complex configuration. The third agenda is to allow the architecture environment to reconfigure and adapt itself in r...
Creswell, J., 2003, A framework for design, 2nd ed., Sage Publications, Thousand Oaks, California, pp. 3-26.
The Quality control mechanism needs to identify the ability of parts in the space shuttle to face reactions from wind, humidity, temperature etc as well make sure the design measures are 100% accurate and the necessary resources are allocated in the designing process to achieve optimum quality in design and should always try to be proactive rather than being reactive which can reduce quality failure cost as well increase effectiveness of the design to face any vulnerabilities.
Furthermore, the RMSs are designed for a specific range of production requirement as opposed to a single set or the wide range of the product requirements. However, the production system can be reconfigured if the product requirement changes by adding, removing, or modifying specific process capabilities, controls, and software or machine structure. It can also accommodate any change in the technology thus prove to be efficient and cost effective in long run unlike its predecessors—DMS and
Client(s) may be in the first stage of our design thinking sequences (Archer, 1984, p. 67), and then the designer job is to explore what is the problem, what do we want, what do they need: to produce a design to meet the requirements. The initial design problem presented to the designer may be poorly and incompletely described (McDonnell, 1997, p. 45...