any help on taguchi method and design of experiment?
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A technique for designing and performing experiments to investigate processes where the output depends on many factors (variables; inputs) without having to tediously and uneconomically run the process using all possible combinations of values of those variables. By systematically choosing certain combinations of variables it is possible to separate their individual effects. \n\nA special variant of Design of Experiments (DOE) that distinguishes itself from classic DOE in the focus on optimizing design parameters to minimize variation BEFORE optimizing design to hit mean target values for output parameters.
875072
Here's an interesting experiment.
84704
What equipment?\nWhat experiment?\nWhat error?
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check thermaltake and tagan\n\nhttp://www.thermaltake.com/\nhttp://www.tagan.com/
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1. Wash the apparatus with some acid first and then rinse with water. \n2. Place them in a position where there will be no risk of falling. \n3. If you see any cracks on any apparatus, do not use them for heating and inform your teacher or lab assistant. \nyou cannot improve these apparatus, since they made with pyrex or plastic or some sort of fibre glass.
375662
Take timer and thermometer.\n\nHeat the first metal, and check temperature every 5 seconds or so and write the temperature in a table.\n\nDo it with all the metals you want to check and compare the results.\n\nit should take about an hour depending on how many differnt metals you want to check, and it dont cost much.
1134906
Here's a link to a PDF file I wrote consisting of all the steps involved (though not quick enough to beat the other two answerers...)\n\nhttp://prash4.esmartdesign.com/ans2.pdf
376678
try the Bates method and pinhole glasses
285116
A loss function is generally defined as the variance of some statistical group from an optimum value. The Taguchi loss function (ref.) has meaning in quality control where the variance affects the quality of a product and the cost of reworking or discarding unacceptable products. The ref. has a fuller definition, formulas and examples.
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You will find all details with calculation and experiment on:\nhttp://www.jgp.org/cgi/reprint/1/4/387.pdf
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first you decide what temp. you can give the product or max. temperature on that product stable. secondly your batch size . \n, third API CHEMICAL COMPOSITION ( i.e what solvent , water etc. you want to remove.\nfourth nature of product.\nafter that you can decide what you require.steam / hot water drier with vacuum system OR VACUUM is only sufficient. or blender cum dryer , orbital mixtue etc.\nIf you provide complete detail ,I try to design the dryer for you.
1041556
The answer to your question is indeterminate, for several reasons\n1) This is a trade secret that competitors would like to know the answer to.  Hire a trade spy.\n2) What are the L x W x H dimensions of the product?. Costs will be determined by the size of the "bath" vessel required.\n3) The surface area-to-volume ratio will determine the melt-spread time, product cooling time required, etc.\n4) Is the production order for 1 ton per day? 2 tons? 10 tons?\n5) WHAT Clarity (letter) per WHAT Rating per WHAT GPS Standard (#) ?
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I guess the best would be NOT TO TRY YOURSELF & contact the manufacturer, they will do it far more professionally.\n\nDo it even if you ve to pay a bit
605673
An integrated microprocessor-based fermenter controller was developed in 1980 for an operational environment at Cetus Corp. The main goals in the design and construction of the system were (1) to facilitate scale-up; (2) to provide flexibility and high performance for optimizing fermentation processes; and (3) to be cost-effective for 15 in-house systems. It was also developed to work in conjunction with a laboratory minicomputer for on-line optimization experiments. The controller controls temperature, agitation, dissolved oxygen, pH, and foam throughout each fermentation run without manual intervention. The feedback control parameters have been optimized to provide very accurate control over a wide range of setpoint conditions and under rapidly changing metabolic conditions such as induced during an Escherichia coli batch run. The controller has also been configured to monitor, display, and record each of the controlled variables; support the interactive operator console; and communicate with the laboratory computer. In over 4 years of operation, these systems have met the design goals and have proven to be very reliable. The controller is described, its operational performance presented, and a typical fermentation run delineated
662479
that depends upon wheather you are going to design experiments for bulk product aspirin or formulations like aspirin tablets.\nfor bulk products tests like melting point, assay(percentage purity), solubility testing .... etc,.\nif that is a tablet you have to proceed with release rate, tablet weight, frightness test,etc.....
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This work aims at identifying the effects of the main operational spray-dryer variables on the milk powder quality. Experiments have been performed in a pilot spray-dryer following the full-factorial design technique to provide data and correlations that predict the whole powder properties as function of the main operational variables of the spray-dryer. The emulsion feed flow rate, the atomization rotation and the inlet air temperature have been chosen as the independent variables while the residual moisture content, the tapped bulk density, the cohesion force enhancement between particles as well as size distribution of agglomerate and its morphology are the response variables that quantify the powder quality. Correlations obtained are analyzed and incorporated into a mathematical model previously developed for simulating the spray-drying of whole milk emulsion.
816490
Its better to get a design engineering guide from one of the plastic raw material suppliers as modifying the melt flow index would change many other properties also. A manufacturer rather than a distributor would probably provide you the information more readily.