MAE486_Fall11_L22_S - MAE 486 Design of Mechanical Systems...

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Unformatted text preview: MAE 486 Design of Mechanical Systems Lecture 22 Fall 2011 Today s topics: Manufacturing consideration of design (Chapter 13); Robust design; Achieving Part Standardiza7on •  With the importance of standardiza7on in mind, what we should avoid? –  Not free to make arbitrary decisions when sizing parts. •  A common misconcep7on: –  Minimum ­cost design minimum ­weight design. Why is it not always right? •  How to be aware of the existence of an iden7cal part? –  One way is to use Group Technology (GT); see Sec7on 13.7.3. Mistake ­Proofing •  Everybody makes mistakes—How to account for that in design? •  Technique: Poka ­yoke (Japanese: Mistake ­ proofing) •  Basic tenet: –  Human errors: individual operators •  Goal:  A state of zero defects (varia7on from design or manufacturing specs) Shigeo Shingo What are the frequent Mistakes •  Design mistakes: Where do they come from? •  Defec7ve material mistakes –  Poorly chosen: –  Failed to meet –  Poorly designed dies or molds Frequent Mistakes •  Manufacturing mistakes –  –  –  –  –  –  –  –  OmiXed opera7on OmiXed parts Wong orienta7on of part; misaligned part; wrong loca7on of part Selec7on of wrong parts Mis ­adjustments Commit a prohibited opera7on (e.g., accident) Added material or parts (e.g., dropping a screw into the assembly) Misread, mis ­measure, or mis ­interpret •  Human mistakes Metal ­Cu[ng Processes Metal ­Cu[ng Processes (cont’d) •  Primary mo9on •  Feed mo9on Machinability •  What does it mean? •  What cons7tutes to good machinability? •  What is the general trend? –  Hardness of the workpiece material  The machinability. –  Example? DFM Guideline for Machining •  Rule 1: How to achieve economy in machining? •  Rule 2: Sequence of machining maXers: •  Rule 3: DFM Guideline for Machining (cont’d) •  Rule 4: Avoid reclamping •  Rule 5: Use whenever possible; •  Rule 6: Avoid on unexposed surfaces of the workpiece (when the part is gripped in the work ­holding device); •  Rule 7: No interference •  Rule 8: Adjust  minimize the forma7on of sharp burrs. Process Capability •  What is process capability? –  The sta7s7cal informa7on about the parts produced by the a machine or process  The percentage of parts that fall outside of a specified tolerance band. •  Process capability index Cp Control charts Process Capability (cont’d) •  Usual limits on machine varia7on: ,  •  For mass produc7on, the percentage of defects is cri7cal Process Capability  ­ ­ Examples •  A spindle has a spec. on its diameter of 1.5+/ ­0.009 inch. If Cp=1. what is δ ?. ˆ •  What would be std to achieve Cp=1.33? •  If Cp=1.33 and mean is centered within the range, how many oversize parts? Process Capability •  If the mean is not centered within the tolerance range, process capability index Cpk •  The distance of the process mean differs from the midpoint of the tolerance region is give by •  How does Cpk and Cp relate to each other? Which one is bigger? Taguchi Methods •  What is it? –  The quality level of a product = The total loss from The failure of the product to deliver the expected performance + Harmful side effects of the product (including the opera7ng cost). Example for each case? Noise Factors and S/N Ra7os •  The input parameters affec7ng the quality of the product/process  •  Noise factors: •  What are they? –  Varia1onal noise: –  Inner noise: –  Design noise: –  External noise (outer noise): Signal ­to ­Noise Ra7os •  Ra7o of the mean (signal) and the varia7on (noise)  The response or output of experiment. •  Three forms of the S/N ra7o corresponding to three loss func7ons –  Nominal ­is ­best type –  Smaller ­the ­beXer type –  Larger ­the ­beXer ­type Understanding, why do these eqns. Make sense? Robust Design •  What is it? •  Parameter design: •  How to do parameter design? –  Step 1: –  Step 2: Parameter Design •  What is the approach? –  Extensive planned experiments. •  How to be efficient in experiments? –  Sta7s7cally designed –  Based on frac7onal factorial designs (a)  Three parameters P tested at two levels. (b) Frac7onal factorial design. All test combina7ons considered. Parameter Design (cont’d) •  What is the trade ­off? –  Min (# of tests) vs. Loss (Detailed informa7on of interac7ons). •  Two commonly used orthogonal arrays. (a)  L4 deals with three control factors at two levels. A total of 4 runs of DOE is needed. (b) L9 array considers four control factors each at three levels. A total of 9 runs of DOE is needed. Parameter Design (cont’d) •  Which to use? Depends on –  The number of control factors and noise factors. –  Whether you are seeking more resolu7on in the results, especially if you feel the responses will be nonlinear. •  Design of experiments usually consists of two parts. –  Part I: A design parameter matrix (inner array) from which the effects of the control parameters are determined through the use of a suitable orthogonal array. –  Part II: A smaller noise matrix (outer array) is formed for noise parameters. Taguchi Robust Design Method What are the steps? •  Step 1: Problem defini7on. –  Select the parameter to be op7mized and the objec7ve func7on. •  Step 2: Selec7on of design parameters; –  The control parameters (controlled under the designer) and the noise parameters (contribute to the varia7on caused by the environment. •  Step 3: Experiment design –  Select the appropriate frac7onal factorial array, the number of levels to be used, and the range of the parameters that correspond to these levels. •  Step 4: Do the experiments –  Follow DOE; •  Step 5: Results analysis; –  Calculate the S/N. •  Step 5: Repeat steps 1 to 4 if no clear op7mum value. OR: •  Step 5: Validate the results; –  Perform a confirming experiment when the method gives a set of op7mal parameter values. Robust Design Example •  Problem: –  A new prototype of new game box has indicator light failure •  Causes: –  Poor solder joints. •  Root cause: –  Use of improper solder paste (i.e., solder balls and flux). •  Objec7ve: –  Design the best condi7ons for making strong solder joints by using the Taguchi method. Robust Design Example (cont’d) •  Step 2: Select control Parameters: –  Four control parameters (with L9 orthogonal array, i.e., three levels) •  Step 2: Select noise parameters •  Three noise parameters (with L4 orthogonal array, i.e., two levels) Robust Design Example (cont’d) •  Step 3: Experiment design –  For each run in L9, we conduct four experiments. For example, run 2 in L9 is executed four 7mes to include the noise matrix. –  The first trial condi7on: a new can of paste, water rinse, and horizontal spray –  The last trial condi7on: a can of paste opened one year ago, a chlorocarbin cleaning agent, and horizontal spray for cleaning. •  Step 4: Experiment run –  For each of the four trials of run 2, measure a response that represents the objec7ve func7on that we are aXemp7ng to op7mize: shear strength of the solder joint measured at room temperature. Robust Design Example (cont’d) •  Step 5: Results analysis –  For four trials, find the average strength measurements and the standard devia7on. •  Step 5: Results analysis •  The appropriate response parameter: the S/N ra7o. Which one to use here? Robust Design Example (cont’d) •  Step 5: Obtain the parameter matrix. Robust Design Example (cont’d) •  Step 5: Determine the average response for each of the four control parameters at each of its three levels. •  Step 5: Plot the average S/N ra7os against the test level Robust Design Example (cont’d) •  Step 5: Observe the plots: Which factor is not important? S/N larger the beXer or the other way around? •  Step 6: Obtain the op7mum se[ng of the control parameters ...
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