25 January 2007MATS326-3 problem.ppt Problem Solving Techniques MST326 lecture 3

25 January 2007 MATS326-3 problem.ppt

Problem Solving Techniques

MST326 lecture 3


Outline of lecture

• Brainstorming• Mind maps• Cause-and-Effect diagrams• Failures Mode and Effects Analysis• Fault Tree Analysis• Design of Experiments


Brainstorming

• proposed by Alex Osborn“for the sole purpose ofproducing checklists of ideas”

• technique to identify causesand develop solutions to problems

• “seeking the wisdom of ten people rather than the knowledge of one person” [Kaizen Institute]


Brainstorming

• no criticism is permittedo “only stupid question is one that is not asked” [Ho]

• wild ideas are encouragedo often trigger good ideas from someone else

• each person contributes one ideao further single ideas on second circuito repeat until no further ideas

• all contributions are recorded in view


Brainstorming

• Osborn proposed 75 fundamental questions

• can be reduced to: seek other uses? adapt? modify? magnify? minify? substitute?

rearrange? reverse?

combine?

TRIZ

• Teorija Reshenija Izobretatel'skih Zadach

• loosely translates asTheory of Inventive Problem Solving (TIPS)

• 40 Inventive Principles


40 inventive principles of TRIZ

IP 01: Segmentation IP 02: Taking out IP 03: Local quality

IP 04: Asymmetry IP 05: Merging IP 06: Universality

IP 07: Nested doll IP 08: Anti-weight IP 09: Preliminary anti-action

IP 10: Preliminary action IP 11: Prior cushioning IP 12: Equipotentiality

IP 13: The other way round IP 14: Spheroidality or curvature IP 15: Dynamics

IP 16: Abundance IP 17: Another dimension IP 18: Mechanical vibration

IP 19: Periodic action IP 20: Continuity of useful action IP 21: Rushing through

IP 22: Blessing in disguise IP 23: Feedback IP 24: Intermediary

IP 25: Self-service IP 26: Copying IP 27: Cheap short-lived objects

IP 28: Mechanics substitution IP 29: Pneumatics and hydraulics

IP 30: Flexible shells and thin films IP 31: Porous materials IP 32: Colour change

IP 33: Homogeneity IP 34: Discarding and recovering IP 35: Parameter change

IP 36: Phase transition IP 37: Thermal expansion IP 38: Strong oxidants

IP 39: Inert atmosphere IP 40: Composite materials



Mind maps

• attributed to Tony Buzano classic book “Use Your Head”


Mind maps

Image from http://www.loanedgenius.com/scrabble_2_letter_words.gif

http://www.loanedgenius.com/scrabble_2_letter_words.gif


Cause-and-Effect diagrams

• Cause-and-Effect diagramo often referred to as a fishbone diagramo or an Ishikawa diagram

• introduced by Kaoru Ishikawao simple graphical method to record and

classify a chain of causes and effects in order to resolve a quality problem


Cause-and-Effect diagrams

• Clarify the object effect

• Pick causes

• Determine the priority causes

• Work out the counteractions for priority causes

• implement appropriate solutions to eliminate or reduce the causes of problems


Cause-and-Effect diagrams I

• Clarify the object effect o a numerical measurement should be

established against which subsequent improvement can be judged


Cause-and-Effect diagrams IIPick causes• create a team of people to brainstorm possible causes that may lead to the effect • study the actual effect in the problem environment • on a horizontal line draw diagonal branches for direct causes of the effect • using arrows onto the branches create sub-branches for appropriate secondary causes • confirm all elements of the diagram are correctly positioned • quantify the causes wherever possible


Cause-and-Effect diagrams III

• Determine the priority causes o analyse any existing data for the problem o if practical, create a Pareto diagram. o otherwise, determine a ranking of the

relative importance of each cause.


Cause-and-Effect diagrams IV

• Work out the counteractions for priority causes o put in place appropriate solutions

to eliminate or reduce the causes of problems


Cause-and-Effect diagram:

• Image from http://www.ifm.eng.cam.ac.uk/dstools/gif/ishika.gif

http://www.ifm.eng.cam.ac.uk/dstools/gif/ishika.gif


Failures Mode and Effects Analysis

• FMEA iso a useful tool for reliability analysiso systematic check of a product or process

• function• failure causes• failure modes• failure consequences



• Requires a thorough knowledge ofo functions of the componentso contribution of those components

to function of the system

• For every failure mode at a low level,failure consequences are analysed ato the local levelo the system level



• FMEA is usually qualitativebut may also be quantitative

• initiated during planning and definitionof a project to investigate qualitative reliability demands of the market

• during design and development, for quantitative reliability activities


Table From Evans and Lindsay Chapter 13



• design-FMEA for design reviewso definition and limiting of the systemo choice of complexity levelo check of component functionso check of system functionso identification of possible failure modeso identification of consequences of failureso possibility of failure detection and failure localisationo assessment of seriousness of failureo identification of failure causeso interdependence of failureso documentation



• quantitative design-FMEA a.k.a. FMECAFailure Mode, Effects and Criticality Analysiso consider every componento quantify and rank different failure modes

• F = probability of failure• A = seriousness (consequences of failure)• U = probability of detection

o subjective judgements on a scale of 1-5 or 1-10o Product (F*A*U) = Risk Priority Number (RPN)



• Process-FMEA for o pre-production engineeringo design of process controlo process improvement

• FMEA is efficient where component failure leads directly to system failure

• for more complex failures, FMEA may be supplemented by Fault Tree Analysis (FTA)


Some URLs for FMEA

• http://www.fmeainfocentre.com/• http://supplier.intel.com/ehs/fmea.PDF• http://www.cs.mdx.ac.uk/puma/wp18.pdf• http://www.sverdrup.com/safety/fmea.pdf• http://www.uscg.mil/hq/msc/fmea.doc

• http://www.competitiveedge.net/pdfs/fmea.pdf

• http://www.fmeca.com/ffmethod/methodol.htm• http://www-personal.engin.umich.edu/~wmkeyser/ioe539/fmea.pdf

• http://www.engin.umich.edu/class/eng401/003/LCNotes/fmea.pdf


Fault Tree Analysis• Logical chart of occurrences

to illustrate cause and effects

• developed by DF Haasl, HA Watson,BJ Fussell and WE Vesely

• initially at Bell Telephone Laboratoriesthen North American Space

Industry


Fault Tree Analysis

• Common symbols used 1omain evento basic evento incompletely analysed evento restriction


Fault Tree Analysis

• Common symbols used 2

o or-gate

o and-gate

o transfer to or from another place

&

1

+


Figure From Evans and Lindsay Chapter 13


Design of Experiments

• originally conceived byRonald Aylmer Fisherat Rothampstead Experimental Station during the 1920so analysing plant growing plots

under different conditions, andneeded to eliminate systematic errors.

Image from http://www.csse.monash.edu.au/~lloyd/tildeImages/People/Fisher.RA/

http://www.csse.monash.edu.au/~lloyd/tildeImages/People/Fisher.RA/

http://www.csse.monash.edu.au/~lloyd/tildeImages/People/Fisher.RA/


Experimental design• Randomisation

• Replication - repetition so that variability can be estimated

• Blocking - experimental units in groups (blocks) which are similar

• Orthogonality - statistically normal.

• Use of factorial experimentsinstead of one-factor-at-a-time



• full factorial experimentowhere a number of factors

may influence the output of a process, it is possible to study all combinationsof levels of each factor

o if the number of factors considered increases, then number of experiments required increases more rapidly.



• For two levels of n-variables,the number of experiments required is 2n

o 4 experiments for two variables(low-low, low-high, high-low and high-high)

o 16 experiments for four variableso 64 experiments for six variables.

• If three levels (low - normal - high) or more are to be studied, then a full factorial experiment soon becomes impractical.



• results plotted to indicate the influence of each of the factors studied

• when one factor affects the response,this is known as the main effect.

• when >1 factor affects the response,this is termed an interaction.



Genichi Taguchi developed orthogonal arrays

• fractional factorial matrix

• permits a balanced comparisonof levels of any factor with a reduced number of experiments.

• each factor can be evaluated independently of each of the other factors.


Orthogonal arrays

L4: three two-level factors

L9: four three level factorsArrays from http://www.york.ac.uk/depts/maths/tables/orthogonal.htm

http://www.york.ac.uk/depts/maths/tables/orthogonal.htm


Common orthogonal arrays

Array Levels EquivalentFull Factorial

L4 3 x 2 8

L8 7 x 2 128

L9 4 x 3 81

L12 11 x 2 2 048

L16 15 x 2 32 768

L25 6 x 5 15 625

L27 13 x 3 1 594 323Table from Tony Bendell “Taguchi Methods”, 1989


Taguchi

• Quality Loss FunctionL(x) = k ( x - t )2

o L = the loss to society of a unit of output at value x

o t = the ideal target valueo k = constant

• as non-conformance increases,losses increase even more rapidly

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25 January 2007MATS326-3 problem.ppt Problem Solving Techniques MST326 lecture 3