Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
SlideShare a Scribd company logo

QM-027-Problem Solving Techniques

•
•
H
handbook

The document discusses various problem solving techniques including: - Brainstorming which encourages wild ideas and builds on others' contributions without criticism. - Mind maps which use diagrams to organize ideas spatially. - Cause-and-effect diagrams which classify chains of causes and effects to resolve quality problems. - Failure mode and effects analysis (FMEA) which systematically checks for potential failures, causes, and consequences to improve reliability.

1 of 37
Problem Solving Techniques MST326 lecture 3 25 January 2007 MATS326-3 problem.ppt
Outline of lecture Brainstorming Mind maps Cause-and-Effect diagrams Failures Mode and Effects Analysis Fault Tree Analysis Design of Experiments 25 January 2007 MATS326-3 problem.ppt
Brainstorming proposed by Alex Osborn “for the sole purpose of producing checklists of ideas” technique to identify causes and develop solutions to problems “ seeking the wisdom of ten people rather than the knowledge of one person” [Kaizen Institute] 25 January 2007 MATS326-3 problem.ppt
Brainstorming no criticism is permitted “ only stupid question is one that is not asked” [Ho] wild ideas are encouraged often trigger good ideas from someone else each person contributes one idea further single ideas on second circuit repeat until no further ideas all contributions are recorded in view 25 January 2007 MATS326-3 problem.ppt
Brainstorming Osborn proposed 75 fundamental questions can be reduced to:  seek other uses?  adapt? modify?  magnify? minify?  substitute?  rearrange?  reverse?  combine? 25 January 2007 MATS326-3 problem.ppt
TRIZ   Teorija Reshenija Izobretatel'skih Zadach loosely translates as Theory of Inventive Problem Solving (TIPS) 40 Inventive Principles 25 January 2007 MATS326-3 problem.ppt
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 25 January 2007 MATS326-3 problem.ppt
Mind maps attributed to Tony Buzan classic book “Use Your Head” 25 January 2007 MATS326-3 problem.ppt
Mind maps Image from http://www.loanedgenius.com/scrabble_2_letter_words.gif 25 January 2007 MATS326-3 problem.ppt
Cause-and-Effect diagrams Cause-and-Effect diagram often referred to as a fishbone diagram or an Ishikawa diagram introduced by Kaoru Ishikawa simple graphical method to record and classify a chain of causes and effects in order to resolve a quality problem 25 January 2007 MATS326-3 problem.ppt
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 25 January 2007 MATS326-3 problem.ppt
Cause-and-Effect diagrams I Clarify the object effect a numerical measurement should be established against which subsequent improvement can be judged 25 January 2007 MATS326-3 problem.ppt
Cause-and-Effect diagrams II 25 January 2007 MATS326-3 problem.ppt Pick 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 analyse any existing data for the problem if practical, create a Pareto diagram.  otherwise, determine a ranking of the relative importance of each cause. 25 January 2007 MATS326-3 problem.ppt
Cause-and-Effect diagrams IV Work out the counteractions for priority causes put in place appropriate solutions to eliminate or reduce the causes of problems 25 January 2007 MATS326-3 problem.ppt
Cause-and-Effect diagram: Image from http://www.ifm.eng.cam.ac.uk/dstools/gif/ishika.gif 25 January 2007 MATS326-3 problem.ppt
Failures Mode and Effects Analysis FMEA is a useful tool for reliability analysis systematic check of a product or process function failure causes failure modes failure consequences 25 January 2007 MATS326-3 problem.ppt
Failures Mode and Effects Analysis Requires a thorough knowledge of functions of the components contribution of those components to function of the system For every failure mode at a low level, failure consequences are analysed at the local level the system level 25 January 2007 MATS326-3 problem.ppt
Failures Mode and Effects Analysis FMEA is usually qualitative but may also be quantitative initiated during planning and definition of a project to investigate qualitative reliability demands of the market during design and development, for quantitative reliability activities 25 January 2007 MATS326-3 problem.ppt
25 January 2007 MATS326-3 problem.ppt Table From Evans and Lindsay Chapter 13
Failures Mode and Effects Analysis design-FMEA for design reviews definition and limiting of the system choice of complexity level check of component functions check of system functions identification of possible failure modes identification of consequences of failures possibility of failure detection and failure localisation assessment of seriousness of failure identification of failure causes interdependence of failures documentation 25 January 2007 MATS326-3 problem.ppt
Failures Mode and Effects Analysis quantitative design-FMEA a.k.a. FMECA Failure Mode, Effects and Criticality Analysis consider every component quantify and rank different failure modes F = probability of failure A = seriousness (consequences of failure) U = probability of detection subjective judgements on a scale of 1-5 or 1-10 Product (F*A*U) = Risk Priority Number (RPN) 25 January 2007 MATS326-3 problem.ppt
Failures Mode and Effects Analysis Process-FMEA for pre-production engineering design of process control 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) 25 January 2007 MATS326-3 problem.ppt
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 25 January 2007 MATS326-3 problem.ppt
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 Laboratories then North American Space Industry 25 January 2007 MATS326-3 problem.ppt
Fault Tree Analysis Common symbols used 1 main event basic event incompletely analysed event restriction 25 January 2007 MATS326-3 problem.ppt
Fault Tree Analysis Common symbols used 2 or-gate and-gate transfer to or from another place 25 January 2007 MATS326-3 problem.ppt &  1 +
25 January 2007 MATS326-3 problem.ppt Figure From Evans and Lindsay Chapter 13
Design of Experiments originally conceived by Ronald Aylmer Fisher at Rothampstead Experimental Station during the 1920s analysing plant growing plots under different conditions, and needed to eliminate systematic errors. Image from http://www.csse.monash.edu.au/~lloyd/tildeImages/People/Fisher.RA/ 25 January 2007 MATS326-3 problem.ppt
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 experiments instead of one-factor-at-a-time 25 January 2007 MATS326-3 problem.ppt
Design of Experiments full factorial experiment where a number of factors may influence the output of a process, it is possible to study all combinations of levels of each factor if the number of factors considered increases, then number of experiments required increases more rapidly.  25 January 2007 MATS326-3 problem.ppt
Design of Experiments For two levels of n-variables, the number of experiments required is 2 n 4 experiments for two variables (low-low, low-high, high-low and high-high) 16 experiments for four variables 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. 25 January 2007 MATS326-3 problem.ppt
Design of Experiments 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 . 25 January 2007 MATS326-3 problem.ppt
Design of Experiments Genichi Taguchi developed orthogonal arrays fractional factorial matrix permits a balanced comparison of levels of any factor with a reduced number of experiments. each factor can be evaluated independently of each of the other factors.  25 January 2007 MATS326-3 problem.ppt
Orthogonal arrays L4: three two-level factors L9: four three level factors Arrays from http://www.york.ac.uk/depts/maths/tables/orthogonal.htm 25 January 2007 MATS326-3 problem.ppt
Common orthogonal arrays 25 January 2007 MATS326-3 problem.ppt Table from Tony Bendell “Taguchi Methods”, 1989 Array Levels Equivalent Full Factorial L 4 3 x 2 8 L 8 7 x 2 128 L 9 4 x 3 81 L 12 11 x 2 2 048 L 16 15 x 2 32 768 L 25 6 x 5 15 625 L 27 13 x 3 1 594 323
Taguchi Quality Loss Function L(x) = k ( x - t ) 2 L = the loss to society of a unit of output at value x   t = the ideal target value k = constant as non-conformance increases, losses increase even more rapidly 25 January 2007 MATS326-3 problem.ppt

More Related Content

QM-027-Problem Solving Techniques

  • 1. Problem Solving Techniques MST326 lecture 3 25 January 2007 MATS326-3 problem.ppt
  • 2. Outline of lecture Brainstorming Mind maps Cause-and-Effect diagrams Failures Mode and Effects Analysis Fault Tree Analysis Design of Experiments 25 January 2007 MATS326-3 problem.ppt
  • 3. Brainstorming proposed by Alex Osborn “for the sole purpose of producing checklists of ideas” technique to identify causes and develop solutions to problems “ seeking the wisdom of ten people rather than the knowledge of one person” [Kaizen Institute] 25 January 2007 MATS326-3 problem.ppt
  • 4. Brainstorming no criticism is permitted “ only stupid question is one that is not asked” [Ho] wild ideas are encouraged often trigger good ideas from someone else each person contributes one idea further single ideas on second circuit repeat until no further ideas all contributions are recorded in view 25 January 2007 MATS326-3 problem.ppt
  • 5. Brainstorming Osborn proposed 75 fundamental questions can be reduced to:  seek other uses?  adapt? modify?  magnify? minify?  substitute?  rearrange?  reverse?  combine? 25 January 2007 MATS326-3 problem.ppt
  • 6. TRIZ   Teorija Reshenija Izobretatel'skih Zadach loosely translates as Theory of Inventive Problem Solving (TIPS) 40 Inventive Principles 25 January 2007 MATS326-3 problem.ppt
  • 7. 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 25 January 2007 MATS326-3 problem.ppt
  • 8. Mind maps attributed to Tony Buzan classic book “Use Your Head” 25 January 2007 MATS326-3 problem.ppt
  • 9. Mind maps Image from http://www.loanedgenius.com/scrabble_2_letter_words.gif 25 January 2007 MATS326-3 problem.ppt
  • 10. Cause-and-Effect diagrams Cause-and-Effect diagram often referred to as a fishbone diagram or an Ishikawa diagram introduced by Kaoru Ishikawa simple graphical method to record and classify a chain of causes and effects in order to resolve a quality problem 25 January 2007 MATS326-3 problem.ppt
  • 11. 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 25 January 2007 MATS326-3 problem.ppt
  • 12. Cause-and-Effect diagrams I Clarify the object effect a numerical measurement should be established against which subsequent improvement can be judged 25 January 2007 MATS326-3 problem.ppt
  • 13. Cause-and-Effect diagrams II 25 January 2007 MATS326-3 problem.ppt Pick 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
  • 14. Cause-and-Effect diagrams III Determine the priority causes analyse any existing data for the problem if practical, create a Pareto diagram.  otherwise, determine a ranking of the relative importance of each cause. 25 January 2007 MATS326-3 problem.ppt
  • 15. Cause-and-Effect diagrams IV Work out the counteractions for priority causes put in place appropriate solutions to eliminate or reduce the causes of problems 25 January 2007 MATS326-3 problem.ppt
  • 16. Cause-and-Effect diagram: Image from http://www.ifm.eng.cam.ac.uk/dstools/gif/ishika.gif 25 January 2007 MATS326-3 problem.ppt
  • 17. Failures Mode and Effects Analysis FMEA is a useful tool for reliability analysis systematic check of a product or process function failure causes failure modes failure consequences 25 January 2007 MATS326-3 problem.ppt
  • 18. Failures Mode and Effects Analysis Requires a thorough knowledge of functions of the components contribution of those components to function of the system For every failure mode at a low level, failure consequences are analysed at the local level the system level 25 January 2007 MATS326-3 problem.ppt
  • 19. Failures Mode and Effects Analysis FMEA is usually qualitative but may also be quantitative initiated during planning and definition of a project to investigate qualitative reliability demands of the market during design and development, for quantitative reliability activities 25 January 2007 MATS326-3 problem.ppt
  • 20. 25 January 2007 MATS326-3 problem.ppt Table From Evans and Lindsay Chapter 13
  • 21. Failures Mode and Effects Analysis design-FMEA for design reviews definition and limiting of the system choice of complexity level check of component functions check of system functions identification of possible failure modes identification of consequences of failures possibility of failure detection and failure localisation assessment of seriousness of failure identification of failure causes interdependence of failures documentation 25 January 2007 MATS326-3 problem.ppt
  • 22. Failures Mode and Effects Analysis quantitative design-FMEA a.k.a. FMECA Failure Mode, Effects and Criticality Analysis consider every component quantify and rank different failure modes F = probability of failure A = seriousness (consequences of failure) U = probability of detection subjective judgements on a scale of 1-5 or 1-10 Product (F*A*U) = Risk Priority Number (RPN) 25 January 2007 MATS326-3 problem.ppt
  • 23. Failures Mode and Effects Analysis Process-FMEA for pre-production engineering design of process control 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) 25 January 2007 MATS326-3 problem.ppt
  • 24. 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 25 January 2007 MATS326-3 problem.ppt
  • 25. 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 Laboratories then North American Space Industry 25 January 2007 MATS326-3 problem.ppt
  • 26. Fault Tree Analysis Common symbols used 1 main event basic event incompletely analysed event restriction 25 January 2007 MATS326-3 problem.ppt
  • 27. Fault Tree Analysis Common symbols used 2 or-gate and-gate transfer to or from another place 25 January 2007 MATS326-3 problem.ppt &  1 +
  • 28. 25 January 2007 MATS326-3 problem.ppt Figure From Evans and Lindsay Chapter 13
  • 29. Design of Experiments originally conceived by Ronald Aylmer Fisher at Rothampstead Experimental Station during the 1920s analysing plant growing plots under different conditions, and needed to eliminate systematic errors. Image from http://www.csse.monash.edu.au/~lloyd/tildeImages/People/Fisher.RA/ 25 January 2007 MATS326-3 problem.ppt
  • 30. 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 experiments instead of one-factor-at-a-time 25 January 2007 MATS326-3 problem.ppt
  • 31. Design of Experiments full factorial experiment where a number of factors may influence the output of a process, it is possible to study all combinations of levels of each factor if the number of factors considered increases, then number of experiments required increases more rapidly.  25 January 2007 MATS326-3 problem.ppt
  • 32. Design of Experiments For two levels of n-variables, the number of experiments required is 2 n 4 experiments for two variables (low-low, low-high, high-low and high-high) 16 experiments for four variables 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. 25 January 2007 MATS326-3 problem.ppt
  • 33. Design of Experiments 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 . 25 January 2007 MATS326-3 problem.ppt
  • 34. Design of Experiments Genichi Taguchi developed orthogonal arrays fractional factorial matrix permits a balanced comparison of levels of any factor with a reduced number of experiments. each factor can be evaluated independently of each of the other factors.  25 January 2007 MATS326-3 problem.ppt
  • 35. Orthogonal arrays L4: three two-level factors L9: four three level factors Arrays from http://www.york.ac.uk/depts/maths/tables/orthogonal.htm 25 January 2007 MATS326-3 problem.ppt
  • 36. Common orthogonal arrays 25 January 2007 MATS326-3 problem.ppt Table from Tony Bendell “Taguchi Methods”, 1989 Array Levels Equivalent Full Factorial L 4 3 x 2 8 L 8 7 x 2 128 L 9 4 x 3 81 L 12 11 x 2 2 048 L 16 15 x 2 32 768 L 25 6 x 5 15 625 L 27 13 x 3 1 594 323
  • 37. Taguchi Quality Loss Function L(x) = k ( x - t ) 2 L = the loss to society of a unit of output at value x   t = the ideal target value k = constant as non-conformance increases, losses increase even more rapidly 25 January 2007 MATS326-3 problem.ppt