Presentation on theme: "Engineering 1000 Chapter 3: Problem Formulation. Problem 2 R. Hornsey Outline Teams and personalities Mental models Herrmann Brain Dominance Model Whole."— Presentation transcript:
Problem 2 R. Hornsey Outline Teams and personalities Mental models Herrmann Brain Dominance Model Whole Brain Model Knowledge Creation Model Metaphors for creative problem solving personalities Mental blocks to creative thinking lessons from exercises Heuristics for problem formulation statement re-statement present-state desired-state Kepner-Tregoe analysis
Problem 3 R. Hornsey Somewhere in the Middle East, a man owned 17 camels – his entire wealth. He had three children who helped him in his transportation business. While on one of their trips, the father fell ill at an oasis. He called his children to his side and told them his last will: the oldest child was to have half of the camels, the middle child one third of the camels, and the youngest child one ninth of the camels (which represented a fair share of the time each had helped the father in his business). Then the man died. After the burial, the children were faced with the problem of how to divide the camels according to their father’s wishes. The discussion soon centred, rather heatedly on how to kill and cut up some of the camels to come up with the specified shares. At this moment an old man arrived at camp, hungry and thirsty, and with a camel in the same condition. The old man listened to the argument for a while and then offered to solve the dilemma by giving them his camel, if they would provide shelter and food for him for the night. The children agreed. During the night, the oldest child decided he better leave with his share of the camels before the old man – or his siblings – had a change of heart. Later, the middle child awoke, noticed nine camels gone, and hastened to depart with six. In the morning, the youngest child, noting that the others had helped themselves to their inheritance, took the allowed two camels, and bid farewell to the old man with thanks. The old man then resumed his journey with his well-fed and rested camel. Camels What is the real problem here? How do we identify and formulate problems? Creative Problem Solving and Engineering Design, Lumsdaine et al., McGraw Hill 1999
Problem 4 R. Hornsey Problems, Teams, and Personalities Much of engineering (and other business) is now performed in teams so it is not surprising that a lot of research has been performed into what makes teams successful including the development and management of the team, the roles and skills of the members, the personalities of the members, conflict resolution Along with the team management is a personal emphasis how do I learn to be a better team member? and hence to do well at my job To do this, we need to understand basic aspects of our personality so simple and reliable have been developed to indicate basic personality types the most famous is the Meyers Briggs test e.g. http://www.humanmetrics.com/cgi-win/JTypes1.htm
Problem 5 R. Hornsey Advantages and Disadvantages of Teams Advantages wider knowledge and experience is available interaction of people leads to synergy better chance of finding optimal solution team members accept the solution and work better to implement it team members learn from each other encourages development of leadership skills Disadvantages more time and personnel needed to build team team process has low efficiency – lots of ideas but few practical ones team conflict “group think”
Problem 6 R. Hornsey A Good Creative Team What makes a good creative team?
Problem 7 R. Hornsey Mental Models Mental models are tools for aiding problem solving and for understanding why individuals tackle problems in different ways We will look briefly at three concepts the Herrmann brain dominance model knowledge creation creative problem solving
Problem 8 R. Hornsey Herrmann Brain Dominance Model Loosely based on the anatomy of the brain, this technique uses a questionnaire to determine a person’s relative strengths in four ‘quadrants’ http://www.hbdi.com/ A B C D rightleft cerebral limbic rational factual quantitative academic mathematical authoritarian analytical critical realistic logical financial technical dominant organised tactical risk-avoiding conservative administrative scheduled procedural sequential reliable detailed spatial risk-taking holistic play strategic simultaneous imaginative artistic visual conceptual change-oriented big- picture intuitive symbolic teaching expressive reaching-out interpersonal sensitive supportive spiritual feeling musical
Problem 9 R. Hornsey The profile for engineers is typically very strong in quadrant A less strong in B and D weak in C None of the categories is ‘bad’ the idea is to identify your natural strengths and to concentrate on developing your less strong areas with the aim of being equally strong in all areas, i.e. multi-dominant or ‘whole brain’ Engineers with strengths in each category are important e.g. for a bridge construction Atechnical specs, financing, project logistics Blow-risk, efficient work flow, how to build it Cconnecting people, effect on communities and environment, politics Dtraffic projections, different possibilities, aesthetics
Problem 10 R. Hornsey Whole-Brain “Creative Problem Solving and Engineering Design” Lumsdaine et al. McGraw Hill 1999
Problem 11 R. Hornsey In Which Quadrant Are You? Based on the data from the previous page give yourself a score out of 10 for each quadrant note: this is not how the real test is done! When in a team, do you find yourself behaving according to your dominant quadrant? do you see others displaying other quadrants? do you see their contributions as valuable to the team?
Problem 12 R. Hornsey Knowledge Creation Model How can the whole-brain model be extended to give an understanding of the innovation process? in “Creative Problem Solving and Engineering Design” Lumsdaine et al. combine the whole-brain approach with lessons for innovation drawn from Japanese companies The idea is that knowledge is created as we move from one quadrant of the Herrmann diagram to the next It is important here to identify two types of knowledge Explicit knowledge “hard” knowledge that can be expressed in formulae, descriptions, instructions, diagrams it can be transmitted readily by manuals, documents etc. Tacit knowledge ‘know-how’, experience, intuition, craft, skill tacit knowledge must be transmitted by interaction and personal instruction
Problem 13 R. Hornsey The combined knowledge creation diagram identifies four stages socialization: shared vision, corporate culture externalization: discussions and brainstorming combination: analysis and evaluation of concepts internalization: learning and integrating the new knowledge “Creative Problem Solving and Engineering Design” Lumsdaine et al. McGraw Hill 1999
Problem 14 R. Hornsey You can see similarities/connections with the design process itself the levels of failure from Ch.2
Problem 15 R. Hornsey Example – Oakland Bay Bridge Completed in 1936 ahead of schedule and within budget Early History Soc. Public discussion and increasing traffic needs after WW1. Extern. 38 proposals and design concepts by 1928. Comb. Board of 3 distinguished engineers recommends analysis of preferred site for more detailed design and cost estimates. benefits of bridge versus tunnel. Intern. Focus on bridge failures with large cantilever designs. Bridge Authority Soc. Political efforts underway Extern. Creating a publicly-owned facility Comb. Financing, appointment of state highway engineer, boring and analysis of potential sites Intern. Detailed traffic studies, best route, California Toll Bridge Authority Bridge Design Soc. Many engineers and consultants work together, port expansion wishes accommodated Extern. Intensive design work on many designs, scenic beauty a factor Comb. Engineering experience and judgement play key roles in narrowing down design possibilities. Switch from cantilever to suspension bridge on San Francisco section for economic, safety and aesthetic reasons. Intern. Model testing carried out because multiple-span suspension bridge was a new concept
Problem 16 R. Hornsey http://www.lib.berkeley.edu/Exhibits/Bridge/bb_ce006.html
Problem 17 R. Hornsey Metaphors for Creative Problem Solving So far, we have considered the thought processes and dynamics of knowledge creation now we consider the ‘mind-sets’ required at each stage of the process These mind-sets can be conveniently though of in terms of fictitious personalities these are the roles required during the different phases of the knowledge creation process ‘Explorer’ is needed to seek out new ideas and to see the opportunities presented by the big picture ‘Detective’ performs a more detailed analysis of the situation problem formulation typically ends after these two roles ‘Artist’ generates creative and imaginative ideas but may not analyse them critically
Problem 18 R. Hornsey ‘Engineer’ shapes the creative ideas into something more practical, examine the technical issues, optimisation ‘Judge’ identifies flaws in the solutions proposed and works with the ‘artist’ and ‘engineer’ to overcome them ‘Producer’ puts it all together to come out with a good product, i.e. solves the problems of implementation may be the project sponsor higher up in the organisation Without any one of these personalities, a critical element of the problem-solving team is absent These personalities fit with the Herrmann diagram and the knowledge creation cycle as shown on the next page
Problem 19 R. Hornsey “Creative Problem Solving and Engineering Design” Lumsdaine et al. McGraw Hill 1999
Problem 20 R. Hornsey Mental Blocks to Creative Thinking There are three common barriers to creative thinking false assumptions habitual thinking attitude barriers From the following list, choose who you think is the most creative group of people NASA engineers, high school teachers, homemakers, college students, first graders, journalists, movie producers, abstract painters, auto mechanics Creativity is more a matter of environment than profession
Problem 21 R. Hornsey “An intelligent mind is a good thinker” … ? Not necessarily; untrained intelligent people may be poor thinkers for a number of reasons they can create a good justification for any point of view and do not see the need to explore alternatives they confuse verbal fluency for good thinking their mental quickness leads them to jump to conclusions they think that quick thinking is good understanding they use intelligence to criticise rather than construct Other valuable attributes play humour what if …?
Problem 22 R. Hornsey Exercises 1a. Which of these figures is different from the rest? Why? Reason: 1b. An army must move some soldiers to a different location. If a maximum of 39 soldiers and their gear fit into a bus, how many buses are needed to move 1261 soldiers? (a) 31(b) 32(c) 32.33(d) 33(e) 34 Answer: 2. How many squares are there? �
Problem 23 R. Hornsey 3a. Join all the dots with 4 straight lines with no more than one line through any dot 3b. Sketch a path from A to B
Problem 24 R. Hornsey 4. What do you see below?
Problem 25 R. Hornsey 5a. What do you see? 5b. Can you find all 9 people? http://www.grand-illusions.com/
Problem 26 R. Hornsey Bad Habits Exercise 1a & 1b it is possible to make a good case for any shape being the odd one out hence the question is too vague Block 1:there is more than one correct answer Corollary to exercise 1 in order to know the best answer of those we have, we must look at the context Block 2: do not look at the problem in isolation Exercise 2 the simple answer is that there are 17 squares but this is limited thinking, e.g. it assumes that the picture is 2-D; what happens if this is looking at the top of a column of blocks? Exercises 3a & 3b ‘thinking outside the box’ Block 3: following the “rules”
Problem 27 R. Hornsey Exercise 4 – to check progress chances are you answered “a black dot” possibly “a rectangle containing a black dot” in fact ~ 95% of the rectangle is white space! Exercise 5a & 5b shows ambiguous images; can you see both images interchangeably? Block 4: discomfort with ambiguity very little in life is 100% clear – including ENG1000 assignments Attitudinal blocks Block 5: risk avoidance/fear of failure “if you never fail, you’re not reaching far enough” Block 6: negative thinking “it’ll never work …”
Problem 28 R. Hornsey Problem Formulation Following our knowledge creation cycle, the ‘explorer’ and then the ‘detective’ personalities are appropriate for problem formulation Problem formulation (or problem definition) is needed to ensure everyone realises that there is a problem and to specify the real problem On the following page, we see how the two personalities approach the same issues
Problem 29 R. Hornsey “Creative Problem Solving and Engineering Design” Lumsdaine et al. McGraw Hill 1999
Problem 30 R. Hornsey The Explorer The ‘explorer’ personality is used for divergent thinking quadrant D thinking taking the far view spotting trends predicting the future How you become a trend spotter? be selective about information you take in read articles that contain ideas talk to people have broad-ranging interests synthesise ideas (i.e. think!) observe what is around you ask questions identify how things change over time find opportunities http://www.angelfire.com/me/jakub/indy/
Problem 31 R. Hornsey The Detective In contrast to the ‘explorer’, the ‘detective’ specialises in convergent thinking quadrant B personality looks for root causes accumulates information, surveys, data who, what, when, where, why, how much? Kepner-Tregoe approach (see later) explicit and tacit knowledge persistent http://www.sherlock-holmes.org.uk
Problem 32 R. Hornsey Heuristics A heuristic technique is essentially a trial and error approach a number of options are generated and the best is selected a try-it-and-see experimental approach a rule of thumb We will look at several heuristic approaches to problem definition statement re-statement source and cause revision method present state and desired state Kepner-Tregoe situation analysis Remember that these (and the methods we have already discussed) are merely aids for thinking not guaranteed to produce good results
Problem 33 R. Hornsey Statement Re-statement Technique This approach aims to promote a better understanding of a problem by stating and re-stating the problem in different ways hence focusing in on the problem The statement re-statement technique consists of four parts for which we assume there is a problem statement of some sort already in existence 1. Determine the real problem this can be done by rewriting the problem statement to see what solutions are triggered see next page 2. Determine actual constraints and boundaries sometimes the perceived constraints are tougher than the real ones in the problem statement, relax the constraints to see if it has changed in a significant way; if not the original constraints were too tough e.g. car >500km/h replaced by car > 200km/h e.g. “lowest price” replaced by “affordable”
Problem 34 R. Hornsey RestatementDescriptionIncrease the number of commuters who use the TTC Vary the emphasisHas the focus of the problem itself changed? How? Is it a better statement? Increase: decrease fares? Make more convenient Commuters: advertise benefits of TTC to commuters TTC: bus lanes, subway to York Substitute explicit definitions Is the problem statement clearer and more precise? In what way? Why? Commuter ‘people travelling to work each day’: encourage employers to reward TTC users. TTC trains/buses: make working easier on trains/buses Change positives to negatives and vice versa Reverse the statement. Instead of how to make the car faster, ask what slows the car down. Reduce the number of commuters:why don’t more people use TTC? Fix reasons. Replace persuasive and/or implied words Where ‘obviously’ or ‘clearly’ occur, examine the reasoning. If reasoning is flawed, what effect will this have? Underlying reasoning is that by increasing TTC ridership, we reduce number of private cars, pollution etc. i.e. number of commuters is constant. Promote telecommuting instead.
Problem 35 R. Hornsey 3. Prioritise goals as we saw in Ch.2, not all objectives are equally important satisficing 4. Link outputs to inputs determine what transforms inputs (raw materials, people, money) into outputs (the desired benefits of the design) are any stages of the transformation process missing? are any stages unpredictable? What would you do about them? re-state problem statement to reflect what is known, unknown, desired, and unpredictable
Problem 36 R. Hornsey Present State and Desired State An alternative heuristic approach to problem definition is to focus on the present and desired states by manipulating statements of the present state (PS) and the desired state (DS) we aim to make a clear correlation between the two PS: too many commuters use private cars DS:less traffic PS: too many commuters use private cars because there is no viable alternative DS: less traffic PS: too many people use private cars because they must commute and they don’t take public transport DS: we need to reduce commuting by private car PS: too many people use private cars because they must commute and they don’t take public transport DS:people should be encouraged to reduce their commute or take public transport PS: too many people use private cars because they must commute and they don’t take public transport DS:people allowed to work closer to/at home or public transport should be made attractive
Problem 37 R. Hornsey How would this sequence have been different if the DS had been “reduced pollution”? The PS/DS approach can be expressed diagrammatically in the so-called Duncker diagram “Engineering by Design” G. Voland, Addison Wesley, 1999
Problem 38 R. Hornsey This is very similar to the objectives and functions trees we saw in Ch.2 except that the aim is to start from the PS and DS and work from both ends it enables both more complex and multiple statements to be included simultaneously
Problem 39 R. Hornsey Kepner–Tregoe Analysis In their 1981 book “The New Rational Manager” Kepner and Tregoe developed a four-step problem solving approach Situation Analysis (SA): critical aspects first Problem Analysis (PA): what past event may have caused problem? Decision Analysis (DA): what actions are needed to correct problem? Potential Problem Analysis (PPA): how to prevent further problems? SA and PA are relevant here DA and PPA are used later in the design process Kepner-Tregoe is now a large management consulting and strategy company http://www.kepner-tregoe.com This analysis is primarily intended for engineering problems in progress but can aid in structuring the search for the real problem in any design process
Problem 40 R. Hornsey Situation Analysis (SA) The current situation is analysed according to three criteria timing: which is the most urgent problem? trend: is the problem getting better or worse? how quickly? impact: what are the consequences of the problem being left unsolved? For each problem and sub-problem, each criterion is given a high, medium, or low ranking of importance see example from p.90 of Engineering by Design (reproduced here for convenience)
Problem 41 R. Hornsey Example – The Water Tank Disaster The following news story is based on the Nassau edition of Newsday, the Long Island, N.Y., newspaper (April 24, 1981 ) and OPLOW, American Water Works Association, vol.7, no.6,June 1981, p.3. Inadequate safety precautions and an accident inside an empty water tank caused the deaths of two workmen in New Jersey on April 23. At 4 P.M., a scaffold inside the tank collapsed and caused the two men painting the tank to fall to the bottom. Stranded there, they were overcome by paint fumes and eventually lost consciousness. John Bakalopoulos, 34, of Brooklyn, N.Y., and Leslie Salomon, 31, also of Brooklyn, were not wearing oxygen masks. The Suffolk County Water Authority's contract for the painting job specified that workmen wear "air hoods," masks connected to air compressors. The masks were available, but Bakalopoulos and Salomon had decided not to wear them because they were unwieldy. Instead, Bakalopoulos wore a thin gauze mask designed 4to filter out dust and paint particles. Salomon wore no mask. Peter Koustas, the safety man who was handling the compressor and paint feed outside the tank, asked a nearby resident to call firemen [sic] as soon as he realized the scaffold had collapsed. Then he rushed into the tank with no oxygen mask, and he, too, was overcome by the fumes and lost consciousness. The men lay unconscious for hours as rescue efforts of more than 100 policemen, firemen, and volunteers were hampered by bad weather. Intense fog, rain, and high winds made climbing the tank difficult and restricted the use of machinery. Several men collapsed from fatigue.
Problem 42 R. Hornsey Inside the tank, conditions were worse. Because of the heavy fumes, rescuers used only hand-held, battery-powered lights, fearing that sparks from electric lights might cause an explosion. Lt. Larry Viverito, 38, a Centereach, N.Y,. volunteer fireman, was overcome by fumes 65 ft (20 m) above the floor of the tank. Fellow rescuers had to pull him out. Rescuer John Flynn, a veteran mountain climber, said he hoped he would never have to go through anything like that night again. For five hours he set up block-and-tackle pulleys, tied knots, adjusted straps on stretchers, and attached safety lines and double safety lines. The interior of the tank was as blindingly white as an Alpine blizzard— completely and nauseatingly disorienting. Fans that had been set up to pull fresh air into the tank caused deafening noise. When Flynn first reached the tank floor, he stepped into the wet paint and began to slide toward the uncovered 4-ft (1.2 m) opening to the feeder pipe in the center of the floor. Flynn was able to stop sliding, but John Bakalopoulos wasn't as fortunate. As rescuers watched helplessly, Bakalopoulos, still out of reach, stirred, rolled over, and in the slippery paint slid into the feeder pipe. He plunged 1 10 ft (34 m) to the bottom. Bakalopoulos was dead on arrival at the University Hospital in Stony Brook, N.Y., Peter Koustas, rescued at 1:45 A.M. and suffering from hypothermia, died the following morning when his heart failed and he could not be revived. Only Leslie Salomon survived.
Problem 43 R. Hornsey Although there may be additional concerns that could be identified (such as rescue expenses and the subsequent use of the water tank), let us assume that Table 3.2 includes the major elements of the problem. A review of the priorities given to each subconcern indicates that "paint fumes" received high levels of concern in all three categories (timing, trend, and impact) for both paint crew members and their rescuers. Therefore, we should initially focus on this most urgent aspect of the situation. This first step in Kepner-Tregoe analysis further requires that we classify each aspect of a situation into one of three categories, corresponding to the next step (problem analysis, decision analysis, or potential problem analysis) to be performed in resolving the problem. In the case of the water tank problem, since we already know the cause of the paint fumes (the paint itself), Kepner-Tregoe problem analysis is unnecessary; we would move directly to decision analysis (see Chapter 10 of text) and strive to eliminate the need for painting the tank. From “Engineering by Design” G. Voland, Addison Wesley, 1999
Problem 44 R. Hornsey Problem Analysis (PA) SA aids our determination of which problem(s) to tackle first problem analysis assist our thinking for a specific sub-problem PA asks the following questions what is the problem? – and what is not? when did the problem occur – and when did it not? where did the problem occur? – and where did it not? what is the extent of the problem? [much of this seems like common sense, but it helps to have a structure to follow in instances of duress – like drilling soldiers] These key considerations are summarized as identity, location, timing, magnitude The aim is to determine why there is a difference between ‘is’ and ‘is not’, between positive and megative
Problem 45 R. Hornsey “Engineering by Design” G. Voland, Addison Wesley, 1999
Problem 46 R. Hornsey Example - Electronics Manufacture An electronics manufacturing company is involved in the demanding task of producing miniaturized printed circuitry. One day, the production quality fell off sharply and the number of rejected circuits skyrocketed. "Why?" demanded the boss. "Why?" echoed his subordinates. "Temperature in the leaching bath is too high," said one technician. So temperatures were lowered. A week later, when rejects climbed still higher, temperatures were raised, then lowered again, then systematically varied up and down for days. Rejects remained astronomical. "Cleanliness is not what it should be. That's what's causing the trouble," someone offered. So everything was scrubbed, polished, filtered, and wiped. The rejects dropped, then rose again. Acid concentration was the next idea. Same results. Water purity was checked out on Wednesday, Thursday, and Friday. The possibility of oil transferred from the operator's fingertips received full scrutiny on the following Monday and Tuesday. Rejects still were high. They might have remained high had not one supervisor begun to ask systematic questions. "What is wrong with the rejected pieces?" This produced the information that the acid leaching step of the printed circuit pattern was occurring unevenly as if some waterborne contaminant in the leaching solution was inhibiting the action. "When does it occur?" A check of the records showed that rejects were at their highest on Monday mornings, lower on Monday afternoons, and gone by noon on Tuesday.
Problem 47 R. Hornsey This cast a different light on everything. Now nobody was asking "Why?" about the cause of a general, ill-defined deviation. Instead they focused on what was distinctive about Monday mornings compared with the rest of the week. They focused on what might have been changed that bore a relationship to this timing. An immediate distinction was recognized: "Monday morning is the first work period following the non- work period of the weekend." And what changed on Monday morning? On each Monday, as soon as the tap was turned, water that had stood in the lines over the weekend came into the printed circuit leaching laboratories. The water used in the process had to go through intensive purification, since purity standards of a few parts per-billion are required. A quick search turned up the fact that some valves had been changed several months before. These valves used a silicone packing material. As water stood in the lines over the weekend, enough of this silicone packing material had begun to diffuse into the water and degrade the leaching process. The result? Many rejections on Monday morning, fewer in the afternoon, and none after Tuesday noon. By then the contaminated water had been purged from the system. From “The New Rational manager”, C. Kepner and B. Tregoe, Princeton Research Press, 1981.
Problem 48 R. Hornsey Summary A good problem definition is necessary for a good design or solution Understanding of thinking preferences and elimination of poor thinking techniques assists the process Using metaphors can help to adopt the necessary approaches to the problem Certain techniques (heuristics) can assist in the process of formulating the problem
Problem 49 R. Hornsey Homework Read and understand Chapter 3 of the text book Read the case studies Do problem 3.7
Problem 50 R. Hornsey Exercise – Leaking Oil Our client is a major food processor. One of the company plants produces oil from corn and soybeans. The five units that filter the oil are located in one building. On the day the problem was first observed, a foreman rushed into his supervisor's office: "Number One Filter is leaking. There's oil all over the floor of the filter house." The foreman guessed that the leak was caused by valves loosening up from vibration. This had happened once before. "Number One sits right next to the main feedwater pump and gets shaken up more than the other four filters." A mechanic tried to find the leak but couldn't tell much because the oil had already been cleaned up. The lid fastener looked all right. After examining pipes, valves, and the walls of the filter chamber, the mechanic concluded that the oil had spilled from another source. The next day there was more oil. Another mechanic traced the leak to the cleanout hatch but that didn't help much. Why should the cleanout hatch leak? It looked perfectly all right. Just to be on the safe side, he replaced the gasket even though it looked new. The hatch continued to leak. "Maintenance people just aren't closing it tight enough after they clean it out," someone volunteered. "There are a couple of new guys on maintenance here since the shifts were changed around last month. I wonder if they're using a torque wrench like they're supposed to. This happened to us once before because somebody didn't use a torque wrench." No one could say for sure. Apply Kepner-Tregoe analysis (SA and PA) to determine the priorities and possible causes of the following problem
Problem 51 R. Hornsey The next day an operator slipped on the oil-slick floor and hurt his back. The cleanup task was becoming more than irksome, according to some outspoken comments overheard by the foreman. A few people began grumbling about promises made at the last safety meeting about improving conditions in the filter house. Two days later the plant manager got wind of the situation, called in the supervisor and the foreman, and made it clear that he expected a solution to the oil mess problem within the day. From “The New Rational manager”, C. Kepner and B. Tregoe, Princeton Research Press, 1981.