Adonis Diaries

Posts Tagged ‘error taxonomies

Daydream project: Restructuring engineering schools and practices…

Technological breakthroughs are exhibiting their medium-term harms: We are at the beginning phase for experiencing the benefits and harms of technologies that we can invent and produce, but do not comprehend or grasp the consequences.

We are traversing a dangerous period without adequate check and balance on the production of new inventions, and are tampering with human genome and agricultural and animal cloning: The consequences might be irreversible this time around on our survival.

We have created enough tools, processes, and know-how to invent all kind of products without the need of thorough theoretical foundations.  It is like a machine that invents new machines with what it already knows. The vast array of tools technology has in its arsenal is driving more technologies:  Theory is becoming an after thought.  Since science requires a rational model, the fast pace of technological inventions decided it can do without theory or rational models .

Experiments require plenty of time, financial and human resources in order to validate and test the consequences of new technological products on human health, and safe usage. The backlog for long-term testing is stretching long, particularly initiated when consumers lodge complaints and file legal suits, and health and safety evaluations can never catch up with what is thrown in the market place.

For example, developed States have realized that a process for testing and validating the consequences of pharmaceutical products before marketing was a must to safeguard health and safety of the consumers; but even that process was not adequate enough or ethically stringently applied when pharmaceutical new products were tested in the third world populations.

Technology is the new metaphysical ideology for defining youth:  You are as young as you can keep up with new updates.  How fast and how readily you can manipulate and use new gadgets is the main criterion for youthfulness, for keeping your membership in the new cult.

The technology cult means that you should have faith in what the market is providing you in updates and inventions, because ultimately, it is you, the kid, the youth who is testing, validating and selling the technology at your own risk.

Technology is basically a cultural revolution against abstract or theoretical works, whether in religion, metaphysics, or sciences. The motto in the technology circles is : “There is no good or evil in technology. Let us keep inventing and let the less expensive and quicker trial and error methods sort out what is beneficial to mankind.  Let youth, these flexible and adaptable mind, these spiritually and culturally ignorant spirits, and these energetically undaunted and bold souls, be our guinea pigs as they used to be historically”.

Mind you that “corporation universities” are surpassing traditional universities and retraining graduates to specific technological fields, sort of hand-on the main business products or services.  Basically, corporation universities are sending the message that the baggage of knowledge of graduates is not appropriate for this fast technology innovation, and fast turn-over of new products.

What of this new “knowledge slavery” of keeping graduate students in a state of training and retraining positions in order to saving money on hiring new personnel and professionals? For more details read https://adonis49.wordpress.com/2011/06/17/how-long-have-you-graduated-are-you-still-in-training/

For all the above reasons, it is becoming urgent to rethink how engineering schools are structured.

First of all, since engineering is fundamentally a design field for mankind, the main goal for designing and redesigning objects, systems, and services is to focus on the health, safety, and dangerous malfunctions of any product sold to consumers. The design process is to cater to the target users, and also to the eventual usage of other people not trained or aware of the warnings.

It is necessary that first year engineers and designers (graphic designers, architects…) be conversant with the consequences of designing any product and the various testing and evaluation procedures of the extent to which any design might harm and injure clients.

Learning the different error taxonomies and the research studies on human behaviors when exposed to new objects and systems are a must for any engineer.

Second year engineers should be methodically taught the various experimental designs, and not wait for graduate programs to brush on this highly important field of designing experiments. This idea that the theories behind design are sacrosanct and need not be revisited is a dangerous concept: We need not live with the illusion that we do know how the natural world function.  Critical innovations are generated by revisiting old theories and practices through more experimentation perspectives.

Mind you that people live under different cultures, customs and idiosyncracies, and the designer first task is to be knowledgeable of the culture of the customers. “Good design captures and takes control of every interface and interaction between the consumer and the brand, right down to the tiniest details, from opening to closing of the package…” Grant McCraken

Any engineering research study must be explicit on how the data, results, and recommendations can be applicable in design projects for the health, safety, and comfort of users and operators.

Reflecting again: On design errors in human-machine interfaces

Note:  I occasionally edit, translate, and re-publish articles that I deem them worth disseminating: Worthy articles are meant to be read.

Matthew Squair posted this May:  “Having recently bought a new car, I was driving home and noticed that the illuminated lighting controls were reflected in the right hand wing mirror. These sort of reflections are at best annoying, but in the worst case ,they could mask the lights of a car in the right hand lane and lead to a side-swipe during lane changing.

This is one of the classic system design errors that is well understood in domains such as the aerospace field.   Not so much in the car industry apparently.

But what really interests me is the fractured nature of engineering knowledge that this problem illustrates. I guess there is an implicit assumption we make that “we’re all getting smarter”.  But if that’s the case, why are the same errors committed over again?

Henry Petroski points to a study by Silby (1977) of bridge failures:  The study shows a 30 year-cycle between major bridge collapse and posits that, in any technology, we go through a cycle of learning, mastery, overconfidence, and subsequent failure due to over reach.

I’d point to the fragility of corporate memory within organizations and design teams:  I recognize that in the current  environment of rapid organizational change, it’s extremely hard to provide mentoring and oversight for young engineers, who unfortunately “don’t know what they don’t know“!

This remorseless cycle of destruction is exacerbated by codes and standards that record ‘what’ must be done from a compliance standpoint, but not the why”  Without the reason for compliance there is always the temptation…

I do agree with Petroski that failure breeds reflection, insight, and knowledge and that engineers, (especially young engineers), need in many ways to experience failure themselves or learn through the failures of others.

Evaluations of cockpit transparencies for reflections are required as part of the development of a new aircraft. These effects are particularly a problem for fighter aircraft with a large curved canopies and where the pilots’ displays sit comparatively close to the canopy.” (End of quote)

I have published over 30 articles on wordpress.com related to Human factors in design.

Human Factors professionals attempted to establish various error taxonomies, some within a specific context, during their study and analysis of errors that might be committed in the operation of nuclear power plants for example, and other taxonomy that are out of any specific context.

One alternative classification of human errors is based on human behavior and the level of comprehension; mainly, skill-based, or rule-based or knowledge-based behavioral patterns. This taxonomy identifies 13 types of errors and discriminates among the stages and strength of controlled routines in the mind that precipitate the occurrence of an error, whether during execution of a task, omitting steps, changing the order of steps, sequence of steps, timing errors, inadequate analysis or decision making.

With a strong knowledge of the behavior of a system, provided that the mental model is not deficient then, applying the rules consistently most of the errors will be concentrated on the level of skill achieved in performing a job.

Another taxonomy rely on the theory of information processing and it is a literal transcription of the experimental processes; mainly, observation of a system status, choice of hypothesis, testing of hypothesis, choice of goal, choice of procedure and execution of procedure.  Basically, this taxonomy may answer the problems in the rule-based and knowledge–based behavior.

It is useful to specify in the final steps of taxonomy whether an error is of omission or of commission.  I suggest that the errors of commission be also fine tuned to differentiate among errors of sequence, the kind of sequence, and timing of the execution.

There are alternative strategies for reducing human errors by either training, selection of the appropriate applicants, or redesigning a system to fit the capabilities of end users and/or taking care of his limitations by preventive designs, exclusion designs, and fail-safe designs.

You may start with this sample of two posts:

1. https://adonis49.wordpress.com/2008/10/14/whats-that-concept-of-human-factors-in-design-5/, and 2. https://adonis49.wordpress.com/2008/10/26/multidisciplinary-view-of-design/

Note 1: Petroski, H. Success through failure: The paradox of design, Princeton Press, 2008.

Note 2: Sibly, P.G., Walker, A.C., Structural Accidents and their Causes. In: Proc. Inst. Civil Engineers. 62 (May 1977), pp. 191–208 part 1. 1977.

 

Article “31 (December 18, 2005)

 “A seminar on a multidisciplinary view of design”  

The term “designing” is so commonly used that its all encompassing scope has lamentably shrunken in the mind of graduating engineers. This talk attempts to restore the true meaning of design as a multidisciplinary concept that draw its value from the cooperation and inputs of many practitioners in a team.

This is a scenario of a seminar targeting freshmen engineers, who will ultimately be involved in submitting design projects, is meant to orient engineers for a procedure that might provide their design projects the necessary substance for becoming marketable and effective in reducing the pitfalls in having to redesign. The ultimate purpose is to providing the correct designing behavior from the first year.

Answering the following questions might be the basis of acquiring a proper behavior in design projects, which should be carried over in their engineering careers.  Many of these questions are never formally asked in the engineering curriculum.

Q1. What is the primary job of an engineer?   What does design means?  How do you perceive designing to look like?

A1. The discussion should be reopened after setting the tone for the talk and warming up the audience to alternative requirements of good design.

Q2. To whom are you designing?  What category of people? Who are your target users? Engineer, consumers, support personnel, operators?

A2. Generate from audience potential design projects as explicit examples to develop on that idea.

Q3. What are your primary criteria in designing?  Error free application product? Who commit errors?  Can a machine do errors?

A3.  Need to explicitly emphasize that error in the design and its usage is the primary criterion and which encompass the other more familiar engineering and business criteria

Q4. How can we categorize errors?  Had you any exposure to error taxonomy? Who is at fault when an error is committed or an accident occurs?

A4. Provide a short summary of different error taxonomies; the whole administrative and managerial procedures and hierarchy of the enterprise need also to be investigated.

Q5. Can you foresee errors, near accidents, accidents in your design?

A5. Take a range oven for example, expose the foreseeable errors and accidents in the design, babies misuse and the display and control idiosyncrasy.

Q6. Can we practically account for errors without specific task taxonomy?

A6. Generate a discussion on tasks and be specific on a selected job.

Q7. Do you view yourself as responsible for designing interfaces to your design projects depending on the target users? Would you relinquish your responsibilities for being in the team assigned to designing an interface for your design project? What kinds of interfaces are needed for your design to be used efficiently?

A7. Discuss the various interfaces attached to any design and as prolongement to marketable designs.

Q8. How engineers solve problems?  Searching for the applicable formulas? Can you figure out the magnitude of the answer?  Have you memorized the allowable range for your answers from the given data and restriction imposed in the problem after solving so many exercises? Have you memorize the dimensions of your design problem?

A8.  Figure out the magnitude and the range of the answers before attempting to solve a question; solve algebraically your equations before inputting data; have a good grasp of all the relevant independent variables.

Q9. What are the factors or independent variables that may affect your design project? How can we account for the interactions among the factors?

A9. Offer an exposition to design of experiments

Q10. Have you been exposed to reading research papers? Can you understand, analyze and interpret the research paper data? Can you have an opinion as to the validity of an experiment? Would you accept the results of any peer reviewed article as facts that may be readily applied to your design projects?

A10.  Explain the need to be familiar with the procedures and ways of understanding research articles as a continuing education requirement.

Q11. Do you expect to be in charged of designing any new product or program or procedures in your career? Do you view most of your job career as a series of supporting responsibilities; like just applying already designed programs and procedures?

Q12. Are you ready to take elective courses in psychology, sociology, marketing, business targeted to learning how to design experiments and know more about the capabilities, limitations and behavioral trends of target users? Are you planning to go for graduate studies and do you know what elective courses might suit you better in your career?

A12.  Taking multidisciplinary courses enhances communication among design team members and more importantly encourages reading research papers in other disciplines related to improving a design project. Designing is a vast and complex concept that requires years of practice and patience to encompass several social science disciplines.

Q13. Can you guess what should have been my profession?

A13.  My discipline is Industrial engineering with a major in Human Factors oriented toward designing interfaces for products and systems. Consequently, my major required taking multidisciplinary courses in marketing, psychology and econometrics and mostly targeting various methodologies for designing experiments, collecting data and statistically analyzing gathered data in order to predict system’s behavior.

 

What are error taxonomies, and other taxonomies in Human Factors in Engineering?

Article #12, written in April 9, 2005)

May you allow me just a side explanation on experimentation, to set the foundations first?

Psychologists, sociologists and marketing graduates are trained to apply various experimentation methods and not just cause and effect designs.

There are many statistical packages oriented to providing dimensions and models to the set of data dumped into the experiment, so that a preliminary understanding of the system behavior is comprehended qualitatively.

Every applied science has gone through many qualitative models or schema, using various qualitative methods, before attempting to quantify their models.

Many chairmen of engineering departments, especially those who have no understanding of the disciple of Human Factors in engineering and would never touch this body of knowledge and methods with a long pole, ask me to concentrate my courses on the quantitative aspects.

That hint sends immediate shiver through my rebellious spirit and I am tempted to ask them “what taxonomy of methods are you using in teaching engineering courses?”

What taxonomies Human Factors have to conceive?  How about the classification of human errors when operating a system, their frequencies and consequences on the safety of operators and system performance?

Human Factors professionals attempted to establish various error taxonomies, some within a specific context, during their study and analysis of errors that might be committed in the operation of nuclear power plants for example, and other taxonomy that are out of any specific context.

One alternative classification of human errors is based on human behavior and the level of comprehension. Mainly, skill-based, or rule-based or knowledge-based behavioral patterns.

This taxonomy identifies 13 types of errors and discriminates among the stages and strength of controlled routines in the mind that precipitate the occurrence of an error, whether during execution of a task, omitting steps, changing the order of steps, sequence of steps, timing errors, inadequate analysis or decision-making.

With a strong knowledge of the behavior of a system, provided that the mental model is not deficient, applying the rules consistently most of the errors will be concentrated on the level of skill achieved in performing a job.

Another taxonomy rely on the theory of information processing and it is a literal transcription of the experimental processes; mainly, observation of a system status, choice of hypothesis, testing of hypothesis, choice of goal, choice of procedure and execution of procedure.  Basically, this taxonomy may answer the problems in the rule-based and knowledge–based behavior.

It is useful to specify in the final steps of taxonomy whether an error is of omission or of commission.  I suggest that the errors of commission be also fine tuned to differentiate among errors of sequence, the kind of sequence, and timing of the execution.

There are alternative strategies for reducing human errors by either training, selection of the appropriate applicants, or redesigning a system to fit the capabilities of end users and/or taking care of his limitations by preventive designs, exclusion designs, and fail-safe designs.

What’s that concept of Human factors in Design? (Started these articles in 2003

 What is this Human Factors profession?

 Article number                                                                                               

1.  “What is your job?”                                                                                                  

2.  “Sorry, you said Human Factors in Engineering?”                                                

3.  “So, you want systems to fit people?”                                                                   

4.  “The rights of the beast of burden; like a donkey?”                                              

5.  “Who could afford to hire Human Factors engineers?”                             

6.  “In peace time, why and how often are Human Factors hired?                    

7.  “What message should the Human Factors profession transmit?”                          

8.  “What do you design again?”                                                                                         

9.  “Besides displays and controls, what other interfaces do you design?”                 

10.  “How Human Factors gets involved in the Safety and Health of end users?”    

11.  “What kind of methods will I have to manipulate and start worrying about?” 

12.  “What are the error taxonomies in Human Factors?”                                 

13.  “What are the task taxonomies and how basic are they in HF?”                           

14.  “How useful are taxonomies of methods?”                                                               

15.  “Are occupational safety and health standards and regulations of any concern for the HF professionals?”                                                                                                       

16.  “Are there any major cross over between HF and safety engineering?”            

17.  “Tell us about a few of your teaching methods and anecdotes”                            

18.  “What this general course in Human Factors covers?”                                         

19.  “Could one general course in Human Factors make a dent in a career behavior?”                                                                                                                     

20.  “How would you like to fit Human Factors in the engineering curriculum?”  

21.  “How to restructure engineering curriculum to respond to end users demands?”

22.  “How can a class assimilate a course material of 1000 pages?”                             

23.  “What undergraduate students care about university courses?”                            

24.  “Students’ feedback on my teaching method”                                              

25.  “My pet project for undergraduate engineering curriculum”                      

26.  “Guess what my job is”                                                                                              

27.  “Do you know what your folk’s jobs are?”                                                              

28.  “How do you perceive the inspection job to mean?”                                               

29.  “How objective and scientific is a research?” 

30.  “How objective and scientific are experiments?”                                                   

31.   “A seminar on a multidisciplinary view of design”                                                  

32.  “Consumer Product Liability Engineering”                                                                 

33.  “How could you tell long and good stories from HF graphs?”                               

34.  “What message has the Human Factors profession been sending?”       

35. “Who should be in charge of workspace design?”                                                  

36.  “Efficiency of the human body structure and mind”                                                

37.  “Psycho-physical method”                                                                                       

38.  “Human factors performance criteria”                                                      

39.  “Fundamentals of controlled experimentation methods”                                      

40.  “Experimentation: natural sciences versus people’s behavior sciences”            

41.  “What do Human Factors measure?”                                                                   

42.  “New semester, new approach to teaching the course”                                       

43.  “Controlled experimentation versus Evaluation and Testing methods”               

44.  “Phases in the process of system/mission analyses”                                             

45.   “Main errors and mistakes in controlled experimentations”                   

46.  “Human Factors versus Industrial, Computer, and traditional engineering” 

47.  “How Human Factors are considered at the NASA jet propulsion laboratory”

48.  “Efficiency of the human cognitive power or mind”                                               

49.  “Human Factors versus Artificial Intelligence”                                                     

50.  Computational Rationality in Artificial Intelligence                                               

51.  “Basic Engineering and Physics Problems Transformed Mathematically”     

52.  Mathematics: a unifying abstraction for Engineering and Physics                        

53. How to optimize human potentials in businesses for profit                                      

 


adonis49

adonis49

adonis49

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