Adonis Diaries

Posts Tagged ‘Human Factors in design

Design: Got necessarily be evidence-based. Design is basically relevant to a human factors need

Note: Finally, an article that explicitly mentions Human Factors in Design

Dr Dan Jenkins leads the human factors and research team at DCA Design International, working on a range of projects in domains including medical, transport, consumer goods and industrial products.

Lisa Baker is a Chartered Ergonomist of the CIEHF and senior human factors researcher at DCA Design International.

Here, in advance of an interactive workshop they will present at Design Council, they discuss the necessity of designing from a strong evidence base.

Design is rarely a solitary exercise.

Despite perceptions brought about and perpetuated by celebrity designers, most products are developed by teams.

The reason is that many products, like planes, trains or automobiles, are simply too complex to be designed by one person alone. (And the more complex the system the worse in safety)

Even if they had the time, very few individuals have the required breadth and depth of skills, knowledge and attitude required to consider all aspects of the design.

For products of any notable complexity, the idea that a single individual could fully research the product, it’s context of use and commercial market, develop a concept, engineer it, test it, select materials and suppliers, and manage production transfer is simply a fantasy.

When it comes to working in teams, it’s not enough to be confident in one’s own convictions. If the best designs are to be developed, it is imperative that each member of the team is able to explain the rationale for the decisions they make and convince others.

The most beautiful products, like works of art, elicit physiological responses: upon first sight, pupils dilate and heart rate quickens.

The strongest brands can have the same impact.

Users often place greater trust in these objects, they care for them and take time to use them effectively.

But initial responses can also be fickle.

How do we ensure that users not only remain engaged with products but can also use them to enhance system performance? Or simply put, how do we create beautiful things that also work beautifully?

Evidence-based design is a key component in developing better things. It’s a philosophy that’s critical for ensuring the team have a common objective and rationale for decision making when working in large multidisciplinary teams.

And Measurement is a critical part of this.

This kind of approach is something that a select few do intuitively. They create compelling arguments for a vision of the future and they have the authority or the gravitas to set a course that others follow.

For most though, some form of systematic structure usually helps.

Fortunately, the human factors tool kit is jam-packed with methods and techniques ready to be used.

These methods range from ethnography and contextual enquiry to more data driven approaches that are able to quantify aspects of system performance such as efficiency, effectiveness, resilience, intuitiveness, usability and inclusiveness.

These approaches can also form the basis for ideation, providing inspiration and information for product improvements.

Ultimately a concise, well-supported argument for change is critical in ensuring that human factors are considered and communicated to a wide range of stakeholders.

This may include those within the design team as well as end users, regulators, maintenance staff, sales and marketing, as well as those involved with construction and decommissioning.

This way we can ensure that we are designing products and services that go beyond initial aesthetic appeal to enhance wider system performance.


A useful chart that maps the key factors in ensuring a strong evidence base for ergonomic design.


Dan Jenkins and Lisa Baker will be presenting an interactive workshop on these ideas at the Ergonomic Design Awards on 22 September at the Design Council. The workshop will introduce a range of human factors tools and explain how they can be used to build, inform, and present a compelling business case for change that leads to better products and greater system performance.

A second workshop will also be presented which examines how designers can ensure inclusivity into later life, and how we design for physical issues of ageing and cognitive impairments such as dementia, for example.

Find out more about these workshops or, alternatively, please contact James Walton on 07736 893 347 or at j.walton@ergonomics.org.uk

More to read on Human Factors designs

  1. On interfaces https://adonis49.wordpress.com/2009/05/17/what-other-interfaces-do-you-design%e2%80%9d/
  2. Message of HF discipline https://adonis49.wordpress.com/2009/07/10/what-message-has-the-human-factors-profession-been-sending/
  3. How HF fits in Engineering curriculum? https://adonis49.wordpress.com/2009/06/17/fitting-human-factors-in-the-engineering-curriculum/
  4. Taxonomy of methods in HF https://adonis49.wordpress.com/2009/06/10/an-exercise-taxonomy-of-methods/
Dr Dan Jenkins leads the human factors and research team at DCA Design International, working on a range of projects in domains including medical, transport, consumer goods and industrial products. Lisa Baker is a Chartered…
designcouncil.org.uk

Human Factors in Design

The term Design is all the rage.

Any professional in any field feels it imperative to add Design in the title.

Engineers, graphic professionals, photographers, dancers, environmentalists, climatologists, scientists… they all claim to be designers first.

And this is very refreshing.

Have you heard of this new field of Design Anthropology? https://adonis49.wordpress.com/2012/02/06/design-anthropology-why-are-there-designs-not-meant-for-human/

Dori Tunstall said in an interview with  Debbie Millman:

Design translate values into tangible experiences…Design can help make values such as equality, democracy, fairness, integration, connection…(values that we have lost to some extent), more tangible and express how we can use them to make the world a better place…”

Looks like Tunstall expanded the term design to overlap with the political realm of Congress jobs, law makers, political parties, election laws…

It is about time that everyone “think design” when undertaking any project or program

Anything we do is basically designed, explicitly or implicitly: Either we are generating products and programs for mankind, or it is mankind who is in charge of executing, controlling and managing what has been conceived.

So long as human are directly involved in using a product or a program, any design must explicitly study and research the safety, health, and mistakes that the operators and users will encounter.

Must as well that the design be as explicit in the attributes of health, safe usage, errors that might generate serious consequences, materially, mentally or physically.

Four decade ago, there was a field of study called Human Factors.

The term Human Factors was considered too general to be taken seriously in Engineering.

The implicit understanding was that “Of course, when an engineer designs anything, it is the human who is targeted….”

However, besides applying standards and mathematical formulas, engineers are the least concerned directly with the safety, health of users: The standards are supposed to take care of these superfluous attributes…

And who are the people concerned in setting standards?

Standards are arrived at in a consensus process between the politicians and the business people, and rarely the concerned users and consumers are invited to participate in the debate, except in later sessions when standards are already drafted…

And how explicitly experiments were designed to allow users to test, and give feedback to any kinds of standards, handed down from successive standard sets…?

Countless engineers and scientists are directly engaged in putting rovers on Mars and launching shuttles and… and the human in the project is taken for granted…

If you ask them whether they have human factors engineers in their teams, they don’t understand what you mean.

The project is supposed to be an engineering project, and “where the hell did you bring this human thing in the picture?”

Anything that is designed must consider the health, safety, and how a person from various ages, genders, and ethnic idiosyncracies might use the product or the program

Take all the time in design process. People are not supposed to be used as ginea pigs for any redesigned process… after countless lawsuits, pains, suffering…

This is a preliminary draft. Any input and replies?

Note: https://adonis49.wordpress.com/2008/10/04/whats-that-concept-of-human-factors-in-design/

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.

What is Human Factors in design? (Article #39, April 1st, 2006)

Fundamentals of controlled experimentation methods

An experiment is designed to study the behavior of the responses of subjects (dependent variables or what are measured as performance), as the values/stimuli of an independent variables or factors are changed, manipulated, or presented randomly or in fixed manner.

There are other factors that need to be controlled because they could have serious effects on the behavior of the selected dependent variables, and thus are held constant or fixed by appropriate techniques, procedures, instructions, experimental setting, and environmental conditions.

Controlled experimentation methods are versions of current simulations methods, but are essentially more structured and controlled.

In a nut shell, an experimental method is a series of controlled observations undertaken in an artificial situation with the deliberate manipulation of variables in order to answer specific hypotheses.

In general, a scientist plans, controls and describes all the circumstances surrounding his tests, in a way they can be repeated by anyone else, which offer dependability for validation.

The requisite of repeatability encourages artificial settings that can be controlled, especially because the participants/subjects in the experiment are not usually involved or engrossed in their tasks, and because it enables a scientist to try combinations of conditions that have not yet occurred.

Controlled experimentation are time-consuming, expensive, and require a staff of skilled researchers and investigators so that they are conducted for basic research, publishing scientific papers, and when sponsored by deep pockets private companies and well-funded public institutions.

There are different types of experiments, some are designed to extract cause and effects among the variables, and especially their interactions in the performance of a system.

Others experiments are not so well structured and are intended to explore a phenomenon at an initial phase.

Experiments varies in their design purposes and levels of control:  there are experiments on inanimate objects or natural phenomena that follow fixed trends and do not change much with time.

Experiments using human subjects in order to select the better performing system or product, and experiments intended to study the cognitive concepts of people such as attitudes, mental abilities, problem solving aptitudes, attention span and the like are very complex, very intricate,  highly time-consuming and expensive to conduct.

The next article entitled “Controlled experimentation: natural sciences versus people’s behavior sciences” is intended to compare the complexity, differences, and levels of difficulties among the various experiments.

This article is striving to establish the fundamental processes or necessary structured steps to conducting a controlled experiment.

In the spectrum of complexity, innovation, and difficulty the experiments in natural sciences are the easiest, and psychology the hardest; within that spectrum fall experiments in the disciplines of agriculture, econometrics, education, social sciences, and marketing.

Early researchers in the phenomenon of electricity had to experiment with simple methods of one dependent and one independent variable, rudimentary equipments, and to rely on an exploratory knowledge of how electricity works and what are the factors that cause definite change in the behavior of certain criteria.

For example, scientists observed that there are relationships among voltage/power, the intensity of the current and the material the current is flowing through, then a scientist set up an experiment to study how the voltage changes when the intensity of the current varies or when the resistance of a material varies.  By conducting several experiments, first by working with a specific conducting material, thus fixing the resistance, and varying the intensity of the current and repeating this simple experiment many times and, second by fixing the current at a certain level and working with different kinds of conducting materials, then the scientist managed to observe a steady mathematical relationship among these three variables.

As the body of knowledge in electricity expanded and more experiments were undertaken, the physical science of electricity discovered many more factors that entered into the mathematical relationship with varying degrees of importance and consequences.

Obviously, physical scientists can now enjoy more powerful, time-saving, and effective experimental designs that can employ several independent variables and several dependent variables in the same experiment thanks to the development in statistical/mathematical modeling and the number crunching computers; these developments in controlled experimentation allow observations of the interactions among the various variables simultaneously, if physical scientists deign to apply them!

Controlled experimentation methods have a set of requisite structured steps that are common to both natural and social studies. Usually, an investigator has to review the research papers on the topic to be investigated, sort out the articles that are scientifically valid and experimentally sound, consider the variables that have been satisfactorily examined and those that were controlled, or not even considered.   Or the scientist may explore the topic by systematic observation of the problem, then he has to propose a hypothesis that could be rejected, but never accepted no matter how often it was not rejected.  He has to conceive a design for the experiment such as the types, numbers of variables, their levels, and how to manipulate the trials, then he has to decide on the best method for selecting the subjects, the materials, or products to be tested, the setting conditions, the procedures, the operations or tasks to be performed, the instructions, the equipments, the appropriate statistical model.

Then the scientist has to conduct the experiment, running the data, analyzing the results, interpreting the results, and finally providing guidelines or practical suggestions to be applied in engineering projects.

The motors of statistical packages used to analyze data are mathematical models or sets of algebraic equations with as many equations as unknown variables and relying on the two main statistical concepts of means and variances among data.

The purpose of controlled experimentation methods is to strictly control systematic errors due to biases and then to sort out the errors that are due to differences among the independent variables and those introduced randomly by human variability.  Once the size of random errors is accounted for then it is possible to study the relationships among the independent variables and to claim that a hypothesis could or could not be rejected at a criterion level of statistical significance, set frequently at 5%.  This criterion level of 5% of statistical significance, means that there is still a 5% chance that an amount of random error might be the cause in the differences of the results.

Types of errors and mistakes committed in controlled experimentation will be reviewed in article #45.   However, it is important to differentiate between evaluation/testing methods and strictly controlled experimentation. In human factors discipline, evaluation methods are applied to compare the effectiveness of several products or systems by measuring end-users behaviors, like/dislike, acceptance/rejection, or satisfying rules and regulations with the purpose that management would be able to decide on the choice among the products offered within specifications.

Controlled experimental methods are mainly applied to study the cause and effects of the main factors on objective measurements that represents valid behaviors of representative samples of end-users with the purpose of reaching design guidelines for products or systems planned for productions.

What could be the Human Factors performance criteria?

Note: Re-edit (Human Factors in Engineering, Article #38, written in March 31, 2006)

Performance” is the magic answer offered by university students to questions like “What is the purpose of this course, of this method, of this technique, or of this design?”

Performance is what summarizes all the conscious learning in the knowledge bag, for lack of meaningful full sentences available in the language to express clear purposes.

It takes a couple of months to wean the students from the catch word “performance” and encourage them to try thinking harder for specificity.

There is a hierarchy for this abstract notion of “performance”.

The next level of abstraction is to answer: “What kind of performance?“.

The third level should answer: “How these various performances criteria correlate?  Can we sort them out between basic performances and redundant performance criteria?”.

The fourth level is: “How much for each basic performance criterion?  Can we measure them accurately and objectively?”

It seems that every discipline has created for itself a set of performance criteria and they are coined in stone, so that an insertion of another element into that set, is like a paradigm shift in its field of science.

If you prompt a business or engineering university student to expand on the meaning of “performance”, when supported by a specific example, it might dawn on him to spell out another piece of jewels such as: “max profit”, “minimize cost”, “improve quality”, “increase production”, “save time”, or “increase market share”.

In order to reach a finer level of specificity we need to define functionally, for example, what “max profit” means.  A string of monosyllables rains from every where such as: “increase price”, “cut expenditure”, “sell more”, and again “improve quality”, “save time”, or “increase market share”.  If we agree that profit is a function of market share, price, expenditure, added values of products, and marketing services then we can understand what could be the basic criteria and which criteria dependent on the basic ones.

How can a business improve performance?

How can it make profit or cut costs? 

Should the firm layoff redundant employees, force early retirement, dip in insurance funds, contract out product parts and administrative processes, eliminate training programs, scrap off the library or continuing learning facilities, streamline the design process, reduce advertising money, abridge break times in duration or frequency, cut overhead expenses such as control lighting and comfort of the working environment, stop investing in new facilities, firing skilled workers, settling consumer plaintiffs out of court, searching for tax loopholes, or engineering financial statements?  How can a business increase its market share? How can it survive competitors and continually flourish?

How can a firm improve products for the quality minded engineers?

Should it invest on the latest technological advancements in equipment, machines, and application software, or should it select the best mind among the graduates, or should it establish a continuing education program with adequate learning facilities, or should it encourage its engineers to experiment and submit research papers, or should it invest on market research to know the characteristics of its customers, or should it built in safety in the design process, or perform an extensive analysis of the foreseeable misuses of its products or services, the type of errors generated in the functioning and operation of its products and their corresponding risks on health of the users, or manage properly employees’ turnover, or care about the safety and health of its skilled and dedicated workers, or ordering management to closely monitor the safety and health standards applied in the company?

At the first session of my course “Human factors in engineering” I ask my class:  “What is the purpose of an engineer?

The unanimous answer is: “performance”.  What are the criteria for an engineer?  The loud and emphatic answer is: “performance”!

At the first session of my class I repeat several times that the purpose of the engineering discipline is to design practical products or systems that man needs and wants, that human factors engineers are trained to consider first the health and safety of end users, the customers, the operators, and the workers when designing interfaces for products or systems.

At the first session I tell my class that the body of knowledge of human factors is about finding practical design guidelines based on the capabilities and limitations of end users, body and mind, with the following performance criteria: to eliminate errors, to foresee unsafe misuses, to foresee near-accidents, to design in safety operations, to consider the health problems in the product and its operation, to study the safety and health conditions in the workplace and the organizational procedures, to improve working conditions physically, socially, and psychologically, and to be aware of the latest consumer liability legal doctrines.

A month later, I am confronted with the same cycle of questions and answers, mainly: “What is the purpose of an engineer?”  The unanimous answer is: “performance”.  What are the criteria for a human factors engineer?  The loud and emphatic answer is: “performance”!

A few students remember part of the long list of human factors performance criteria, but the end users are still hard to recognize them.

A few students retained the concept of designing practical interfaces or what an interface could be but the pictures of end users are still blurred.

I have to emphasize frequently that the end users could be their engineering colleagues, their family members, and themselves.  I have to remind them that any product, service, or system design is ultimately designed for people to use, operate, and enjoy the benefit of its utility.

Human factors performance criteria are all the above and the design of products or services should alleviating the repetitive musculo-skeletal disorders by reducing efforts, vibration, and proper handling of tools and equipment, designing for proper postures, minimizing static positions, and especially to keep in mind that any testing and evaluation study should factor in the condition that a worker or an employee is operating 8 hours a day, 5 days a week, and for many years.

I tell them that any profit or cost cutting is ultimately at the expense of workers/employees, their financial stability, safety standards, comfort, and health conditions physically, socially, and psychologically whereas any increase in performance should be undertaken as a value added to the safety, comfort, and health of the end users.

Article 25, September 11, 2005

“My pet project for undergraduate engineering curriculum”

My aim is to produce hybrid scientists or engineers with Human Factors background in undergraduate curriculum.  Undergraduate university students must enjoy a comprehensive curriculum initiating them to methods applied in both hard and soft sciences.  Basically, students must be knowledgeable in the various ways of designing experiment, which is the common denominator methods, taught implicitly but never satisfactorily because the logic is not that straighforward unless exposed explicitly and trained.

Undergraduate engineering disciplines must require courses in experimental research and statistical analyses training and drawn from multidisciplinary social sciences so that they can be better positioned to handle research involving mathematical modeling of theories in sciences.

I believe that at least 6 courses should be included in any engineering field involved in system design, which are: “Human Factors” in 2 courses, “Design for inferential experiments” and “Structural linear equations modeling applying the statistical analytical package LISREL”, “Human performance”, “Systems risk assessments”,  and “Occupational safety and health”.

It is advisable that engineering departments, architecture and any field involved in designing systems or subsystems, with the avowed mission of reducing errors committed by end users in the application and maintenance of their tasks, need to offer 3 required courses and three elective courses related to the factors that affect the performance of end users.

These courses are meant mainly to designing interfaces between systems and end users, whether the latter are engineers, operators, workers, technicians or consumers, but they are also important for the designers of the systems to be cognizant of the problems related to the capabilities, limitations and behavior of end users who will ultimately break or implement any well-intentioned and best designed systems from textbook standards and processes.

The first required Human Factors course would be an introduction to the basics in designing for people, the physical and cognitive capabilities and limitations of end users, the environmental and organizational factors that may affect performance and the physical/mental applications and methods for designing interfaces between systems and end users.

The second Human Factors course, which could be elective, would initiate designers to actually design an interface with the needed experiments relevant to validating the requirements and guidelines that foresee the compatibility of the system performance with the level of skills and training required by the end users. A designed interface would be accompanied by facilitating aids, procedures and functional booklets to enable end users for ready application.

The third course called “Design of experiments” is to initiate designers on efficient designed experiments that would save time, effort and money with the additional result of accounting for the interactions among all the factors under study and providing designers with facts that they could readily apply in their design endeavors. This course is not meant to dwell heavily on the mathematical basis for the statistical analysis, which requires another follow-up course, but to form scientific minds which can critically analyze research papers and the experimental procedures that encourage designers to start reading research papers and appreciating the materials that would form the basis for their continuing education.

The fourth course called “Systems risk assessments” would initiate designers to the trade-off decisions of the safety and health risks on the users, environment and organizational structures in societies and the financial cost from the adoption of technologically complex alternative designs.

The fifth course called “Occupational safety and health”, in addition to initiating the engineers on the laws and processes for a safe work place, will also encompass the concept of consumer’s product liability and forensic engineering. A designer needs to be familiar with the problems and consequences of his designs to the end users, their idiosyncrasies and cultural differences in using any product or manufacturing process design in an occupational setting.  The knowledge of the standards and applicable laws and guidelines for a safe and healthy manufacturing or processing plant can make a substantial difference among graduating engineers not only in their people communication skills and designing performance but also for later promotions in any administrative or organizational positions.

The sixth course “Human performance” is designed to providing the skills and training necessary to designing and evaluating the performance of interfaces. Examples of these skills include the development of written instructions, designing relevant questionnaires to assess the characteristics and training skills of target users and how well the interface is performing, designing performance aids to helping the short-term memory of operators, formatting instructions and information, input data display formats, output formats, coding design, personnel selection, determining qualifications and any written or verbal technique or method necessary to testing, evaluating and quantifying operators’ performance.

An informed engineering designer, who can define the limitations, skills and needs of the target users for his interface and who is trained early on in his academic years to the consequences of his tasks, may save end users from committing many foreseeable errors, greatly alleviate their physical and mental anguish, suffering, pain and inefficiency and thus save his sponsors time and money for later redesign undertaking.

The afore-mentioned courses, if offered in the first 2 years of the curriculum, might provide the undergraduate students with a different perspective toward the remaining core courses that enhance the seriousness of his responsibilities and the importance of his profession.

I frankly cannot conceive of an engineer pursuing higher graduate studies without being exposed to the fundamental necessity of designing to target users.  Engineering is an applied science for practical human needs and not knowing the needs and behavior of target users then the engineer’s design endeavor might be flawed from the start.

What’s that concept of Human Factors in design? Article 21

“How engineering curriculums can be restructured to respond to end users demands?” (Written in  April 19, 2005)

In 1987 Alphonse Chapanis, a renowned Human Factors professional, urged that published Human Factors research papers target the practical design need of the various engineering disciplines so that the research data be readily used by engineers.  Chapanis was trying to send a clear message that Human Factors sin qua was to design interfaces between systems and end users.  And thus, research papers have to include sections directing the engineers as to the applicability of the results of the paper to design purposes.

In return, it is appropriate to send the message to all engineering disciplines that research papers should include sections orienting the engineering practitioners to the applicability of the results of the papers to the end users and how Human Factors professionals can judiciously use the data in their interface designs.

As it was difficult for the Human Factors professional to send the right message to the engineering practitioners, and still has enormous difficulty disseminating the proper purpose and goals, it would be a steep road for the engineers to send the right message that “what they design is actually targeting the needs and new trends of the end users“.

As long as the engineering curriculums fail to include the Human Factors field as an integral part in their structures it would not be realistic to contemplate any shift in their designs toward the end users. Systems would become even more complex and testing and evaluation more expensive in order to make end users accept any system and patronize it.

Instead of recognizing from the beginning phases that reducing errors and risks to the safety and health of end users are the best marketing criteria for encouraging end users to adopt and apply a system systems are still being designed by different engineers who cannot relate to the end users because their training is not directed explicitly toward them.

What is so incongruous with the engineering curriculums to include course that target end users?

Why would not these curriculums include courses in occupational safety and health, consumer product liability, engineers as expert witnesses, the capabilities and limitations of human, marketing, psychophysics and experimental design?

Are the needs and desires of end users beneath the objectives of designing systems?

If that was true then why systems are constantly being redesigned, evaluated and tested in order to match the market demands?

Why do companies have to incur heavy expenses in order to rediscover the wheel that the basis of any successful design ultimately relies on the usefulness, acceptability and agreement with the end users desires and dreams?

Why not start from the foundation that any engineering design is meant for human and that designed objects or systems are meant to fit the human behavior and not vice versa?

What seem to be the main problems for implementing changes in the philosophy of engineering curriculums?

Is it the lack to find enough Human Factors, ergonomics and industrial psychologist professionals to teaching these courses?

Is it the need to allow the thousands of psychologists, marketing and business graduates to find debouche in the market place for estimating users’ needs, desires, demands and retesting and reevaluating systems after the damages were done?

May be because the Human factors professionals failed so far to make any significant impact to pressure government to be part and parcel of the engineering practices?

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.


adonis49

adonis49

adonis49

October 2020
M T W T F S S
 1234
567891011
12131415161718
19202122232425
262728293031  

Blog Stats

  • 1,420,586 hits

Enter your email address to subscribe to this blog and receive notifications of new posts by email.adonisbouh@gmail.com

Join 771 other followers

%d bloggers like this: