Adonis Diaries

Archive for October 26th, 2008

How to optimize human potentials in businesses for profit”

Article #53, (Written in October 3, 2006)

            University students learn their future profession theoretically and piece meal, one course at a time… They are not exposed to meaningful courses with the objective of linking all the concepts together or a cross-over knowledge of the problems of the different concepts within the profession.

The best that most universities come up with is a last year project, supposedly to initiate the graduate to a real life problem in one aspect of the business.

For example in industrial engineering, when a student learn how to optimize inventory he has the impression that ultimately some magic inventory formula will generate the most profit to the enterprise; the student fails to comprehend the interactions among inventory, production capacity, marketing, sales, finance, management style, medium and long-term planning for profitability of the whole business.

Most of the time, the student does not understand that maximizing in one department is counter productive in another department and that what he believed is excellent performance might turn to complete disaster for the business in return on investment and profitability.

            What a university student needs to comprehend is that the success of any enterprise is the development of human potentials within it, and the best potential for a graduating student is to joining a serious and comprehensive training program before graduating or after when hired by a company.

The training program must necessarily introduce the new recruits to the interactions among the different departments and their cross-over difficulties. The best example I can offer is the successes of Carlos Ghosn, the “Cost Killer” from Lebanese descent, who revived Nissan from certain death into profitability within three years.

Carlos university background was mostly in abstract higher mathematics and graduated from the prestigious engineering university of Mines in Paris. It is the formation of Carlos at the multinational pneumatic company Michelin that provided him with a wide spectrum in managerial skills and know-how that prepared him for tackling general and particular problems in several faltering enterprises.

It is necessary to dwell on the training program in Michelin.

Carlos was hired in 1978 and in the first 3 months, the new recruits for all types of functions followed the same program consisting of conferences given by the main directors of departments on the different aspects of the business.  These conferences were backed up by small real operational problems that needed simple solutions within a restricted time limit.

The new recruits live together and they learn to go through the transition between a student life and the active one.  This training program also offers management a profile of the new recruits and their potentials in different sectors of the business.

At the end of the training period, Carlos was affected to work for another three months in a factory preparing the rubber that will be turned into tires.  His work consisted of cutting the rubber, rolling it up, inserting it into moulds and then transporting it… The best part is the fraternity that is created among the workers and the future bosses.

Carlos is then promoted foreman for a group of workers in a new factory.  Six months later, he is dispatched to an affiliate company in Germany to get training on quality control, and training in industrial organization at the factory in Tours.  He is promoted group chief of production for a whole year at the factory in Cholet.

In 1981, Carlos is 27 years old and director of the new factory where he worked as foreman and will stay 2 years and three months.

Carlos is summoned to headquarter to meet with the ‘Boss’ Francois Michelin. The Boss assigns him the task of investigating the troubles of the straggling affiliate Kleber-Colombes.  Carlos has to work as adjunct to the director of finance Behrouz Chahid-Nourai and discover the concept of “cross manufacturing” for utilizing the same tools of production for several products under different brands.

After offering his recommendations to revitalize Kleber-Colombes, he is affected to the research department for a year, the job that Michelin initially contemplated that he might fit better in the company when he was in the training program.

In June 1985, Carlos is promoted director of the troubled operations in Brazil.  In February 1989, Carlos takes over the operations in the USA and settles in Greenville South Carolina.

This training formation at Michelin is at the foundation of Carlos concept of forming leaders in any enterprise.  He views the primary task of the ‘Boss’ in any institution is to send everyone with potential to the hot fronts on the terrains where difficulties are observed and then offer them chances to fail sometimes.

It is by providing opportunities to learn and prove leadership that the ‘Boss’ can ensure the survival of his enterprise when he decides to retire. The leaders of tomorrow are formed from the challenges of today and the clever ‘Boss’ should end up with a wide choice of alternative leaders when the time to retire is near.

When a general director is hired he should embrace the responsibilities of the past, present, and future status of the enterprise; he is not allowed to dwell on excuses from past failures as if they were not of his doing.

A general director has to first gather all the current facts and information on the institution and base his theory on these pieces of intelligence. The boss has to feel the enterprise and the clients, suppliers, concessionaires, stockholders, and customers, by frequent visit to the different sections of the business and proffer the same message everywhere.

The boss does not have to comprehend in-depth every facet of the business, which is the job of the specialists whose task is to adequately summarize the topic so that the boss is in a position to take decisions.

The boss should not forget for a moment that the crux of the matter is to produce quality products and be able to sell at profit.  Otherwise, if diversification into other businesses is undertaken without close supervision to the core business then the enterprise will suffer ultimately.

I might generalize the term “boss’ to include any employee who was assigned a position of responsibilities, even a foreman job and he has to follow all the above prerequisites in order to achieve quantified results.

This section will focus on the professional aspects of Carlos after the strategic alliance of Renault and Nissan, whereof Renault bought 36% of Nissan shares for $ 5 billion.  Carlos was selected to head the operations of reviving Nissan from certain death in 1999 because Japan did not yet transform its economy and financial institutions to absorb and rely on foreign investments in the deflation period of the 90’s.  Carlos brought with him a total of 30 French specialists in Renault in a period of three months to support his job; the understanding was that they are not in Japan to change the culture of the Japanese employees but with the objective of turning Nissan around to profitability.

For three months Carlos set up nine “transversal or cross-functional teams or CFT”, constituted of ten members and each headed by two members of the executive committee which was reduced to ten, with the task of understanding each other departmental problems.  For example, the Executive Vice President (EVP) for procurement was teamed with the EVP for research and development.  Each main CFT team relied on other CFT cells with tasks to investigate deeper special problems.

In total, 500 persons were mobilized in the CFT organizations between July and September 1999.  Carlos visited all the factories and suppliers to get a feel of the major problems and to get to the bottom of the illnesses of Nissan.

For example, Carlos discovered that six suppliers of tires for a factory producing 200,000 cars did not know the vision of Nissan, its strategy, or its priorities; the peculiar standards of Nissan were changed and imposed every three months, instead of the standards in the business and their suggestions were not heard or acted upon. During these months Carlos encouraged and was open to interviews by the Medias in order to promote the concept of transparency that will be adopted in reviving Nissan and also to encourage communications inside the institution and disseminate the steps to be taken and the expected changes that will follow.

In October 18, 1999 Carlos divulged his plan of rebirth NRP to an assembly of journalists; it was a surprise announcement and no one outside the members of the executive committee new about the announcement; even the Japanese government got wind an hour prior to the announcement.

Nissan dropped from 6.6% to 4.9 % of the world market in 8 years or a reduction in production of 600,000 cars; it was heavily indebted of $19.4 billion. Carlos promised that Nissan will introduce 22 new models within three years and that the objective is to reduce the cost of procurement to 20% since it represented 60% of the total cost, the number of suppliers of pieces; materials, equipment and services to almost half from a total of more than 8000 suppliers by 2002.

Nissan had the capacity of producing 2.4 million cars but actually produced 1.3 million; thus five factories would be closed by 2002 so that the rate of utilization of the remaining factories would be up to 82% taking into account a growth of 5.5% by 2002.  Thus, Nissan will end up with 4 factories utilizing only 12 plate-forms. Nissan will have to reduce by 20% the number in its network of distribution subsidiaries and close 10% in its points of sales.

Most important, Nissan will sell its shares in almost 1400 societies that do not strategically contribute to car manufacturing business.  The number of employees would be reduced 14% to 127,000 with the exception of the department of research and development which will gain 500 additional jobs and the engineering department another two thousands.

Three targets were set to be accomplished by 2002, otherwise, Carlos and all his executive committee will quit even if one of these targets is not attained; these targets are the return to profitability, a rate of operational margin exceeding 4.5%, and the reduction of the total debt to 50%.

These three targets were reached and in 2002.  By 2003, Nisan stocks jumped from 360 to 1200 yens, the syndicate at Nissan obtained all their demands which were reasonable while the number one Toyota froze salaries. Many in Nissan are now exercising their rights for stock options and the minimal number of stocks was reduced to 100 instead of one thousand. The team of Carlos Ghosn then elaborated a three years plan called Nissan 180, where 1 represent an additional one million cars produced, 8 for an operational margin of eight percent growth, and 0 for zero debt by the end of the triennial.

As Carlos explained: “If an enterprise does not develop middle and long-term plans then the financial analysts will have nothing to rely on but the near term results and the employees will feel totally disoriented and discouraged if the results were not satisfactory“.

By the year 2003, 80% of Nissan’s cars would emit only 25% on the regulatory limit on pollutants.  An agreement with its archenemy Toyota was signed in September 2002; Toyota would provide Nissan 100,000 hybrid engines vehicles to be marketed in the USA by the year 2006. A hybrid engine works in the classical manner on highways and electrically within city routes.

In November 2000, six months after the announcement of the NRP plan, Carlos decided to invest $ one billion in the USA for the construction of a new plant in Canton in the State of Mississippi; this new plant will target the segment of large pick-ups and SUV in the Middle West market where the American companies have it locked. This investment secures a stronger implantation in the most profitable market in the world because it has the best mix and a homogeneous market for advertisement and distribution and selling 16 million vehicles a year; it will also save on the tax barriers and monetary exchanges.

Another development is the investment in China, a new emergent market with the biggest potential given the saturation of the matured developed nations.  Nissan concluded a deal to invest more than $ one billion to acquire 50% of Dongfeng, a Chinese state-owned enterprise that manufactures buses and heavy trucks. By the year 2010, this joint venture is projecting to produce 450,000 Nissan cars and 450,000 heavy vehicles.

The Chinese government gave priority to Nissan because of the bold steps it has taken to get back to profitability and of its experience with multicultural and global management practices.

Although the initial intention was to revive Nissan into profitability some cultural changes within Japanese business behavior had to occur. For example, Nissan had an organization of assigning counselors to each field teams with no definite operational functions and not responsible to results; these counselors were originally dispatched to foreign countries to disseminate the Japanese practices but were of no use anymore; these counselors ended up diluting the responsibilities of the field directors; they  had to go.

Another Japanese practice was to promote employees according to seniority as well as increase in salaries without any regard to productivity or innovation; Carlos instituted the notion of result instead of effort in judging what is fair.  The consequences for that notion of result did away with the practice of working overtime and spending unduly longer time at the offices, even showing to work on holidays in order to please management and prove that they were investing lots of efforts.

The doing away with the seniority criterion for automatic promotion meant that new recruits could be hired at higher and competitive salaries. The cost of incentives represented the variable portion in the total cost which was 40% at Nissan. Employees will thus be judged according to their contributions and incentives given to those who satisfy quantitative criteria.

The third practice was hiring for life. During the recession in the 90’s, many Japanese companies concocted many gimmicks to in reality fire employees while providing the image of still belonging to the firm; for examples, many were assigned to concessionaires and suppliers who paid their salaries. Fourteen percent of employees will lose their jobs and many of these fictitious employees distributed to suppliers were repatriated to Nissan.

In the automotive business the question for the future is: can it afford a competitive offer and the capacity to maintain it? The end game reduces to maintaining innovation in a complex market, where emotions of clients for a stylistic car play a critical part along with quality and at a competitive price.

The team detached from Renault to Nissan played the role of catalyst because the real resource of Japan as the second economy in the world is its professional and skilled people.  Japan has no natural resources, a relatively tiny island, ravaged by earthquakes and typhoons and facing strong adversaries. Japan has the third of the world monetary reserves although it has now a public debt up to 150% of its PIB.

It is apparent that the Japanese companies have not assimilated the Nissan experience because they are still suffering from indecision and indebtedness; the “Cost Killer” Carlos believes that the problem is a lack of know-how and experience to treating their own managerial problems that did not change for over 40 years.


Article #52, (September 12, 2006)

“Mathematics: a unifying abstraction for Engineering and Physics Phenomena”

A few examples of mechanical and electrical problems will demonstrate that mathematical equations play a unifying abstraction to various physical phenomena of entirely different physical nature.

Many linear homogeneous differential equations with constant coefficients can be solved by algebraic methods and their solutions are elementary functions known from calculus such as the examples in article 51.  For the differential equations with variable coefficients, the functions are non elementary and they fall within two classes and play an important role in engineering mathematics.

The first class consists of linear differential equations such as Bessel, Legendre, and the hyper geometric equations; these equations can be solved by the power series method.

The second class consists of functions defined by integrals which cannot be evaluated in terms of finite many elementary functions such as the Gamma, Beta, and error functions (used in statistics for the normal distribution) and the sine, cosine, and Fresnel integrals (used in optics and antenna theory); these functions have asymptotic expansions in the sense that their series may not converge but numerical values could be computed for large values of the independent variable.

Entirely different physical systems may correspond to the same differential equations, not only qualitatively, but even quantitatively in the sense that, to a given mechanical system, we can construct an electric circuit whose current will give the exact values of the displacement in the mechanical system when suitable scale factors are introduced.

The practical importance of such an analogy between mechanical and electrical systems may be used for constructing an electrical model of a given mechanical system. In many cases the electrical model provides essential simplification because it is much easier to assemble and the values easily measured with accuracy while the construction of a mechanical model may be complicated, expensive, and time-consuming.

An RLC-circuit offers the following correspondence with a mechanical system such as: Inductance (L) to mass (m), resistance (R) to damping constant (c), reciprocal of capacitance (1/C) to spring modulus (k), derivative of electromotive force to the driving force or input force, and the current I(t) to the displacement y(t) or output.

Here are a few elementary examples:

5)      Ohm’s law: Experiments show that the voltage drop (E) in a close circuit when an electric current flows across a resistor (R) is proportional to the instantaneous current (I), or E = R* I.

Also, that the voltage drop across an inductor (L) is proportional to the instantaneous time rate of change of the current, or E = L*dI/dt.

Also, the voltage drop across a capacitor (C) is proportional to the instantaneous electric charge (Q) on the capacitor, or E = Q*1/C.  Note that I(t) = dQ/dt.

6)    Kirchhoff’s second law:  The algebraic sum of all the instantaneous voltage drops around any closed loop is zero, or the voltage impressed on a closed loop is equal to the sum of the voltage drops in the rest of the loop. Thus,

E(t) = R*I + L*dI/dt + Q*1/C.

For example, a capacitor (C = 0.1 farad) in series with a resistor (R = 200 ohms) is charged from a source (E = 12 volts).  Find the voltage V(t) on the capacitor, assuming that at t = 0 the capacitor is completely uncharged.

7)    Hooke’s Law: Experiments show that when a string is stretched then the force generated from the string is proportional to the displacement of the stretch,

or F = k*s.  If a mass (M) is attached to a string, then when the string is stretched further more (y) after the system is in a static equilibrium, then: F = -k*s(0) – k*y.

Newton’s second law for the resultant of all forces acting on a body says that:

Mass * Acceleration = Force, or My” = -k*y.

Furthermore, if we connect the mass to a dashpot, then an additional force come into play, which is proportional to the rate of change of the displacement due to the viscous substance with constant (c).  The equation is then a homogeneous second order differential equation: M*y” + c*y’ + k*y = 0.  Depending on the magnitude of (c) we have 3 different solutions: either 2 distinct real rots, 2 complex conjugate roots, or a real double root [c(2) = 4*M*k)} corresponding respectively to the conditions of  over damping, under dumping, or critical damping.

For example, determine the motions of the mechanical system described in the last equation, starting from y = 1, initial velocity equal zero, M = 1 kg, k =1 for the various damping constant: c = 0, c = 0.5, c = 1, c =1.5, and c = 2.

8)    Laplace’s equation is one of the most important partial differential equations because it occurs in connection with gravitational fields, electrostatic fields, steady-state heat conduction, and incompressible fluid flow.  The solutions of the Laplace equation fall within the potential theory.

For example, find the potential of the field between two parallel conducting plates extending to infinity which are kept at constant potentials; or the potential between two coaxial conducting cylinders; or the complex potential of a pair of opposite charged sources lines of the same strength at two points.


Article #51; (August 23, 2006)

“Basic Engineering and Physics Problems Transformed Mathematically” (draft)           

 This article exposes several practical exercises in engineering and physics that experimental data or observations had generated laws.  Consequently, the resolution of their mathematical equations provided the necessary incentives to open up new mathematical methods and fields of studies.

Conversely, many mathematical discoveries done on purely theoretical basis lead to practical applications later on.  We should keep in mind that mathematical equations are merely an abstraction of the reality, obtained by disregarding certain physical facts which seem to be of minor influence. In complicated physical situations, there may be no way of judging a priori the importance of various circumstances.

Let us state that rate of a quantity is the proportion of change in that quantity over a specific duration; the mathematical definition is written as the differential of that quantity (Q) over time (t) or dQ/dt.  For the following exercises the first step of the mathematical formulations of the laws will be provided without any attempt to solving them:

1)  Newton’s law of cooling:  Experiments show that the rate of change of the temperature T1 of a conductive material to heat is proportional to the difference between T and the temperature of the surrounding medium. The mathematical formulation is: dT/dt = -k*(T1-T2); where k is a positive constant.  Let us suppose that a copper ball is heated to a temperature T1 = 100 degrees C.  At time t=0 the ball is placed in water which is maintained at a temperature T2 = 30.  At the end of 3 minutes the temperature of the ball is reduced to T3 = 70.  Find the time at which the temperature of the ball is reduced to T4 = 31.

2) Newton’s law of gravitation:  Experiments show that the acceleration (a) of a body is proportional to inverse of the square of the distance (r) between the body and the center of the earth, or a(r) = k/r(2).  Find the minimum initial velocity of a body which is fired in radial direction from the earth and is supposed to escape from earth; neglect the air resistance and the gravitational pull of other celestial bodies. Formulation: a(r) = – g*R(2)/r(2)

3)  Torricelli’s law:  Experiments show that the velocity with which a liquid issues from an orifice is v = [0.6*square root (2*g*h)] where h is the instantaneous height of the liquid above the orifice and the constant 0.6 was introduced by Borda to account for the fact that the cross-section of the out flowing stream of liquid is somewhat smaller than that of the orifice.  A funnel whose angle at the outlet is 60 degrees and whose outlet has a cross-sectional area of 0.5 cm(2), contains water at a height of h = 10 cm.  At time t = 0 the outlet is opened and the water flows out.  Determine the time when the funnel will be empty.  Formulation: the change in volume of water lowing out during a short interval of time is: dV = 0.5* v*dt.

4)  Boyle-Mariotte’s law for ideal gases:  Experiments show that for a gas at low pressure (p) and constant temperature (T) the rate of change of the volume is: dV = -V/p

5)    The radiation of element radium law:  Experiment show that radium disintegrates at a rate proportional to the amount of radium (M) instantaneously present or: dM/dt = k*M.  What is its half-life or the time in which 50% of the amount M will disappear?  If the half-time is 1590 years, then what per cent will disappear in one year?

6)    The atmospheric pressure law:  Observations show that the rate of change of the atmospheric pressure (p) with altitude (h) is proportional to the pressure, or  dp/dh = – k*p.  If p at 18,000 ft is half its value at sea level, find the formula for the pressure at any height.

7)    The evaporation law:  Observations show that a wet porous substance in the open air loses its moisture at a rate proportional to the moisture content (Q) or:  dQ/dt = -k*Q.  If a sheet hung in the wind loses half its moisture during the first hour, when will it have lost 99% under the same weather condition?

8)    Sugar cane dilution law:  Experiments show that the rate of change of the inversion of cane sugar in diluted solution is proportional to the concentration (Y) of the unaltered sugar, or d(1/Y)/dt = k*Y.  If the concentration is 1/100 at t = 0 and is 1/250 at t = 5 hours, then find Y(t).

9)    The law of boiling liquids:  Observations show that the ratio of the quantities of two liquids of each passing off as vapor at any instant is proportional to the ratio of the quantities x and y still in the liquid state, or dy/dx = k*y/x.

10) Lambert’s law of absorption:  Observations show that the absorption of light in a very thin transparent layer is proportional to the thickness (x) of the layer and to the amount incident (A) on that layer, or dA/dx = -k*A.

11)  The law of mass action:  Experiments show that the velocity (v) of a chemical reaction, under a constant temperature, is proportional to the product of the concentrations (a) and (b) in moles per liter of the substances which are reacting.  If y is the number of moles per liter which have reacted after time (t), then the rate of reaction is: dy/dt = k*(a – y)*(b – y).

12)  Falling body law:  Experiments show that, if a body falls in vacuum due to the action of gravity and starting at time t = 0 with initial velocity v = 0, then the velocity of the body is proportional to the time or ds/dt = k*t, where s is the displacement or the distance of the body from its initial position.

Article #50, (September 10, 2006)

Computational Rationality in Artificial Intelligence

The field of Artificial Intelligence would have been more on target if it was called “Computational Rationality”, which is fundamentally the approach of the fourth system:  Any scientific field, to be considered mature, a consensus by the professionals has to be reached; and the roots of the field of knowledge should be firmly grounded on mathematics and recognized traditional “rational logic”.

            In order to have a holistic view of the elements that are considered in AI, it would be interesting to picture a table of basic elements such as designed for the chemistry elements. Thus A for atom, Ab for alpha-beta search, Al for algorithm, Af for automatic theory formation, At for augmented transition net, B for Bayes’ rule, Bf for breadth first search, Bl for blocks-world labelling heuristics, Br for binary relations, Bt for backtracking search, C for concept formation, Cd for COND, Cf for closure of functions, Cg for context-free grammar,  Cl for cellular logic,  Cn for constraint, Cr for circular reaction paradigm, Cs for CONS, Df for differentiation, D for depth, Dc for Dempster-Shafer calculus, De for debugging, Df for DEFUN, Di for discovery, Dm for dialogue management, Dn for discrimination network,  Ds for depth first search, E for expertise, F for frame, Fc for forward chaining, Fm for formula manipulation, Fz for fuzzy logic, H for heuristic, Hm for the Hough transform, Ht for Herbrand’s theorem, I for ISA hierarchy, In for integration, Ie for inference engine, If for image formation and acquisition, Ih for inheritance, In for inference network, Ir for image representation, Kr for knowledge representation, L for lexicon, Lp for LISP, Lr for logical reasoning, Ls for LEIBNIZ structure, M for morphology, Mp for MAPCAR, Nm for numerical model, P for Prolog, Pa for pattern matching, Pb for probability, Pc for propositional calculus, Pd for predicate calculus,  Pf for preprocessing of low-pass filtering, Pg for pragmatics, Pl for planning, Pp for parallel processing, Ps for problem solving, Pr for production rule, Py for PYTHAGORUS, Q for quantization, R for robotics, Ra for Ramer’s algorithm, Rb for rule-based systems, Rc for recursive lists, Rd for relational database, Re for relaxation, Rn for resolution, S for semantics, Sc for schemata, Sf for sufficiency factor, Sg for segmentation, Sh for shell, Sn for semantic net, Sp for script, Sq for SETQ, SS for state space, St for stereo, Sx for S-expression, Sy for syntax, U for unification, T for topology, Tt for Turing’s test, V for version space, Z for zero-sum games.

It would be interesting to classify these AI elements into chapters such as: Programming in LISP, Productions and matching, Knowledge representation, Search methods, Logical reasoning, Probabilistic reasoning, Learning, Natural-language understanding, Vision, and Expert systems…

Is our intelligence that natural or acquired through customs, tradition, formal teaching, standards of moral value, community consensus…Even a person living in a forest, away from any mankind habitation and communication, he is learning from animal behaviors communicated from customs, tradition, teaching processes inculcated by the particular animal communities…

How mankind intelligence differ and developed? Mostly through trading with other human communities:  Exchanging expert tools of production, learning mechanisms, various customs and traditions…Variety of perspectives to looking at life, the universe and survival processes…

(To be developed further)


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

Article #47 ( written in June 7, 2006)

Professor Charles Elachy, the director of NASA jet propulsion center at Pasadena in California, gave a lecture at LAU, Byblos, during his visit to Lebanon, and was inducted a member of the Board of Director of the university.

I instructed my class to prepare written questions to submit to Professor Elachy after the lecture, but we failed in our endeavor because questions were stricly managed.  I composed a series of questions, and after discussing them with my class, I e-mailed them to Elachy on May 30, 2006.  The mail stated:

            “I teach a single course “Human Factors in engineering“, which is required for industrial engineers. This course used to be elective for the computer and other traditional engineering fields before this year, until it was eliminated as a viable choice in the curricula.

The main value of this course is to offer a behavioral change at looking at the design of projects from a different perspective. A few students in my class of Human Factors in engineering prepared a series of written questions for your lecture at LAU at Byblos, and we would appreciate your reply on the following:

1)   As a leading member of one of the most sophisticated man-made system from conception, to designing, testing, evaluation, production, operation, and execution, then would you consider that any failure in your system is ultimately a human error?

2)  Could you offer us samples of what NASA would consider as near accidents?  In such cases, would your internal investigation of any near accident try to assign the error to a person, a team, or the organization as a whole in order to redress potential hazards?

3)  I read that the engineering work force at your department in NASA is around 5000.  What is the percentage of human factors and “industrial psychology” professionals in that work force who are involved in designing interfaces, facilitator’ tools, training programs, conducting controlled experimentation, testing, and evaluating human behavioral performance in operations in order to foreseeing potential errors and eliminating safety hazards?

4)  To what extent are tailor-made task analysis, foreseeable errors analysis, and decision flow diagrams in every stage of the development process computerized as expert systems, and how embedded is the role of experts in reviewing computer outputs?

5) Could you give us a few samples of the kind of expert opinions that NASA still seek in system development? What are the impacts of expert opinions in the development cycle and how critical are they? On what system do you rely in decisions concerning the allocation of tasks to either operators or automation?

6)  Do you think that NASA has already accumulated an exhaustive list of cognitive and physical capabilities/limitations of human operators compared to machine potentials?  How efficient is a human operator currently evaluated within this growing trend in technology and automation?  What kind of guidelines does NASA engineers rely on for designing interfaces or anything that requires operators’ interactions with the system?

7) What types of inspectors do you mostly hire, such as technical versus people oriented? Would your guidelines for hiring technical or people performance inspectors differ (for example in-house hiring or outside contracting)?  Is assigning an employee to inspection jobs is generally viewed by engineers as a negative coded message for position downgrading?”

On June 4, I received the following reply from Eachy:

“Dear Adonis, my response to your questions will not be in the direct order because our work here is not a production activity.

Each spacecraft is different and they are always first of a kind.  However, we do have a system of checks and balances.

We have one organization which does the design and development (about 3,500 technical people) and a separate organization which does Quality Control (about 350 technical people).

The role of QC is not only to check on the quality of the work, but also to help the development organization do it right to start with.  So, we assign a few QC experts to each project, but they report through a different chain than the project manager.

When we have a problem we try to understand the root cause and develop procedure/training to avoid it in the future.

We do not try to blame a person but we put a number of reviews and independent checks to make sure problems don’t slip through the cracks.”

I read Professor Elachy’s response to class.  It was clear that Human Factors professionals are still viewed as more relevant in the production activity phase, although there are many cases where they were involved in analyzing missions from their inception, knowing that NASA pioneered the process of hiring Human Factors in the agency.

Update 1:Professor Elachy was awarded this year 2011, the French highest order in scientific achievement. He had done his highest studies in France before Charles Elachy was hired in the USA.

Update 2: Charles Elachy is the head of the team that landed the rover on Mars to find out if there is life on this hot planet

Article #42  (April 6, 2006)

 “New semester, new approach to teaching the HF course”

This semester ten students enrolled for my class; only one is a computer engineer finishing his degree and the remaining are industrial engineers.  As a reminder, this course is required for IE and the other engineering disciplines managed to open up new elective courses and were trying to market them at the expense of the wishes of many students who wanted to take my course and their petitions were denied.

With a class, one fourth its usual number, I had to capitalize on the advantages of smaller classes, once the shock is under control.  This semester, methods applied in human factors engineering are the focus and the reduction to half the previous semester of body of knowledge in the course materials might encourage my class to appreciate the efforts and time invested by the pool of human factors researchers and professionals to make available practical design guidelines for the other engineering professions.

Whereas in the previous semesters I shun away from exposing my class to new methods, except teaching them explicitly the concept of controlled experimentations, the differences among dependent, independent and controlled variables and correcting their misunderstanding, thinking that there was an abundance of knowledge to assimilate for a meager semester, I boldly changed direction in my teaching approach by investing more time on exposing and explaining the various methods that human factors might be applying in their profession.  The first assignment was using excel to compare 40 methods used in human factors, industrial engineering, industrial psychology, and designers of intelligent machines.  This assignment was a version of article #14, about the taxonomy of methods, from 20 articles that I wrote the previous years and offered them as an introduction to the course, in addition to the course materials. The students were supposed to select five categories from more than the dozen ways to classifying methods such as definition, purpose, applications, inputs, processes, procedures, output/product, mathematical requirements, disciplines teaching them, advantages, disadvantages, sources/links, connections with other methods, and comments.

I expected that, as engineers, they would logically select for columns applications, input, procedure, output, and comments because they are what define a method but somehow they opted for applications, procedures, advantages, disadvantages, and comments mainly because it is how the internet offer information.  After 3 students submitted their assignment on time I handed them over 40 summary sheets for the 16 methods used to analyzing a system or a mission, at least 2 sheets for each of 16 methods, one sheet on the purpose, input, procedure, and output/product of the method and the other sheets as examples of what the output is expected to look for presentation. I then asked the less performing students to concentrate on only the 16 methods for their assignment and most of them did not submit this assignment even two months later.

So far I used up six sessions for methods or related topics such as the methods applied in the process of analyzing systems’ performance, psychophysical procedures, the fundamentals of controlled experimentation methods, human factors performance criteria, and what human factors measure in their experiments. 

As for the body of knowledge I extract a few facts from experiments and asked them to participate in providing me with the rationales or processes that might explain these facts. For example, if data show that females on average are two third the strength of males then what could be the underlying causes for that discovery?  Could that fact be explained by the length of the muscles, the cross section thickness of the muscles, the number of muscle fibers, or the length of the corresponding bones?

Facts are entertaining but I figured that they are big boys to be constantly entertained while shovelful of money is being spent for their university education. Facts are entertaining but there have to come a time when these big boys stop and wonder at the brain power, Herculean patience, and hard work behind these amusing sessions.

The next assignment was to observe the business of the family’s bread earner, note down the minute tasks of his typical day work, learn about the business by attempting to generate detailed answers from a questionnaire they have to develop based on a set of investigative query and problems related to human factors performance criteria in the assignment sheet, and to report back what are the routine and daily tasks that enabled the students to join a university.  Three students worked with their fathers’ in summer times and enjoyed the assignment; the remaining students could not shake off their 8th grade habits, wrote the questionnaire, mailed it, and waited for the answers.  I was expecting that the students would apply the methodology they learned in analyzing systems such as activity, decision, and task analyses but the good stuff was not forthcoming. To encourage them to cater to the business that they might inherit, I assigned them a lecture project that would generate the requisite analyses with a clear objective of focusing on near-accidents, foreseeable errors, safety of the workers and heath conditions in the work place.

So far, the products of the two quizzes were complete failures; although most of the questions in the second quiz were from the same chapter sources as the first quiz, it is amazing how ill prepared are the students for assimilating or focusing on the essential ideas, concepts, and methods. So far, with a third of the semester over, I can points to only two students who are delivering serious investment in time, hard work, and excitement and are shooting for a deserved grade of A.

Article #35 (Started March 4, 2006)

 “Efficiency of the human body structure”

This article is an on going project to summarize a few capabilities and limitations of man. While the most sophisticated intelligent machines invented by man may contain up to ten thousand elements, the human machine is constituted of up to a million trillion of cells, up to a thousand trillions of neurons in the central nervous system, about a couple hundred bones, and as many organs, muscles, tendons and ligaments.

In the previous article #33 we discussed a graph in a story style and discovered that a human barefoot in texture, shape, and toes has a higher coefficient of friction than many man-made shoes that allow easier traction to move forward for less energy expenditure. We also expanded our story to observe that the structure of the bones and major muscles attached to limbs for movements as lever systems provide higher speed and range of movements at the expense of exorbitant muscular efforts.

A most important knowledge for designing interfaces is a thorough recognition of the capabilities and limitations of the five senses.  One of the assignment involves comparing the various senses within two dozens categories such as: anatomy, physiology, receptor organs, stimulus, sources of energy, wave forms, reaction time, detectable wavelengths and frequencies, practical detection thresholds of signals, muscles, physical pressure, infections and inflammations, disorders and dysfunctions, assessment, diagnostic procedures, corrective measures, effects of age, and safety and risk.

Human dynamic efforts for doing mechanical work is at best 30% efficient because most of the efforts are converted to maintaining static positions in order to preserve stability and equilibrium for all the other concomitant stabilizing joints, bones and muscles.  For example, the stooping position consumes 60% of the efforts for having a work done, in addition to the extremely high moment effected on the edges of the lower back intervertebrae discs.  Static postures constrict the blood vessels and fresh blood is no longer carrying the necessary nutrients to sustain any effort for long duration and heart rate increases dramatically; lactic acid accumulates in the cells and fatigue ensues until the body rests in order to break down that acid.

Human energy efficiency is even worse because most of the energy expended is converted into heat.  Not only physical exercises generate heat but, except for glucose or sugar, most of the nutrients have to undergo chemical transformations to break down the compounds into useful and ready sources of energy, thus generating more heat.  Consequently, heat is produced even when sleeping when the body cells are regenerated. Internal heat could be a blessing in cold environments but a worst case scenario in a hot atmosphere because the cooling mechanism in human is solely confined to sweating off the heat accumulated in the blood stream.  Heat is a source of blessing when we are sick with microbes and bacteria because the latter is killed when the internal body temperature rises above normal.

 “How to tell long and good stories from human factors graphs?”

Article #33, (Feb. 28, 2006)

If we concentrate on a graph we might generate a long story that span many disciplines and furnish us with a wealth of information and knowledge that pages of words barely can convey. A graph might open the gate for dozen of questions that are the foundation of scientific, experimental, and critical thinking.

Suppose that we are comparing the efficiency in energy consumption between walking bare feet or wearing shoes that weight 1.3 Kg.  Considering the walking speed as the other independent variable, along with the type and weight of shoes, we observe that the curves show that we are consuming less energy at low speed, then both curves decreasing to a minimum consumption of 0.2 KJ/Nm and intersecting at around 80 meter/min and then increasing as walking speed increases.

This graph is telling us that casual walking consumes less energy per unit walking effort than fast walking and that, at a cut off speed of 80 meter/min, the energy consumption is equal for both foot wares.  Some people might jump to the conclusion that this cut-off speed can be generalized to all foot wears, but more experiments are necessarily needed to verify this initial hypothesis.

Another piece of information is that after the cut-off speed, it is more economical in energy to walk barefoot. Basically, this graph is saying that the more weight you add to your lower limbs the more energy you should expect to spend, a fact that is not an earth shattering observation.

Biomechanics tells us that the structure of our body is not geared toward saving on our muscular effort, but to increasing our range and speed of movements.  Most of our muscles are connected to the bones of our limbs and their respective joints in manners they have to exert great effort and many fold the weight of our body members to overcome any of our limb’s mass.

Usually, the tendons of our muscles are inserted to the limb bones, close to the joints, and thus the muscles have to exert a huge effort to overcome the moment of the bone and flesh weight in order to effect a movement. Any extra mass to our limbs will tax our muscles to produce many folds the additional weight.

There is a caveat however; if you wrapped a weight of 1.3 kg around your ankles and walked bare feet you would consume more energy than without the added weight, but the curve would be parallel to the previous curve and not increasing more steepily than walking with shoes weighting 1.3 Kg.  Consequently, the variation in the behavior of the graphs result from a combination of added weight and lesser static coefficient of friction exerted by the shoes on the walking surface than the bare foot..

Thus, what this graph does not mention is the static coefficient of friction between the footwear and the ground, and which is the most important variable and in this case, can concatenate many independent and control variables such as the materials of the footwear and the type of ground into a unique independent variable of coefficient of friction.

The higher the coefficient of friction the easier it is to move and progress and thus walking faster for the same amount of effort invested.  It is not that important to generate muscle force if the reaction force on the surface cannot be produced to move a person in the right direction.  For example, it is extremely difficult to move on slippery surfaces no matter how much muscular effort we generate.  Apparently, the shape and skin texture of our foot provide a better and more efficient coefficient of friction than most foot wears.

However, the most important fact of this simple experiment is showing us the behavior of the curves and offering additional hypotheses for other studies.

What this graph is not telling us is the best story of all, and which can excite the mind into further investigation. For example, what kind of earth materials are we walking on; sands, asphalt, rough terrains, slippery roads or grassy fields?  Does the sample of bare feet walkers include aboriginals used in walking bare feet, city dwellers, and people from the province?  Does the sample includes groups of  people according to the softness of their feet skins or the size of feet?

May be the shape of the curves are the same for females as well, but it would be curious to find out the magnitude of variations compared to males.  It is clear that a simple and lousy graph delved us into the problems of experimentation and raised enough questions to attend to various fields of knowledge.

In the final analysis, the question is how relevant is this experiment practically?  How far can a modern man walk bare feet?  Does any economy in energy compensate for the ache, pain and injuries suffered by walking bare feet?  Would athletes be allowed to compete bare feet if it is proven to increase performance and break new records?  Does anyone care of walking barefoot in order to save a few kilo Joules?

The theme of this article is that you can venture into many fields of knowledge, just by focusing your attention on graphs and tables and permitting your mind to navigate into uncharted waters through queries and critical thinking.



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.


“A few anecdotes of my teaching methods” 

(Article #17 in the category of Human Factors, written on April 13, 2005)

My composite class of all engineering disciplines takes my course in Human Factors in engineering for different reasons. It is a required course to the industrial engineers, but optional to all the others.

You assume that most university students have discussed with the previous students about the contents, difficulty, novelty and time consuming constraints of this course.

Apparently, the responses generated in class to my query whether the students have any idea about this course prove that they have no knowledge whatsoever of Human Factors discipline, which is to design products and services with health, safety, and ease of use of consumers in mind.

I prompt them by mentioning the term ergonomics, and lo and behold, they have read this term somewhere in ads on ergonomically designed chairs and keyboards.

Another surprise is that when it comes to purchasing course materials and answering old questions in assignments, many succeed in locating previous students who took the course.

I have tried many teaching styles, revised several times the contents and arrangements of the course chapters, and experimented with various methods to encourage the students into reading the course materials on their own volition.

I varied the number of quizzes, exams, assignments and lab projects, tried to encourage them to read research articles, investigated new presentation techniques, gave them hints on how best to read and assimilate the materials, emphasized on thinking like engineers and not memorize information, and I assigned students to read to the class:  I received basically the same observations, no matter how I change the course.

1.Engineering students will read only under duress,

2. Will barely take notes even if bonus points are at stakes,

3. Will start an assignment a couple of days before due date, even if the assignment was handed out several weeks prior to due date,

4. Will remember to ask for clarifications only on due date,

5. Will copy and cheat unabashedly.

Engineering students refuse to carry to class any course material, unless the exam is an open book.

Many don’t bring any paper or pen to take notes, many refuse to redo their assignments for a couple extra points or for closure sake, and most of the redone works show no improvement.

Students can use word processors or any computer applications for their assignments, but the end product has to be hand written, including tables, charts and figures. Guess why I figured out this constraints?

It turned out that my guess was correct: most of the time I can manage to read physicians’ prescriptions better than their handwriting assignment.

There was a time when engineers were trained to submit neat drawings, as engineers should be trained to do, but this time is long gone.

Another advantage of submitting hand written work is that students will actually read what they are writing and rely less on copied CD’s and try their hands on being neat, using rulers, compasses and the long lost engineering working components.

I invented several ways to brute force students to read at least parts of the course materials.

In addition to mid-term and final exams, they have to answer dozens of questions for their mid-term and final take homes exams.

I assign graphs, tables and figures to students to hand write, copy on transparent sheets and present to class with written explanation attached.

All assignments are submitted on composition booklets.

I encourage them to take notes by asking them questions on materials not covered in the course materials, and giving bonuses to anyone who remember to provide a copy of his notes on final day.

I have come to realize that any zest I invest in teaching is for just a couple of students each semesters.

Yes, there is this couple of students who demonstrate this want to learn: it is always refreshing to feel that a few students are serious about the money invested by their parents for them to learn at universities.




October 2008

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