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detail production design

  • 1 рабочий проект

    Рабочий проект-- They carry out the conceptual design of each new batch of rolling stock and its systems, although the detail production design is done by the manufacturers.

    Русско-английский научно-технический словарь переводчика > рабочий проект

  • 2 рабочий проект

    contractor design, detail(ed) design, production project
    * * *

    Русско-английский политехнический словарь > рабочий проект

  • 3 план

    design, draft, drawing, skeleton, ( обычно генеральный) layout строит., outline, plan, plot, program, project, projection, scheme
    * * *
    план м.
    plan
    составля́ть план — draw up a plan
    уточни́ть план — refine [revise] the plan
    план в горизонта́лях геод., картогр. — contour plan
    вентиляцио́нный план горн. — ventilation layout, ventilation scheme
    генера́льный план — master plot plan, general layout
    грузово́й план — cargo [loading, stowage] plan
    за́дний план кфт. — background
    кру́пный план кфт. — close-up, close shot
    маркше́йдерский план горн. — surveying plan
    о́бщий план кфт. — long shot
    ориентацио́нный план стр. — key plan
    пере́дний план кфт. — foreground
    перспекти́вный план эк. — long-term plan
    план полё́та — flight plan
    аннули́ровать [отменя́ть] план полё́та — cancel a flight plan
    произво́дственный план — production plan
    план рабо́т — work schedule
    рабо́чий план — working plan
    план расположе́ния обору́дования — equipment layout
    план распределе́ния часто́т свз. — (radio-)frequency plan
    план расстано́вки ваго́нного па́рка горн. — rolling stock plan
    план скоросте́й (центробежных вентиляторов, компрессоров) — velocity diagram
    план скоросте́й на вхо́де — inlet velocity diagram
    план скоросте́й на вы́ходе — outlet-velocity diagram
    сре́дний план кфт. — medium shot
    схемати́ческий план — diagrammatic plan
    план телефо́нной се́ти — exchange area layout
    укрупнё́нный план — ontime plan
    уточнё́нный план — detail plan
    план экспериме́нта — design of an experiment
    план экспериме́нта, композицио́нный — composite design
    план экспериме́нта, после́довательный — sequential design
    план экспериме́нта, фа́кторный — factorial design
    план экспериме́нта, фа́кторный по́лный — full factorial design
    план экспериме́нта, части́чный — fractional factorial design
    план экспериме́нта 2k — full two-level factorial experiment, 2k design
    эски́зный план — sketch plan
    * * *

    Русско-английский политехнический словарь > план

  • 4 производственный чертеж

    Авиация и космонавтика. Русско-английский словарь > производственный чертеж

  • 5 disminuir

    v.
    1 to reduce.
    2 to decrease.
    El medicamento disminuyó la fiebre The drug decreased the fever.
    Me disminuyó la temperatura My temperature decreased.
    3 to diminish, to decrease, to fall off, to drop off.
    El calor disminuyó The heat diminished.
    4 to lessen, to take down, to humiliate, to deflate.
    Su actitud disminuyó a su hijo His attitude lessened his son.
    5 to have less.
    Te disminuyó la fiebre You have less fever.
    * * *
    Conjugation model [ HUIR], like link=huir huir
    1 (gen) to decrease
    2 (medidas, velocidad) to reduce
    1 (gen) to diminish
    2 (temperatura, precios) to drop, fall
    * * *
    verb
    2) drop, fall
    * * *
    1. VT
    1) (=reducir) [+ nivel, precio, gastos, intereses] to reduce, bring down; [+ riesgo, incidencia, dolor] to reduce, lessen; [+ temperatura] to lower, bring down; [+ prestigio, autoridad] to diminish, lessen; [+ fuerzas] to sap; [+ entusiasmo] to dampen

    algunos bancos han disminuido en un 0,15% sus tipos de interés — some banks have reduced o brought down their interest rates by 0.15%

    disminuyó la velocidad para tomar la curva — she slowed down o reduced her speed to go round the bend

    2) (Cos) [+ puntos] to decrease
    2. VI
    1) (=decrecer) [número, población] to decrease, drop, fall; [temperatura, precios] to drop, fall; [distancia, diferencia, velocidad, tensión] to decrease; [fuerzas, autoridad, poder] to diminish; [días] to grow shorter; [luz] to fade; [prestigio, entusiasmo] to dwindle

    el paro disminuyó en un 0,3% — unemployment dropped o fell by 0.3%

    2) (=empeorar) [memoria, vista] to fail
    3) (Cos) [puntos] to decrease
    * * *
    1.
    verbo intransitivo
    1) ( menguar) número/cantidad to decrease, drop, fall; entusiasmo/interés to wane, diminish; precios/temperaturas to drop, fall; poder/fama to diminish; dolor to diminish, lessen
    2) ( al tejer) to decrease
    2.
    1) ( reducir) <gastos/costos/impuestos> to reduce, cut; < velocidad> to reduce; <número/cantidad> to reduce, diminish
    2) ( al tejer) < puntos> to decrease
    * * *
    = decline, decrease, diminish, dwindle, fall off, reduce, relax, shrink, slow down, tail off, lower, dip, subside, mitigate, lessen, abate, decelerate, regress, wane, take + a dive, ebb, slacken, whittle (away/down/at), slow up, taper, scale back, remit, take + a dip, turn down.
    Ex. Library use declines during the June-October period when examinations have finished and the students are on vacation.
    Ex. Recall is inversely proportional to precision, and vice versa, or in other words, as one increases, the other must decrease.
    Ex. While another colleague of mine offered the wry comment that 'as the computer's capabilities have increased our expectations of what it can do have proportionally diminished'.
    Ex. Whereas this proportion is dwindling as a percentage of the total budget, agricultural spending continues to rise in real terms.
    Ex. When the recording procedures were removed study time fell off immediately.
    Ex. The disadvantage of inversion of words is that inversion or indirect word order reduces predictability of form of headings.
    Ex. Since the Federal Government has not been willing to relax import restrictions on books, academic librarians have had to devise a number of strategies for the survival of collection development.
    Ex. The 'false hit' problem still arises, but becomes less likely as the 'neighborhood' of the two words shrinks.
    Ex. However, the flight from DC appears to have slowed down more quickly than was anticipated, and we no longer read of large numbers of libraries making the change.
    Ex. In this unsettled atmosphere, it is not surprising that enthusiasm for membership of the Community should tail off.
    Ex. When a forme was in place on the press stone, paper was lowered on to it by means of a tympan and frisket.
    Ex. The proportions of books bought for children have been extraordinarily steady for four of the five years, only dipping at all appreciably in the last year of 1979-80.
    Ex. Her agitation subsided suddenly.
    Ex. Confusion caused by repetition of descriptive information in access points can be mitigated by careful screen design.
    Ex. Two possible solutions are possible: (1) to lessen the frequency of production, or (2) to reduce the amount of detail in the entries.
    Ex. As the sobbing abated, the secretary's voice regained some steadiness.
    Ex. Accumulation of new data bases is decelerating rapidly with the focus on deriving subsets from current files to serve niche markets.
    Ex. Interloans have regressed recently, despite the rapid advancement of the computer age.
    Ex. The population waxed again slightly, then waned again, until it finally stabilized around its present 55,000.
    Ex. The article 'Wages, hours, bookfunds take a dive' examines how some authorities are proposing cuts in wages to preserve services; others reducing bookfunds by as much as a quarter, or cutting their opening hours in half.
    Ex. Subsequently, library development stalled as cultural interaction ebbed from classical levels.
    Ex. The trend direct supply of books to schools shows no sign of slackening.
    Ex. However, such idealism is often whittled away over time by bureaucratic problems & organizational demands.
    Ex. Since cataloging is the most time consuming part of digitization, it has slowed up the placement of files.
    Ex. The tube in the two types tapers almost unnoticeably from base to tip.
    Ex. He first spotted trouble when she started being short with users and so he solved the problem by scaling back her workload.
    Ex. The fever was resolved and the skin lesions started to remit during the following 3 weeks.
    Ex. Sales took a dip in 2005 but exploded in 2006.
    Ex. Cytokines are small proteins used to communicate messages between the immune cells in the immune system to either turn up or down the immune response.
    ----
    * atención + disminuir = attention + wane.
    * disminuir casi hasta su desaparación = drop to + near vanishing point.
    * disminuir de tamaño = dwindle in + size.
    * disminuir el riesgo = reduce + risk.
    * disminuir el valor de = belittle.
    * disminuir la importancia de = lessen + the importance of.
    * disminuir la marcha = slow down.
    * disminuir la posibilidad = lessen + possibility.
    * disminuir la probabilidad = reduce + chances.
    * disminuir las probabilidades = lengthen + the odds.
    * disminuir la velocidad = slow up.
    * sin disminuir = non-decreasing, unabated.
    * * *
    1.
    verbo intransitivo
    1) ( menguar) número/cantidad to decrease, drop, fall; entusiasmo/interés to wane, diminish; precios/temperaturas to drop, fall; poder/fama to diminish; dolor to diminish, lessen
    2) ( al tejer) to decrease
    2.
    1) ( reducir) <gastos/costos/impuestos> to reduce, cut; < velocidad> to reduce; <número/cantidad> to reduce, diminish
    2) ( al tejer) < puntos> to decrease
    * * *
    = decline, decrease, diminish, dwindle, fall off, reduce, relax, shrink, slow down, tail off, lower, dip, subside, mitigate, lessen, abate, decelerate, regress, wane, take + a dive, ebb, slacken, whittle (away/down/at), slow up, taper, scale back, remit, take + a dip, turn down.

    Ex: Library use declines during the June-October period when examinations have finished and the students are on vacation.

    Ex: Recall is inversely proportional to precision, and vice versa, or in other words, as one increases, the other must decrease.
    Ex: While another colleague of mine offered the wry comment that 'as the computer's capabilities have increased our expectations of what it can do have proportionally diminished'.
    Ex: Whereas this proportion is dwindling as a percentage of the total budget, agricultural spending continues to rise in real terms.
    Ex: When the recording procedures were removed study time fell off immediately.
    Ex: The disadvantage of inversion of words is that inversion or indirect word order reduces predictability of form of headings.
    Ex: Since the Federal Government has not been willing to relax import restrictions on books, academic librarians have had to devise a number of strategies for the survival of collection development.
    Ex: The 'false hit' problem still arises, but becomes less likely as the 'neighborhood' of the two words shrinks.
    Ex: However, the flight from DC appears to have slowed down more quickly than was anticipated, and we no longer read of large numbers of libraries making the change.
    Ex: In this unsettled atmosphere, it is not surprising that enthusiasm for membership of the Community should tail off.
    Ex: When a forme was in place on the press stone, paper was lowered on to it by means of a tympan and frisket.
    Ex: The proportions of books bought for children have been extraordinarily steady for four of the five years, only dipping at all appreciably in the last year of 1979-80.
    Ex: Her agitation subsided suddenly.
    Ex: Confusion caused by repetition of descriptive information in access points can be mitigated by careful screen design.
    Ex: Two possible solutions are possible: (1) to lessen the frequency of production, or (2) to reduce the amount of detail in the entries.
    Ex: As the sobbing abated, the secretary's voice regained some steadiness.
    Ex: Accumulation of new data bases is decelerating rapidly with the focus on deriving subsets from current files to serve niche markets.
    Ex: Interloans have regressed recently, despite the rapid advancement of the computer age.
    Ex: The population waxed again slightly, then waned again, until it finally stabilized around its present 55,000.
    Ex: The article 'Wages, hours, bookfunds take a dive' examines how some authorities are proposing cuts in wages to preserve services; others reducing bookfunds by as much as a quarter, or cutting their opening hours in half.
    Ex: Subsequently, library development stalled as cultural interaction ebbed from classical levels.
    Ex: The trend direct supply of books to schools shows no sign of slackening.
    Ex: However, such idealism is often whittled away over time by bureaucratic problems & organizational demands.
    Ex: Since cataloging is the most time consuming part of digitization, it has slowed up the placement of files.
    Ex: The tube in the two types tapers almost unnoticeably from base to tip.
    Ex: He first spotted trouble when she started being short with users and so he solved the problem by scaling back her workload.
    Ex: The fever was resolved and the skin lesions started to remit during the following 3 weeks.
    Ex: Sales took a dip in 2005 but exploded in 2006.
    Ex: Cytokines are small proteins used to communicate messages between the immune cells in the immune system to either turn up or down the immune response.
    * atención + disminuir = attention + wane.
    * disminuir casi hasta su desaparación = drop to + near vanishing point.
    * disminuir de tamaño = dwindle in + size.
    * disminuir el riesgo = reduce + risk.
    * disminuir el valor de = belittle.
    * disminuir la importancia de = lessen + the importance of.
    * disminuir la marcha = slow down.
    * disminuir la posibilidad = lessen + possibility.
    * disminuir la probabilidad = reduce + chances.
    * disminuir las probabilidades = lengthen + the odds.
    * disminuir la velocidad = slow up.
    * sin disminuir = non-decreasing, unabated.

    * * *
    vi
    A (menguar) «número/cantidad» to decrease, drop, fall; «desempleo/exportaciones/gastos» to decrease, drop, fall; «entusiasmo» to wane, diminish; «interés» to wane, diminish, fall off
    el número de fumadores ha disminuido the number of smokers has dropped o fallen o decreased
    los impuestos no disminuyeron there was no decrease o cut in taxes
    los casos de malaria han disminuido there has been a drop o fall o decrease in the number of malaria cases
    disminuyó la intensidad del viento the wind died down o dropped
    la agilidad disminuye con los años one becomes less agile with age
    B (al tejer) to decrease
    ■ disminuir
    vt
    A (reducir) ‹gastos/costos› to reduce, bring down, cut
    disminuimos la velocidad we reduced speed
    es un asunto muy grave y se intenta disminuir su importancia it is a very serious matter, and its importance is being played down
    el alcohol disminuye la rapidez de los reflejos alcohol slows down your reactions
    B (al tejer) ‹puntos› to decrease
    * * *

     

    disminuir ( conjugate disminuir) verbo intransitivo ( menguar) [número/cantidad] to decrease, fall;
    [precios/temperaturas] to drop, fall;
    [ dolor] to diminish, lessen
    verbo transitivo ( reducir) ‹gastos/producción› to cut back on;
    ‹ impuestos› to cut;
    ‹velocidad/número/cantidad› to reduce
    disminuir
    I verbo transitivo to reduce: esto disminuye sus probabilidades de entrar en la Universidad, this lowers his chances of admission to the University
    II verbo intransitivo to diminish: el calor ha disminuido, the heat has lessened
    ' disminuir' also found in these entries:
    Spanish:
    aclararse
    - atenuar
    - bajar
    - descender
    - enfriar
    - perder
    - rebajar
    - reducir
    - reducirse
    - velocidad
    English:
    cut back
    - decline
    - decrease
    - die down
    - diminish
    - drop
    - dwindle
    - ease off
    - ease up
    - lessen
    - lower
    - odds
    - reduce
    - shrink
    - sink
    - slacken
    - slacken off
    - taper off
    - thin out
    - abate
    - ease
    - flag
    - go
    - let
    - tail
    - taper
    - wane
    * * *
    ♦ vt
    to reduce, to decrease;
    disminuye la velocidad al entrar en la curva reduce speed as you go into the curve;
    pastillas que disminuyen el sueño tablets that prevent drowsiness;
    la lesión no ha disminuido su habilidad con el balón the injury hasn't affected his skill with the ball
    ♦ vi
    [cantidad, velocidad, intensidad, contaminación] to decrease, to decline; [desempleo, inflación] to decrease, to fall; [precios, temperatura] to fall, to go down; [vista, memoria] to fail; [interés] to decline, to wane;
    no disminuye la euforia inversora investor enthusiasm continues unabated
    * * *
    I v/t gastos, costos reduce, cut; velocidad reduce
    II v/i decrease, diminish
    * * *
    disminuir {41} vt
    reducir: to reduce, to decrease, to lower
    1) : to lower
    2) : to drop, to fall
    * * *
    1. (reducir) to reduce
    2. (bajar, menguar) to fall [pt. fell; pp. fallen] / to drop [pt. & pp. dropped]

    Spanish-English dictionary > disminuir

  • 6 расчёт

    1) General subject: account (lay (one's) account with something - рассчитывать на что-либо), accounting, arithmetic (ы), calculation, clearing-off, computation, consideration, design, detachment, dismissal, economy, estimation, expectation, gunners, intention, payment, prediction, providence, reckoning, reckoning (тж. перен.), sack (увольнение), settlement, (например технических требований или данных) quotation, accountance, rationale
    2) Computers: count
    4) Medicine: billing
    5) Military: advantage, counting off (при построении), crew, detachment (орудия, миномёта), estimate, gun crew, gun section, manning detail (огневого средства), operating personnel, section, squad, squad section, team
    6) Engineering: analysis (обычно проверочный), computing, designing, sizing, valuation
    7) Professional term: dismissal pay
    8) Mathematics: anal (analysis), the reckoning of
    11) Accounting: making-up
    12) Finances: (по платежам) settlement (в отличие от calculation - расчёт, определение. вычисление ( какого-либо показателя))
    13) Australian slang: tick
    14) Architecture: ultimate load design
    15) Psychology: guessing
    17) Information technology: acct, bill, calculating, invoice
    18) Oil: reliance
    19) Astronautics: figuring
    21) Business: final pay, making up
    22) Drilling: dimensioning
    23) EBRD: clearance
    24) Automation: calculus
    27) leg.N.P. voucher
    28) Makarov: analysis (определение напряжений, деформаций, внутр. сил, моментов, условий жёсткости в имеющейся конструкции), calculation (вычисления), calculations (вычисления), computation (вычисления), computations (вычисления), consideration (рассмотрение), design (подбор сечений и др. размеров реальной конструкции при заданных напряжениях, моментах и т.п.), manning detail (огневого средства и т.п.), solution, solution (решение)
    29) SAP.tech. settl.
    30) SAP.fin. settlmt
    31) oil&gas: fire team

    Универсальный русско-английский словарь > расчёт

  • 7 McCormick, Cyrus

    [br]
    b. 1809 Walnut Grove, Virginia, USA
    d. 1884 USA
    [br]
    American inventor of the first functionally and commercially successful reaping machine; founder of the McCormick Company, which was to become one of the founding companies of International Harvester.
    [br]
    Cyrus McCormick's father, a farmer, began to experiment unsuccessfully with a harvesting machine between 1809 and 1816. His son took up the challenge and gave his first public demonstration of his machine in 1831. It cut a 4 ft swathe, but, wanting to perfect the machine, he waited until 1834 before patenting it, by which time he felt that his invention was threatened by others of similar design. In the same year he entered an article in the Mechanics Magazine, warning competitors off his design. His main rival was Obed Hussey who contested McCormick's claim to the originality of the idea, having patented his own machine six months before McCormick.
    A competition between the two machines was held in 1843, the judges favouring McCormick's, even after additional trials were conducted after objections of unfairness from Hussey. The rivalry continued over a number of years, being avidly reported in the agricultural press. The publicity did no harm to reaper sales, and McCormick sold twenty-nine machines in 1843 and fifty the following year.
    As the westward settlement movement progressed, so the demand for McCormick's machine grew. In order to be more central to his markets, McCormick established himself in Chicago. In partnership with C.M.Gray he established a factory to produce 500 harvesters for the 1848 season. By means of advertising and offers of credit terms, as well as production-line assembly, McCormick was able to establish himself as sole owner and also control all production, under the one roof. By the end of the decade he dominated reaper production but other developments were to threaten this position; however, foreign markets were appearing at the same time, not least the opportunities of European sales stimulated by the Great Exhibition in 1851. In the trials arranged by the Royal Agricultural Society of England the McCormick machine significantly outperformed that of Hussey's, and as a result McCormick arranged for 500 to be made under licence in England.
    In 1874 McCormick bought a half interest in the patent for a wire binder from Charles Withington, a watchmaker from Janesville, Wisconsin, and by 1885 a total of 50,000 wire binders had been built in Chicago. By 1881 McCormick was producing twine binders using Appleby's twine knotter under a licence agreement, and by 1885 the company was producing only twine binders. The McCormick Company was one of the co-founders of the International Harvester Company in 1901.
    [br]
    Bibliography
    1972, The Century of the Reaper, Johnson Reprint (the original is in the New York State Library).
    Further Reading
    Graeme Quick and Wesley Buchele, 1978, The Grain Harvesters, American Society of Agricultural Engineers (deals in detail with McCormick's developments).
    G.H.Wendell, 1981, 150 Years of International Harvester, Crestlink (though more concerned with the machinery produced by International Harvester, it gives an account of its originating companies).
    T.W.Hutchinson, 1930, Cyrus Hall McCormick, Seedtime 1809–1856; ——1935, Cyrus Hall McCormick, Harvest 1856–1884 (both attempt to unravel the many claims surrounding the reaper story).
    Herbert N.Casson, 1908, The Romance of the Reaper, Doubleday Page (deals with McCormick, Deering and the formation of International Harvester).
    AP

    Biographical history of technology > McCormick, Cyrus

  • 8 рабочий чертёж

    1) General subject: working plan
    2) Aviation: workshop drawing
    6) Geophysics: blueprint
    7) Business: equipment drawing
    8) Oilfield: design drawing

    Универсальный русско-английский словарь > рабочий чертёж

  • 9 рабочий чертеж

    1) General subject: working plan
    2) Aviation: workshop drawing
    6) Geophysics: blueprint
    7) Business: equipment drawing
    8) Oilfield: design drawing

    Универсальный русско-английский словарь > рабочий чертеж

  • 10 Breuer, Marcel Lajos

    [br]
    b. 22 May 1902 Pécs, Hungary
    d. 1 July 1981 New York (?), USA
    [br]
    Hungarian member of the European Bauhaus generation in the 1920s, who went on to become a leader in the modern school of architectural and furniture design in Europe and the United States.
    [br]
    Breuer began his student days following an art course in Vienna, but joined the Bauhaus at Weimar, where he later graduated, in 1920. When Gropius re-established the school in purpose-built structures at Dessau, Breuer became a member of the teaching staff in charge of the carpentry and furniture workshops. Much of his time there was spent in design and research into new materials being applied to furniture and interior decoration. The essence of his contribution was to relate the design of furniture to industrial production; in this field he developed the tubular-steel structure, especially in chair design, and experimented with aluminium as a furniture material as well as pieces of furniture made up from modular units. His furniture style was characterized by an elegance of line and a careful avoidance of superfluous detail. By 1926 he had furnished the Bauhaus with such furniture in chromium-plated steel, and two years later had developed a cantilevered chair.
    Breuer left the Bauhaus in 1928 and set up an architectural practice in Berlin. In the early 1930s he also spent some time in Switzerland. Notable from these years was his Harnischmacher Haus in Wiesbaden and his apartment buildings in the Dolderthal area of Zurich. His architectural work was at first influenced by constructivism, and then by that of Le Corbusier (see Charles-Edouard Jeanneret). In 1935 he moved to England, where in partnership with F.R.S. Yorke he built some houses and continued to practise furniture design. The Isokon Furniture Co. commissioned him to develop ideas that took advantage of the new bending and moulding processes in laminated wood, one result being his much-copied reclining chair.
    In 1937, like so many of the European architectural refugees from Nazism, he found himself under-occupied due to the reluctance of English clients to embrace the modern architectural movement. He went to the United States at Gropius's invitation to join him as a professor at Harvard. Breuer and Gropius were influential in training a new generation of American architects, and in particular they built a number of houses. This partnership ended in 1941 and Breuer set up practice in New York. His style of work from this time on was still modern, but became more varied. In housing, he adapted his style to American needs and used local materials in a functional manner. In the Whitney Museum (1966) he worked in a sculptural, granite-clad style. Often he utilized a bold reinforced-concrete form, as in his collaboration with Pier Luigi Nervi and Bernard Zehrfuss in the Paris UNESCO Building (1953–8) and the US Embassy in the Hague (1954–8). He displayed his masterly handling of poured concrete used in a strikingly expressionistic, sculptural manner in his St John's Abbey (1953–61) in Collegeville, Minnesota, and in 1973 his Church of St Francis de Sale in Michigan won him the top award of the American Institute of Architects.
    [br]
    Principal Honours and Distinctions
    American Institute of Architects Medal of Honour 1964, Gold Medal 1968. Jefferson Foundation Medal 1968.
    Bibliography
    1955, Sun and Shadow, the Philosophy of an Architect, New York: Dodd Read (autobiography).
    Further Reading
    C.Jones (ed.), 1963, Marcel Breuer: Buildings and Projects 1921–1961, New York: Praeger.
    T.Papachristou (ed.), 1970, Marcel Breuer: New Buildings and Projects 1960–1970, New York: Praeger.
    DY

    Biographical history of technology > Breuer, Marcel Lajos

  • 11 quality function deployment

    Ops
    a quality technique used to design services or products based on customer expectations. Quality function deployment is an approach that sees quality as something that can be designed into a product or service at an early stage. It involves converting customers’ demands into quality characteristics of the finished product. The four phases of the approach are design or house of quality, detail, process, and production. Each phase helps to steer a design team toward customer satisfaction. Quality function deployment is based on methods developed by Genichi Taguchi.
    Abbr. QFD

    The ultimate business dictionary > quality function deployment

  • 12 Jacquard Machine

    The jacquard machine is an essential addition to looms intended for weaving ornamental designs that are beyond the scope of stave -work. The machine is made in many forms and sizes for different branches of the weaving industry, but its characteristic feature is that it furnishes the means whereby every individual thread in a design may weave differently from all the others. This permits the delineation of all forms and shapes and the fineness of the detail is only limited by the texture, e.g., the number of ends and picks per inch. The action of the jacquard machine is communicated to the warp threads through a system of cords known variously as the harness mounting and jacquard harness. Actually, loom harness ante-dated the jacquard machine by many centuries, and many draw loom harnesses were much more complicated than modern jacquard harnesses. An essential feature of a jacquard is that each hook in the machine can be lifted at will independently of the others. The selection of which hooks shall lift and which shall be left down is made by the designer, by painting marks on squared paper to indicate the hooks that must be lifted on each pick. In cutting the pattern cards, a hole is cut for every mark or filled square on the design paper, and a blank is left for every empty square on the paper. Assuming that each pattern card represents one pick of weft, when the card is pressed against the needles of the jacquard, the blanks push the unwanted needles and hooks out of the path of the lifting griffe; the holes allow the needles to pass through and thus remain stationary, so that the corresponding hooks remain in the path of the lifting griffe and cause the corresponding warp threads to be lifted. Jacquard: Single-lift, single-cylinder - In this machine there is only one griffe which lifts on every pick, and only one pattern cylinder, which strikes every pick. This restricts the speed at which the loom can be operated. Jacquard: Double-lift, single-cylinder - This is the machine in most common use for ordinary jacquard work. There are two lifting griffes and twice as many hooks as in a single-lift machine, but only the same number of needles and one card cylinder. The shed formed is of the semi-open type, which causes less movement of the warp threads, as any threads which require to be up for two or more picks in succession are arrested in their fall and taken up again. Double-lift jacquards give a greatly increased loom production as compared with single-lift machines, as they permit the speed of the loom to be increased to about 180 picks per minute for narrow looms, as compared with 120 to 140 picks per minute for single-lift jacquards. Jacquard: Double-lift, double-cylinder - In this machine there are two sets of hooks and needles, two lifting griffes and two card cylinders, odd picks in one set of cards and even picks in the other set. This permits maximum loom speed, it prolongs the life of the pattern cards, but is open to the serious drawback that spoiled cloth is caused whenever the two card cylinders get out of correct rotation. Jacquard: Cross Border - Fabrics with borders, such as tablecloths, bed quilts, etc., are woven with jacquards with two griffes, two sets of hooks and two card cylinders. The cards for weaving the border are laced together and weave on one cylinder, while the centre cards are on the other cylinder. The loom weaves at the speed of a single-cylinder, single-lift machine, and the change from the border to the centre cards can be made by hand or automatically

    Dictionary of the English textile terms > Jacquard Machine

  • 13 назначать

    1) General subject: administer, allocate, allot, announce, appoint, appoint (на пост), apportion (часть, долю кому-л. - to), assign (срок, границы), attach, consign, constitute (комиссию, должностное лицо), designate, destinate, destine, determine (дату и т.п.), elect (на должность), fix, institute (на должность и т. п.), lot, make (на должность), mete (награду, наказание), name (на должность), nominate (на должность), order (лекарство и т. п.), prescribe, schedule, set (цену, время и т. п.), set down, settle, write up, administer a medicine, anoint, tap
    3) American: slate
    4) Military: appoint (на должность), assign (на должность, службу), assign (на должность, службу), design (на должность), designate (на должность), detail, reassign (на новую должность), tell off
    5) Law: allowance (содержание, паек), assign (на должность, для исполнения обязанностей), impose (в законе, приговоре), inflict, prescribe (наказание), put (цену)
    6) Economy: appropriate, assign (на пост, должность), commission (на пост, должность), fix (цену, скидку, ставки), place, put in (на должность), set
    7) Accounting: assign (напр. срок), name (напр. цену)
    8) Diplomatic term: assign (срок, время), charge
    9) Information technology: map
    10) Astronautics: specify
    11) Business: establish, (на должность) assign to
    12) Automation: (пред) assign
    13) Arms production: station
    14) leg.N.P. appoint (e.g., an official, a manager, a committee), fix (e.g., a remuneration, a pension), prescribe (e.g., a certain treatment)
    15) Makarov: assign (срок), establish (на должность и т.п.), give, lay on, mark, put (напр. цену), upset, call for (состав размер режим)
    16) Foreign Ministry: assign (на должность)

    Универсальный русско-английский словарь > назначать

  • 14 план

    м. plan

    Русско-английский большой базовый словарь > план

  • 15 Royce, Sir Frederick Henry

    [br]
    b. 27 March 1863 Alwalton, Huntingdonshire, England
    d. 22 April 1933 West Wittering, Sussex, England.
    [br]
    English engineer and industrialist.
    [br]
    Royce was the younger son of a flour miller. His father's death forced him to earn his own living from the age of 10 selling newspapers, as a post office messenger boy, and in other jobs. At the age of 14, he became an apprentice at the Great Northern Railway's locomotive works, but was unable to complete his apprenticeship due to a shortage of money. He moved to a tool company in Leeds, then in 1882 he became a tester for the London Electric Light \& Power Company and attended classes at the City \& Guilds Technical College. In the same year, the company made him Chief Electrical Engineer for the lighting of the streets of Liverpool.
    In 1884, at the age of 21, he founded F.H. Royce \& Co (later called Royce Ltd, from 1894 to 1933) with a capital of £70, manufacturing arc lamps, dynamos and electric cranes. In 1903, he bought a 10 hp Deauville car which proved noisy and unreliable; he therefore designed his own car. By the end of 1903 he had produced a twocylinder engine which ran for many hundreds of hours driving dynamos; on 31 March 1904, a 10 hp Royce car was driven smoothly and silently from the works in Cooke Street, Manchester. This car so impressed Charles S. Rolls, whose London firm were agents for high-class continental cars, that he agreed to take the entire output from the Manchester works. In 1906 they jointly formed Rolls-Royce Ltd and at the end of that year Royce produced the first 40/50 hp Silver Ghost, which remained in production until 1925 when it was replaced by the Phantom and Wraith. The demand for the cars grew so great that in 1908 manufacture was transferred to a new factory in Derby.
    In 1911 Royce had a breakdown due to overwork and his lack of attention to taking regular meals. From that time he never returned to the works but continued in charge of design from a drawing office in his home in the south of France and later at West Wittering, Sussex, England. During the First World War he designed the Falcon, Hawk and Condor engines as well as the VI2 Eagle, all of which were liquid-cooled. Later he designed the 36.7-litre Rolls-Royce R engines for the Vickers Supermarine S.6 and S.6B seaplanes which were entered for the Schneider Trophy (which they won in 1929 and 1931, the 5.5 having won in 1927 with a Napier Lion engine) and set a world speed record of 408 mph (657 km/h) in 1931; the 1941 Griffon engine was derived from the R.
    Royce was an improver rather than an innovator, though he did invent a silent form of valve gear, a friction-damped slipper flywheel, the Royce carburettor and a spring drive for timing gears. He was a modest man with a remarkable memory who concentrated on perfecting the detail of every component. He married Minnie Punt, but they had no children. A bust of him at the Derby factory is captioned simply "Henry Royce, Mechanic".
    [br]
    Further Reading
    R.Bird, 1995, Rolls Royce Heritage, London: Osprey.
    IMcN

    Biographical history of technology > Royce, Sir Frederick Henry

  • 16 Artificial Intelligence

       In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)
       Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)
       Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....
       When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)
       4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, Eventually
       Just as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)
       Many problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)
       What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)
       [AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)
       The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)
       9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract Form
       The basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)
       There are many different kinds of reasoning one might imagine:
        Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."
        Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)
       Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)
       Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)
       The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)
        14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory Formation
       It is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)
       We might distinguish among four kinds of AI.
       Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.
       Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.
    ... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)
       Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)
        16) Determination of Relevance of Rules in Particular Contexts
       Even if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)
       Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)
        18) The Assumption That the Mind Is a Formal System
       Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)
        19) A Statement of the Primary and Secondary Purposes of Artificial Intelligence
       The primary goal of Artificial Intelligence is to make machines smarter.
       The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)
       The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....
       AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)
        21) Perceptual Structures Can Be Represented as Lists of Elementary Propositions
       In artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)
       Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)
       Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)
       The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)

    Historical dictionary of quotations in cognitive science > Artificial Intelligence

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