5 PRODUCT SYSTEM

INTRODUCTION

We have noted that a new economic functional system is constructed from the new high-tech products of the new technology. We have also seen that technologies are a kind of system and emphasized that invention of the technology system is the first part of innovation. The second part of innovation, commercialization, occurs by de- signing the new technology into new products (or services or operations). Now we look at high-tech products, and we will see how products, too, are systems. As the idea of a technology system is fundamental to innovation theory, so is the idea of a product system. But there is an important difference between them. A technology system is knowledge, and a product system is a utility. The knowledge of a tech- nology is embodied in the design of a useful product. We will review the idea of a product as a system, including the basic ideas of: product architecture and com- plexity and the differing roles of technology in product, service, production, and operations systems. As an example of a product system, we use the case of the . It makes an interesting illustration, since the technology in a computer is complex in both physical morphology and schematic logic. First we look at the invention of the elec- tronic computer and then we look at the design of an early computer product, the PDP-8 minicomputer.

CASE STUDY: F Invention of the Computer

Like the ancient invention of iron, the computer was one of those great inventions that change human civilization—an invention of mythic scale—a Promethean in- vention. Prometheus was a titan in ancient Greek mythology to whom the Greeks ascribed the invention of the technology of fire as a gift to humans. The ancient Greeks thought the gift of fire so valuable—and so godlike in power—that they imagined that Prometheus was punished for his gift. The angry gods chained 85 86 PRODUCT SYSTEM

Prometheus to a mountain, to be exposed eternally to the harshness of weather, blasts of lightning, and the flesh-tearing beaks of vultures. Fascination with the power of technology has long been a part of human culture. The computer changed the mythic power of humanity to acquire and process information. Central to its invention were five people: von Neumann, Goedel, Turing, Mauchly, and Eckert (Heppenheimer, 1990), each of whom came to a tragic end. was born in Hungary in 1903, the son of a Budapest banker. He was precocious; at the age of 6 he could divide eight-digit numbers in his head and talk with his father in ancient Greek. At 8 years of age, he began learning calculus. He had a photographic memory; he could take a page of the Budapest phone directory, read it, and recite it back from memory. When it was time for university training, he went to study in Germany under a great mathematician, David Hilbert. Hilbert believed that all the diverse topics in mathematics could be established on self-consistent and self-contained intellectual foundations. In a famous address in 1900, Hilbert expressed his position: “Every mathematical prob- lem can be solved. We are all convinced of that. After all, one of the things that attracts us most when we apply ourselves to a mathematical problem is precisely, that within us we always hear the call: here is the problem, search for the solu- tion; one can find it by pure thought, for in mathematics there is no ignorabimus (we will not know)” (Heppenheimer, 1990, p. 8). As a graduate student, von Neumann worked on the problem of mathematical foundations. But in 1931, Kurt Goedel’s famous papers were published, arguing that no foundation of mathematics could be constructed wholly self-contained. If one tried to provide a self-contained foundation, one could always devise math- ematical statements that were formally undecidable within that foundation (inca- pable of being proved or disproved purely within the foundational framework). This disturbed von Neumann, as it did all other mathematicians of the time. But Goedel also introduced an interesting notation in which any series of mathemat- ical statements or equations could be encoded as numbers. This notation would later turn out to be a central idea for von Neumann’s vision of a stored program computer. All mathematical statements, logical expressions as well as data, could be expressed as numerically encoded instructions. However, the first person to take up this idea was not von Neumann but Alan Turing. Turing was a 25-year-old graduate student at Cambridge University when he published his seminal paper, “On Computable Numbers,” in 1937. He had used Goedel’s idea for expressing a series of mathematical statements in sequential numbering, Turning proposed an idealized machine that could do mathematical computations. A series of mathematical steps could be expressed in the form of coded instructions on a long paper tape. The machine would execute these in- structions in sequence as the paper tape was read. His idea was later to be called a Turing machine. Turing had described the key idea for what would later become a general-purpose programmable computer. Although many people had thought of and devised calculating devices, these had to be instructed externally or could solve only a specific type of problem. A machine that could be instructed gener- ally to solve any kind of mathematical problem had not yet been built. INTRODUCTION 87

Back to von Neumann. After finishing his graduate studies in Germany, von Neumann emigrated to the United States and joined the faculty of Princeton Uni- versity in 1930. There Turing’s and von Neumann’s paths crossed temporarily when, in 1936, Turing came to Princeton to do his graduate work. He was think- ing about the problem of his idealized machine (which he would soon publish), and he worked with von Neumann, exposing von Neumann to his ideas. Von Neu- mann offered Turing a position as an assistant after Turing received his doctor- ate. But Turing chose to return to Cambridge where in the following year, he published his famous paper. So Turing’s ideas were in the back of von Neumann’s mind. But meanwhile, war was to intervene, beginning with the German invasion of Poland in 1939. During that war, Turing went into England’s secret code-breaking project and helped construct a large electronic computer to break enemy codes. Called the Colossus, it began operating in 1943, but it was a single-purpose computational machine (Zorpette, 1987). At the same time in the United States, von Neumann was involved in the Man- hattan Project, to create the atomic bomb. Earlier at Princeton, von Neumann had been exploring the mathematics of problems in fluid flow. In the design of one of the atomic bombs, it was proposed to place a sphere of dynamite around pie- shaped wedges of plutonium. When the dynamite exploded, the wedges were in- tended to be blown together into a small sphere (slightly smaller than a soccer ball). This plutonium sphere would then undergo the violent nuclear chain reac- tion of an atomic explosion. Von Neumann designed the dynamite trigger for this bomb, called the “Fat Man” version of the atomic bomb. The trigger problem was: To precisely what thickness should the dynamite around the wedges of plutonium be formed so that they would all be blown in at the same time? To design this, one had to calculate the physical form of the shock waves from the dynamite explosion that would push the plutonium wedges in- ward. It was a flow type of mathematical problem, and von Neumann would be just the one to calculate it. But it was a tough problem because of the accuracy required in describing the shock waves. To do it, von Neumann and a colleague at Los Alamos, Stanislaw Ulam, devised a kind of human computing system. They had one of their colleagues, Stanley Frankel, devise a lengthy sequence of com- putational steps that could be carried out on mechanical calculating machines made by IBM. Frankel then had a large number of Army enlistees running these steps on the calculating machines. It was a slow kind of human computer, but it worked. von Neumann got the solutions he needed to design the explosives for the Fat Man. The Fat Man bomb was the second atomic bomb to be exploded. It was dropped on Nagasaki, killing more than 100,000 Japanese. This technical challenge taught von Neumann an important lesson, the need for a general- purpose computer. (Afterward, one of von Neumann’s favorite events was ob- serving atom bomb tests, and exposure to radiation may have been the cause of von Neumann’s fatal tumor.) One day in August 1944 (before the atomic bombs were dropped), von Neu- mann had gone to the Army’s in Maryland on a 88 PRODUCT SYSTEM

consulting assignment. Afterward, he waited at the station for a train. On the same platform happened to be Lt. (who before the war had taught mathematics at the University of Michigan). He recognized von Neumann, already a world-famous mathematician. Goldstine introduced himself. Personally, von Neumann was a warm, pleasant man. He chatted amiably with Goldstine, ask- ing him about his work. Later Goldstine said of the meeting: “ ‘When it became clear to von Neumann that I was concerned with the development of an electronic computer capable of 333 multiplications per second, the whole atmosphere changed from one of relaxed good humor to one more like the oral examination for a doctor’s degree in mathematics.’ ” (Heppenheimer, 1990, p. 13). It turned out that Goldstine was one of Mauchly and Eckert’s team building the ENIAC, the world’s first electronic computer; and it was in this meeting that von Neu- mann first heard of the ENIAC project, a project conceived by John W. Mauchly. The story of the computer now switches to Mauchly. Mauchly had been born in Cincinnati, Ohio in 1907. In 1932, he had received a Ph.D. in physics from Johns Hopkins University. Teaching physics at Ursinus College from 1933 to 1941, Mauchly had begun to experiment with electronic counters while doing research on meteorology. In 1941, he attended a summer course in electronics at the Moore School of Electrical Engineering at the Uni- versity of Pennsylvania. He was then invited to join the faculty. In 1941, Mauchly heard of some computational work by a physicist, John Atanasoff at Iowa State University. He visited him, and Atanasoff showed Mauchly an experimental elec- tronic adder which Atanasoff had completed in 1940. That gave Mauchly an idea. In the fall of 1942, he wrote a memorandum on the idea of using electron vac- uum tubes for a calculating machine (Brittain, 1984). The key idea in Mauchly’s proposal was to use Atanasoff’s flip-flop circuit as a basic logic circuit for com- puters, since it could record a binary state of either 0 or 1. A signal applied to the grid of a tube could turn the tube on, and thereafter it would stay on and con- ducting (a state of 1). Another signal might then be applied to the tube, and it would turn off (a state of 0). In either state, the flip-flop circuit would be stable until a new signal arrived to flip it. This circuit used a pair of tubes hooked to- gether. Mauchly outlined in the memorandum how one could use a set of flip- flop circuits to express a number system (binary numbers) and so construct a reconfigurable calculating machine. Mauchly submitted his proposal to the Army Ordinance Department: Colonel Paul N. Gillon, Colonel Leslie E. Simon, and Major H. H. Goldstine. They ap- proved the idea and gave an R&D contract to the Moore School to build the ma- chine, which Mauchly would call the ENIAC. For this project, Eckert was the chief engineer and Mauchly the research engineer. J. G. Brainerd was project su- pervisor; and several others made up the team, including Arthur Burks, Joseph Chedaker, Chuan Chu, James Cummings Leland Cunningham, John Davis, Harry Gail, Robert Michael, Frank Mural, and Robert Shaw. It was a large undertaking and required a large R&D team (Brainerd and Sharpless, 1984). When constructed, the ENIAC took up an entire large air-conditioned room, whose four walls were covered by cabinets containing electron-tube circuits INTRODUCTION 89

Figure 5.1. ENIAC, 1946. Eckert is in the foreground and Mauchly is in the center.

(Figure 5.1). Altogether the circuit cabinets weighted 30 tons and drew 174 kilo- watts of power. The major problem was tube failure. Mauchly and Eckert had cal- culated that of the 17,468 tubes they were using in ENIAC, they were likely to have on average one failure every 8 minutes. This would have made ENIAC use- less, not able to compute anything that took 8 minutes or longer. Cleverly, they de- cided to run the tubes at less than one-half of their rated voltage and one-fourth of their rated current, which reduced the failure rate to one tube about every two days. Still, the ENIAC was not easily programmable. To set up a new problem for cal- culation, one had to connect circuits physically using patch cords between jacks, and the cabling ran up to a total of 80 feet in length. The patching task itself could take at least two days. It all came together in the summer of 1944 after Goldstine met von Neumann. The ENIAC was already working, and Eckert and Mauchly were thinking about an improved successor, which they intended to call EDVAC (electronic discrete variable automatic computer). At Goldstine’s urging, the Army was considering awarding the Moore School $105,600 to build the EDVAC: “Into this stimulating environment stepped von Neumann. He joined the ENIAC group as a consultant, with special interest in ideas for EDVAC. He helped secure the EDVAC contract and spent long hours in discussions with Mauchly and Eckert” (Heppenheimer, 1990, p. 13). The contract was let in October 1944, and in June 1945 von Neu- mann completed his famous paper “First Draft of a Report on the EDVAC.” This was one of the most influential papers in what was to become computer science. 90 PRODUCT SYSTEM

Goldstine circulated the draft with only von Neumann’s name on the title page: “In a later patent dispute, von Neumann declined to share credit for his ideas with Mauchly, Eckert, or anyone else. So the “First Draft” spawned the legend that von Neumann invented the stored-program computer. He did not, though he made con- tributions of great importance” (Heppenheimer, 1990, p. 13). However, neither von Neumann nor Eckert nor Mauchly built the EDVAC. The ENIAC group broke up. The University of Pennsylvania hired a new director of research, Irvin Travis, who quarreled with Eckert and Mauchly over patent rights. Eckert and Mauchly had a letter from the university’s president stating that they could hold the patents on ENIAC. But Travis told them that they must sign patent releases to the university. Mauchly and Eckert refused and resigned from the uni- versity in 1946. They formed the Electronic Control Company, which became the Eckert–Mauchly Computer Corporation in 1947. It built the first commercial general-purpose electronic computer, the UNIVAC, selling its first product to the U.S. Census Bureau. But running out of funds to build that first machine, Eckert and Mauchly sold out to Remington Rand, which in turn became Sperry Rand in 1955. In 1959, Mauchly left Sperry Rand to form a consulting firm. After the war, von Neumann returned to the Institute for Advanced Study in Princeton. He decided to build a computer, and Goldstine joined him, along with Julian Bigelow (who had worked on radar-guided antiaircraft gun control during the war). Goldstine and Bigelow built a 2300-vacuum-tube computer for von Neu- mann in the boiler room of the main building at the Institute. This was the first fully automatic stored-program computer. A patent on this basic invention would have been valuable. Somewhere be- tween Turing, von Neuman, Mauchly, and Eckert the inventive idea arose. But von Neuman published the idea before filing for a patent. In patent law, this in- validated anyone from filing for a patent. So it happened that there was no basic patent on the stored-program computer. In summary, John von Neumann created the world’s first stored-program elec- tronic computer. He was influenced by the earlier ideas of Kurt Goedel and Allen Turing. He also drew upon the contemporary ideas and work of and J. Presper Eckert. Mauchly and Eckert created one of the world’s first all electron-vacuum-tube special-purpose (about the same time, other special-purpose computers were being created independently in England by Turing and in Germany by Konrad Zuse). Mauchly had also borrowed earlier ideas from John Atanasoff. Mauchly and Eckert were in turn influenced by von Neu- man’s ideas. Mauchly and Eckert did create the world’s first commercially suc- cessful stored-program electronic computer, the UNIVAC. Mauchly was very bitter that von Neumann never acknowledged him as a coin- ventor of the stored-program concept. Adding injury to insult, von Neumann tes- tified against Mauchly in an important trial that challenged Mauchly and Eckert’s patent claim from the ENIAC. The judge ruled that Mauchly and Eckert were not the true inventors of the electronic computer. This ruling contributed to Mauchly’s final penury: “ ‘Lawyers keep making money,’ said Mauchly toward the end. ‘We’ve got down to the point where maybe we can buy some hot dogs with our Social Security.’ ” (Heppenheimer, 1990, p. 16). COMPUTER ARCHITECTURE 91

And the gods seemed to add to Mauchly’s woes. In 1980 he died from a ge- netic disease that had terribly disfigured him. Terrible also was the gods’ fate for von Neumann: “For von Neumann, it was even worse. In the summer of 1955, he was diagnosed with bone cancer, which soon brought on excruciating pain. In the words of his friend Edward Teller, ‘I think that von Neumann suffered more when his mind would no longer function than I have ever seen any human being suf- fer.’ Toward the end there was panic and uncontrolled terror” (Heppenheimer, 1990, p. 16). Things also went hard for Allen Turing, the person who had first conceptual- ized general computation as programmable operations: “Convicted in England of soliciting sexual favors from a teen-age boy, he was given a choice of prison or hormone treatments. He chose the hormones and soon found his breasts growing. Driven to despair, he made up a batch of cyanide in a home laboratory and died an apparent suicide” (Heppenheimer, 1990, p. 16). Even the famous logician, Kurt Goedel, whose work influenced the computa- tional ideas of both Turing and von Neumann, was personally tormented: “It was his own personal demons that would drive him to death. . . . After his wife un- derwent surgery and was placed in a nursing home, in 1977, Goedel refused to take any food. He starved himself to death” (Heppenheimer, 1990, p. 16). Apparently, Promethean inventions make gods angry.

COMPUTER ARCHITECTURE

Von Neumann’s famous report had described the logical scheme of a computer op- erational architecture: single-instruction single-processing (SISP) architecture. The key advance was the inclusion of stored-program instructions, which made the ma- chine a general-purpose computational device. First a program and data must be in- put into computer memory. A (CPU) calls up the program instructions in sequence from the stored program and executes each instruction on the data. After the data have been transformed according to each instruction, the re- sult calculated is stored temporarily and then transformed further by the next in- struction in the program. After all instructions in the program have been executed, the final results are both stored in the memory and outputted from the computer. In this computational scheme, the program expresses the logic of the mathemat- ical transformation. The operation of the computer is to map each instruction of this logic onto a specific configuration of the electronic circuits within the computer. This is a mapping of logic to physical electronic processes within the computer, and it is a high-level program logic mapped to physical structures of the computer se- quentially for calculations. At a lower logical level of computer technology, a binary number system has been mapped onto physical circuits of the computer. The instructions of the pro- gram and the data upon which calculations are performed are expressed in binary numbers, which constitute the lowest level of logic mapped into the physical struc- ture of the computer. 92 PRODUCT SYSTEM

A binary number system is a way of writing integer numbers with only two sym- bols (0 and 1). In a binary system:

zero is symbolized as 0 one is symbolized as 1 two is symbolized as 10 three is symbolized as 11 four is symbolized as 100 five is symbolized as 101 six is symbolized as 110 seven is symbolized as 111 eight is symbolized as 1000 nine is symbolized as 1001 ten is symbolized as 1010 and so on

In a decimal system, an addition of numbers such as 1 2 3 would be in the binary system 1 10 11. In the von Neumann architecture, one could build a cal- culating machine using only binary-state electron-vacuum tubes and all calculations in the machine would be performed in the binary number system. This is an exam- ple of a mapping of a logic onto a physical structure (the logic of numbers to binary physical states of electron-tube flip-flop circuits) In the mathematical oper- ations, computer calculations are performed as a coordination of physical processes to logical operations. Arithmetical operations are coordinated to as a series of phys- ical processes, such as turning some tubes in circuits off and others on. Von Neumann used Turing’s idea for a mathematical algorithm to be performed as an ordered sequence of operations, beginning with the initial data and trans- forming them to calculated results. This is the concept of the stored-program com- puter: to store both the data and the program algorithm in the active memory of the computer architecture. A von Neumann computer architecture is then run, timed to an internal clock, performing the following calculational cycle:

1. Initiate running the program. 2. Fetch the first instruction from main memory to the program register. 3. Read the instruction and set the appropriate control signals for the various internal units of the computer to execute the instruction. 4. Fetch the data to be operated on by the instruction from main memory to the data register. 5. Execute the first instruction on the data and store the results in a storage register. 6. Fetch the second instruction from the main memory of the program register. 7. Read the instruction and set the appropriate control signals for the various internal units of the computer to execute the instruction. 8. Execute the second instruction on the recently processed data, whose result is in the storage register, and store the new result in the storage register. COMPUTER ARCHITECTURE 93

9. Proceed to fetch, read, set, and execute the sequence of program instructions, storing the most recent result in the storage register until the complete pro- gram has been executed. 10. Transfer the final result calculated from the storage register to the main mem- ory and/or to the output of the computer.

The von Neuman stored-program computer worked like a Turing machine. Any mathematical calculation can be expressed as a sequence of ordered algorithmic steps that transform initial data into calculated results (with both the data and pro- gram stored in the main memory of the computer).

CASE STUDY: F PDP-8 Computer

The idea behind computer architecture just discussed represents technical knowl- edge, knowledge of a technology system. To actually make a computer that uses this knowledge, the ideas must be translated into the design of a computer prod- uct. We see how the ideas of a technology are translated into the design of a product by looking at the design of an early minicomputer in 1970, Digital Equip- ments PDP-8. After the invention of the computer, technical progress in computer development came first as improved components for memory and logic, ferrite core memories, and transistorized circuits. Next, the invention of the semiconductor integrated- circuit (IC) chip provided the parts for both memory and logic circuits. By the late 1960s, technological progress in IC chips made possible a new product line, mini- computers, lower in performance and price than mainframe computers. The PDP-8 was innovated by a new company, Digital Equipment Corporation (DEC), founded by Ben Olsen. As a student at MIT, Ben Olsen had worked on the world’s second general- purpose computer, developed by Jay Forrester at MIT (after Forrester had seen Mauchly and Eckert’s computer). Later, Olsen founded DEC to produce transis- torized circuits boards for computer applications. By the late 1960s, Olsen saw that he could make a relatively simple transistorized computer that although lower powered than the expensive mainframe computers of the time, could be afforded by a single scientist rather than only by a research laboratory. This was the com- mercial focus of the PDP-8, and over 100,000 of these units were built and sold to scientists. It launched the minicomputer industry as a market niche beneath the higher-priced mainframe industry. The PDP-8 was configured on a von Neumann architecture. Its central pro- cessing unit was an arithmetic–logic unit (ALU) to perform both arithmetic (e.g., addition, multiplication, integration) and logical operations (e.g., and, or, if–then). It had a memory unit storing 4096 words, with each word of 12-bit length. It had a data bus (internal electrical connections to move data around inside the com- puter from input to memory, from memory to ALU, from ALU back to memory, 94 PRODUCT SYSTEM

and from memory to output). It had an input/output (I/O) and control panel with switches with a lighted display register for inputting, displaying output, and over- all control. In the simplest form, data were entered manually by the graduate stu- dent (or technician). Most scientists also added other devices to the PDP-8, for automatic data entry and output (such as punched tape drives and readers). The units noted above constituted the central components of the technology system of the stored-program computer. The PDP-8 added several other units. The first addition was an accumulator (AC) register, which stored the intermediate computational results from the ALU as it stepped through a computation. It also had a storage register, called LINK, to store temporarily arithmetic overflow bits in the calculations (e.g., to add the units and carry the overflow to the tens). It also had a memory address (MA) to indicate where in memory to find the data (or instruction) to read and where to store the computed data result from the ALU. There was also a memory buffer (MB), where data read from memory was stored temporarily to be ready at the exact time the ALU needed it. The ALU ran on a very strict and rapid sequence, according to stored-program instructions. There was also a program counter (PC) to specify the location in memory where the in- struction could be found that was to be executed next by the ALU. There was also an instruction register (IR) into which had been read from memory the instruc- tion that the ALU was currently executing. The difference between the PCP-8’s principal units (arithmetic–logic unit, memory, input–output) and its secondary units (arithmetic overflow, memory ad- dress, memory buffer, program counter, instruction register) is an illustration of one of the important differences between a generic technology and an actual prod- uct that implements the technology. Additional features are necessary to make the technology perform adequately for an application. In addition to adding features to a generic technology, a product may also arrange a hierarchy of technology subsystems. The concept on which the stored- program computer was based used the idea that a binary number system could be mapped directly to the two physical states of a flip-flop electronic circuit. This circuit was one in which one tube was constantly conducting electricity (on) un- til a signal arrived to turn it off. Then it remained off (nonconducting) until an- other signal arrived to turn in on again. The logical concept of the binary unit 1 could be interpreted as on (or conducting) state, and the binary unit 0 could be interpreted as the off (or nonconducting) state of the electric circuit. In this way the functional concept of numbers (written on a binary base) could be mapped di- rectly into the physical states (morphology) of a set of electronic flip-flop circuits. The number of these circuits together would express how large a number could be represented. This is what is meant by word length in a digital computer. The PDP-8 was designed with a 12-bit word length, which required 12 transistorized flip-flop circuits to be constructed wherever a word was to be expressed mor- phologically in the computer. Binary numbers must encode not only data but also the instructions that perform the computational operations on the data. So a word length of 12 bits had the important constraint of limiting the complexity of the TECHNOLOGY SYSTEM AND PRODUCT SYSTEM 95

instruction. (One of the points of progress in computer technology has been how long a word length the computer can use. For example, in microcomputers (com- puters on a chip), the word length began at 8 bits in 1975, increased to 16 bits in 1980, and increased to 32 bits in 1988. Each increase in word bit length lead to faster processing speeds and faster memory access.) The design of the PDP-8’s technology system used a hierarchy of subsystems. The lowest level of the computer morphology mapped to logic was the mapping of a set of bistable flip-flop circuits to a binary number system. At the highest logic level, von Neumann’s stored-program concept was a clocked cycle of fetching and performing computational instructions on data. At an intermediate logic level be- tween the binary number logic and the program logic of the computer was an in- termediate level of logic in arithmetic operations. Thus, the PDP-8 computer had several hierarchical levels of schematic logics mapped to physical morphologies:

1. Binary numbers mapped to bistable electronic circuits 2. Boolean logic operations mapped to basic electronic circuits 3. Mathematical basic operations mapped (through Boolean constructions) to electronic circuits 4. Computer architecture mapping algorithms into temporally sequenced elec- tronic circuits

TECHNOLOGY SYSTEM AND PRODUCT SYSTEM

The configuration of a technology system indicates only the principles necessary for the functional transformation of the technology. But the configuration of a prod- uct system embodying the technology must add secondary steps and processes needed to fill in the details and fully connect the principal logic steps and other sec- ondary technology systems to complete the product.

The differences between a technology system and a product system are (1) in the details and fully connected steps of the core technology in the product system, and (2) in completing the product system with the neces- sary secondary technologies.

For example, consider the familiar automoble as a product system. The functional transformation of the automobile provides land transportation for moving passen- gers and goods from one location on land to another. In logical order, an automo- bile must be fueled, entered, started, directed, and stopped. To accomplish this, the physical structure of the automobile has several subsystems which together config- ure the automobile system:

• A body subsystem • A fuel subsystem 96 PRODUCT SYSTEM

• A starting and ignition subsystem • An engine and transmission and drive train subsystem • A wheels and suspension subsystem • A breaking subsystem • A steering subsystem

In addition, there are subsystems for passenger comfort and safety:

• Seating • Windows and climate control • Seat belts and airbags

Knowing how a technology works is not sufficient to know how to design a prod- uct of that technology. Knowing how to design a product provides a source of tech- nical differences between competitors.

A product system is a completed and connected transformational technol- ogy system used by a customer.

A product system such as a computer involves not just one simple logic in its technology system but many complex logics. The schematic logic of the computer technology requires several hierarchical logic levels from transistors to circuits to binary numbers to Boolean algebra to mathematical operations, and above that, a Turning machine procedure. Although information technologies (such as the com- puter) have complex logics, not all technologies have complex logic. Most physical technologies have relatively simple schematic logic but have complex physical mor- phologies in their product systems. For example, the relatively simple schematic logic of a helicopter technology is to provide lift by rotating propellers and to pro- vide stability by controlling the tilt of the propeller blades and a counter-rotational tail propeller. A complex technological system may be constructed of parallel subsystems, or of a hierarchy of subsystems, or of both parallel and hierarchical subsystems. Par- allel subsystems are component systems of a system which operate simultaneously but independently in the system’s transformation function. Hierarchical subsystems are functionally lower-level systems whose operations determine the operation of the system at a synthetic upper level. As we saw, the logic of the computer system is constructed of hierarchical subsys- tems: beginning with transistorized bit word lengths, scaling up to basic logic opera- tions and up to basic arithmetic operations and up to programmed mathematical and logical operations. Information products perform logically complex transformations.

TECHNICAL PROGRESS IN PRODUCT SYSTEMS

Technical progress in a product can occur from technological inventions to im- prove the product design or to improve its production process. To see the need for SUMMARY AND PRACTICAL IDEAS 97 technical progress in products, one should ask the following kinds of questions of an existing product system:

1. What level of product performance is minimally acceptable for an applica- tion, and what increments in performance would be clearly noticeable by a customer? 2. What features of the product are used in which application? 3. What peripheral devices are essential to an application? 4. What aspects of the product have glitches or breakdowns or require frequent maintenance in an application? 5. What aspects of the product operating in various environments create safety or pollution risks? 6. How does the current cost of a product limit the number of applications? 7. What factors in the application system determine the product’s replacement rate by customers? 8. What factors in the product facilitate (or inhibit) brand loyalty in replacement purchases?

TECHNOLOGY IN PRODUCT, SERVICE, PRODUCTION, OR OPERATIONS

Finally, we note that business technology systems are embodied not only in product systems but also in production systems, service systems, and operations systems:

•A production system is a completed and connected set of transformational tech- nology systems used in producing a product. •A service system is a completed and connected set of transformational tech- nology systems used in communicating and transacting operations within and between producer/customer/supplier networks. • An operations system is a completed and connected set of transformational technology systems used in communicating within and operating a business enterprise.

SUMMARY AND PRACTICAL IDEAS

In case studies on

• Invention of the computer • PDP-8 computer we have examined the following key ideas:

• Computer architecture • Product system complexity 98 PRODUCT SYSTEM

• Technology system and product system • Technical progress in product systems

These theoretical ideas can be used practically to understand how technological invention occurs and how technology becomes embedded into products, production, services, or operations that are high-tech—embodiments of the latest in technolog- ical progress.

FOR REFLECTION

Identify a key invention and read a history of how it came to be invented. What was the functional logic in the invention? Into which products, processes, or services was the technology embedded?