Page 169

C—
Illustrative Advanced Long-range
Technology Demonstrations

The projects described below are intended to illustrate the types of advanced long-range technology demonstrations (ALRTDs) suggested in Chapter 7. These sketches omit many important issues, such as project size, participants (universities, companies), duration, budget, and funding mechanism; intellectual property concerns; and so on. However, given the broad scope of some of these projects, support of ALRTDs by mission-oriented agencies as well as research agencies would be desirable. Each project is described briefly in terms of its vision, the infrastructure it would require, the objectives of the demonstration, and its significance.

A Manufacturing Enterprise
Modeling Management System
Vision

An enterprise faces many problems in the course of doing business. To develop insight into these problems and to evaluate different courses of action, decision makers often rely on computer-based models of these problems as they apply to the enterprise. Today, such models are often built "from scratch," because the problems span a set of organizational or functional boundaries that differ from those related to previous problems that have been modeled. However, the model of the problem at hand still requires access to most of the same databases that have been used previously; what is different most often relates to data form, aggregation, granularity, period, frequency, precision, and so on. A



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 169
Page 169 C— Illustrative Advanced Long-range Technology Demonstrations The projects described below are intended to illustrate the types of advanced long-range technology demonstrations (ALRTDs) suggested in Chapter 7. These sketches omit many important issues, such as project size, participants (universities, companies), duration, budget, and funding mechanism; intellectual property concerns; and so on. However, given the broad scope of some of these projects, support of ALRTDs by mission-oriented agencies as well as research agencies would be desirable. Each project is described briefly in terms of its vision, the infrastructure it would require, the objectives of the demonstration, and its significance. A Manufacturing Enterprise Modeling Management System Vision An enterprise faces many problems in the course of doing business. To develop insight into these problems and to evaluate different courses of action, decision makers often rely on computer-based models of these problems as they apply to the enterprise. Today, such models are often built "from scratch," because the problems span a set of organizational or functional boundaries that differ from those related to previous problems that have been modeled. However, the model of the problem at hand still requires access to most of the same databases that have been used previously; what is different most often relates to data form, aggregation, granularity, period, frequency, precision, and so on. A

OCR for page 169
Page 170 manufacturing enterprise modeling management system (MEMMS) would manage the reconfiguration of databases and existing models to account for these specific needs (Table C.1). Infrastructure A MEMMS would require a complete, modern digital communications system, most likely including a wide area network, a local area network with the necessary bandwidth, network management software, network servers, and individual man-machine interfaces; also included would be bridges into databases external to the enterprise. The enterprise would require a standard language and dynamic data dictionary, a distributed database management system, and digitally accessible archival systems. Models of different aspects of the business would have to be stable enough to allow the enterprise itself to evolve. Objectives of the Demonstration • To show that a MEMMS would provide direct, tangible, bottom-line benefits to the enterprise in flexibility, response time, and the complexity of problems that can be tackled. Problems could be addressed quickly and efficiently when an organization had completed the up-front work of standards, common language, data elements definition, database design, and modernization of the archival knowledge bases. • To show that an appropriate methodology for model construction within an enterprise involving techniques of modular design, scaling, enterprise model hierarchy, and modeling software architecture would allow individual models and databases to be reconfigurable and reusable for new problems. • To show that a MEMMS is possible that would enable employees in all functions within an enterprise to manage reconfiguration of a set of models for meaningful analysis and solution of problems facing manufacturing enterprises today. A corollary is that a software interface for a MEMMS is possible that does not require highly specialized training in its operation. Significance The MEMMS would provide a common language and analysis tools that would accelerate decision making but provide all players with access to the best and most current data and tools. Organizations would thus be able to focus more on the enterprise problems and less on the task of building new models. The interdependence of disparate business functions within the organization would become clear, and integration of all activities would accelerate. These changes would allow organizations to become more focused, flexible, and responsive to the marketplace.

OCR for page 169
Page 171 TABLE C.1 A Manufacturing Enterprise Modeling Management System   Example Models Example Databases Research and development Process, material, and product concept models Material properties data, performance data, boundary data Product design Process and product models—design, fabrication cost Material performance data, production costs, design history library Production Process and product models Data on volume, mix, cost, materials, maintenance, uptime Supplier management Product and process models, production and throughput models Statistical process data, status and cost data, production data Logistics Shop floor production planning and throughput models Data on volume, condition of paths of material flow, shipping schedules Financial management Financial models—production, debt structuring, investment Production costs, financing costs, external interest rates Human resources management Cost-per-employee, succession, and training models Compensation data, employee ratings, government regulations Sales and marketing Price-cost-market share models, sales forecasting models Customer needs; costs to produce, ship, and advertise; data on customer needs, preferences Business strategy and planning Dynamic strategic analysis models, scenario models Macroeconomic data; data on markets, competitors, costs, exchange rates Alliance-joint venture management Process and product models, financial models, distribution and flow models Data on production, processes, products, costs, revenues, technology used External stakeholder management Life-cycle models, legislative and regulatory models Data from the Environmental Protection Agency, Occupational Safety and Health Administration, legislative records, newspapers NOTE: The manufacturing enterprise modeling management system would connect models and internal databases through a network and would access external databases as necessary.

OCR for page 169
Page 172 Operation Of A Machine Shop Brokerage System Vision A machine shop brokerage clearinghouse would be given responsibility for on-line brokerage policies and procedures for participating customers, permitting their machining needs to be matched to the available machining capacity of a certain set of suppliers. The broker's responsibilities would include the establishment of machine shop certification and qualification, bidding procedures, request-for-quote procedures, arbitration of disputes, payment, and so on. The clearinghouse would solicit suppliers and advertise for customers; participating customers and suppliers would be connected by network in a given geographic region. Infrastructure The region served would require a wide area network and easy access of customers to the network. Suppliers and customers would have to be skilled enough to handle such things as computer-aided design data exchange, electronic data interchange requests for quotes and invoicing, electronic funds transfer payments, and so on. Suppliers would have to be sophisticated enough to handle statistical process and quality control techniques, provide records of employees' training and qualifications, and use computerized production order tracking and status reporting. Objectives of the Demonstration • To show that a set of policies and procedures could be developed for the purpose of electronic brokering of machine-shop-type work tasks and assurance that this type of business could be supported by existing technology. • To show that a clearinghouse of this nature would enable customers to find services of assured quality and dependability and at reasonable cost. • To show that technical and business issues between customers and suppliers (answering questions, modifying the design) could be handled over the network. Consequences The traditional business practice in which companies deal with a small number of familiar suppliers would change. Brokering would allow an enterprise to become more flexible and cost-effective by providing a menu of certified suppliers with differing availability, cost, skill sets, and quantity attributes.

OCR for page 169
Page 173 Brokerage For National Prototyping Facilities Vision Prototyping technology is being developed in a number of U.S. universities, private industries, and national laboratories. To demostrate their capabilities and to increase customer awareness of and access to these facilities, a national brokerage institute would take responsibility for on-line policy and procedures such as the establishment of prototyping site certification and qualification, bidding procedures, request-for-quote procedures, arbitration of disputes, payment, and so on. The institute would solicit members and advertise for customers. If it were successful, the flow of business into these facilities would help to amortize their high cost. Infrastructure The institute would require a wide area network and easy access of customers to the network. Suppliers and customers would have to be advanced enough to handle computer-aided design data exchange, electronic data interchange requests for quotes and invoicing, electronic funds transfer payments, and so on. Suppliers would have to be sophisticated enough to handle statistical process and quality control techniques, provide records of employees' training and qualifications, and use computerized production order tracking and status reporting. Objectives of the Demonstration • To show that a set of policies and procedures could be developed for the purpose of electronic brokering of prototyping work tasks and that this type of business could be supported by existing technology. • To raise the visibility of limitations in software, standards, and the prototyping processes and also pinpoint industries in which large markets for this type of work exist. This should spur further research and development along the lines that industry really needs. Consequences A prototyping brokerage would expand access to and knowledge of prototyping processes and capabilities. Prototyping decreases design time by validating design decisions or providing early notice of design errors.

OCR for page 169
Page 174 Real-Time Sales Forecasting Vision A company should be able to locate and query financial, economic, and demographic databases and predict sales of one of its products by regional market. With such information in hand, it would then notify its supplier base of its anticipated needs for a defined time period in the future. Infrastructure A real-time sales forecasting system would require databases, search techniques, and modeling methods for extrapolating information that is not available directly. Of particular relevance are national and regional economietric data on and models of consumer behavior at the present time; data on stocks of finished goods unsold in a company's own pipeline plus estimates of stocks in competitors' pipelines extrapolated from other economic data; methods of determining demand for the company's products based on demand from allied economic fields (e.g., demand for electric sockets based on demand for wire, or demand for paint and varnish based on demand for lumber); and access to statistics from home shopping systems. Objectives of the Demonstration • To show that a company could find needed data. • To show that a company could construct the models it needed if models did not exist, or that it could find experts to help construct models. • To show that a company could obtain valid sales forecasts more rapidly with information technology than by former means, and/or that it could obtain more accurate forecasts than before. • To show that a company could integrate these forecasts advantageously into dealings with its suppliers or business partners. Consequences Normal business practices would change greatly because each company as well as its competitors would have better forecasts. Thus each firm would have to add its own capabilities to what is available to everyone on the network. Relationships with suppliers would become tighter, ordering patterns would change to ever-smaller orders spaced more closely together, and inventories would become smaller, saving working capital.