This section is a survey of some of the applications that were described to the panel, either by oral presentation or in answers to our questionnaire. Most of this material is abstracted from the site visit reports in Appendix E. The companies that we visited that are not listed below, namely Japan Air Lines and Sekisui Chemical, basically had one major application each, and that application has already been discussed.
Fujitsu Laboratories reports that it has built about 240 systems for internal use. The company also has knowledge of about 250 systems built by its customers, but cannot categorize any of them in terms of operationality. Fujitsu estimates that about 20 percent of the projects started get as far as a complete prototype, and of those, 20 percent get to an operational system status. A best overall guess is that five percent of the reported systems are in routine use. The current success rate in fielding expert systems is better than five percent. Because of the experience base it now has, Fujitsu is better able to select problems which are solvable by this technology, and the success rate is now somewhere between 75 and 95 percent.
Planning/Scheduling. The largest percentage of systems developed for internal use are for planning or scheduling. The most successful is PSS, a production support system for planning assembly and test of printed circuit boards. The application is relatively small, built on ESHELL, and runs on a mainframe. The system, which is in daily use, saves about one person-year per year by speeding up the planning time. A workstation version is under development.
Fujitsu stresses integration of KBS and conventional systems. It now has ES tools written in COBOL (YPS/KR) and in FORTRAN (FORTRAN/KR), to support such integration (see Chapter 3).
At Fujitsu, 60-75 percent of the development cost of a system goes into the graphic user interface (GUI). Better GUIs are needed. That need has stimulated work on a GUI called GUIDEPOWER.
In addition to the need for better GUIs, Fujitsu also pointed to other problems with the existing technology. Knowledge changes rapidly in the real world (e.g., in banking), and hence the maintenance of the KB is too costly using existing techniques. A more automated means of knowledge acquisition/revision is needed. Another problem is the relative paucity of development tools, such as for testing a system. Our Fujitsu hosts expressed the view that the ES and CASE worlds are not well matched -- in general, expert systems are best suited to ill-structured problems, whereas CASE tools are better suited to well-structured problems.
Finally, Fujitsu worked with NKK on the blast furnace system described earlier. It is one of the largest applications with which Fujitsu has been associated.
Hitachi has developed 500 to 600 systems for customers. It has sold on the order of 4,000 copies of its ES/KERNEL Systems, half of that number in the last two years, to approximately 1,000 customers. About 50 systems each are in field test mode, are completed prototypes, or are under development.
Construction. One of Hitachi's most successful applications is a tunnel construction planning system, developed for Okamura Corp. (Harada, Igarashi et al. 1990). Use of this ES has cut planning time in half, reduced variations in the plans due to personal factors, facilitated the preparation of alternative plans, and given inexperienced engineers the capability to draft detailed construction plans. The system (which combines KBS, relational databases, CAD and a reporting system) has been used on at least 20 projects to date.
Process Scheduling. Another highly successful system is for process scheduling in chemical plants. Use of the system has resulted in reducing the costs of raw materials and labor by billions of yen annually.
Initially, most of Hitachi's business applications were in banking and financial diagnostic systems, but more recently, industrial clients have requested scheduling systems. The largest application market now is in the insurance industry. Within the domain of planning and scheduling, job shop scheduling is the biggest market, accounting for 40-50 percent of the business, followed by process scheduling. Planning and scheduling applications got started three years ago. A Hitachi engineer worked with a customer to figure out how to do a planning application on ES/KERNEL after the customer had failed using a competitor's shell. Initially, the scheduling job took 17 hours, but eventually was reduced to five minutes of workstation time. The system has saved ´7 billion. Hitachi is familiar enough with scheduling problems to divide them into four classes, each with its own solution technique. Until now, Hitachi has done most of the planning applications for customers, but is beginning to introduce courses so that customers can learn to do this task themselves.
Approximately 500 expert systems have been developed at Toshiba for both internal and external use, with about 10 percent in routine use. Design and planning/scheduling are the major growth application areas. Within design, the principal tasks are LSI and PCB design.
Paper Production. The most successful expert system is a paper production scheduling system for the Tomakomai mill of Ohji Paper Co., Ltd. The system uses 25 kinds of pulp, which are combined in 10 papermaking machines to produce 200 different paper products. There are hundreds of constraints to be satisfied. The system employs a top-down hierarchical scheduling strategy, starting with scheduling product groups, then individual products, and then line balancing. This application has reduced the time required to produce a monthly schedule from three days to two hours.
Microwave Circuit Design. Toshiba also reported data on a microwave circuit design system, called FIRE, built with an internally developed tool called Debut. FIRE captures the design process for highly parametric design problems. The system runs on a workstation, is C-based, and interfaces with microwave circuit simulators and a mechanical CAD system. The primary benefits of the system are speed-up of problem solving and accumulation of design knowledge.
A fault diagnosis system developed for Kyushu Electric Company is representative, and is in routine use by Kyushu operators. The system diagnoses faults and restores operation to an electric power system. The fault diagnosis system has 900 rules; the fault restoration system has 600 rules. The system was built using TDES-3, a real-time application shell that uses rules and frames for knowledge representation. The development team consisted mostly of Toshiba personnel, with domain experts supplied by Kyushu.
Toshiba also reported on a diagnostic system for a subway station facility, called SMART-7, which was built for the Tokyo Eidan 7th line. The system was built with a diagnostic knowledge acquisition support tool called DiKAST. SMART-7 is implemented as a support module that detects malfunctions in the air conditioning facilities. The system contains 1600 frames, and runs on a workstation. It was built by three system engineers in three months.
Electric Subassembly. Another expert system is used for placing electronic components on printed circuit boards. The knowledge base consists of about 70 rules and 8500 functions, and was built on top of the ASIREX tool. The ES is integrated with a PCB CAD tool called BoardMATE, a commercial product developed by Toshiba. The system took three years to develop, with an estimated labor cost of three man-years. The system has sped up problem solving by a factor of 10.
DSS. A small knowledge system (110 rules, 32K lines of C code) that Toshiba sells is MARKETS-I, a decision support system to determine the suitability of opening a convenience store at a particular site. Estimation accuracy is improved with the use of this system.
Banking. ESCORT is a banking operations advisor system that is used in Mitsui Bank. It plans the most appropriate procedure to get the computer banking system back on line following an accident. The system has about 250 rules and 900 frames, and was built using a LISP-based expert system shell called ExPearls. The GUI was written in C. The system runs on the AS3000 workstation.
Software Engineering. In the area of software engineering, Toshiba has developed an automatic programming system for sequence control. This system generates a control program for a steel plant from high-level specifications. It analyzes and refines the specification, generates code, and retrieves program modules. This is a fairly large system: 2,900 frames, 320 rules, and a library of 190 program modules. It was written in LISP, using an internally developed frame-based knowledge representation language with object oriented facilities. Twenty person-years went into its development, over a four-year span. The system has resulted in cost reduction and an improvement in the quality of the sequence control program designs. Test and verification are performed manually.
Reasoning Methodologies. One of the most advanced applications that was described to JTEC combines model-based and heuristic reasoning. The system is used for control of a manufacturing or processing plant (Suzuki, Sueda et al. 1990). The shallow reasoner uses knowledge in the form of a heuristic control sequence (see Figure 2.10). When unforeseen events occur, for which the shallow knowledge is inadequate, the system can resort to deep knowledge, in the form of a model of the plant, to reason about an appropriate control sequence. The deep knowledge includes the structure of the plant, the function of the plant devices, causal relations among plant components and principles of operation. The system combines several advanced technologies: model-based reasoning, knowledge compilation, and qualitative reasoning.
The following approach is used: If the shallow knowledge is insufficient, go to the deep model. In the deep model, (1) use the causal model to deduce the abnormality; (2) find the operations that would bring the plant to a desired state; (3) find the conditions under which an operation should be performed; (4) simulate to test the hypotheses (the simulator uses qualitative reasoning and fuzzy control techniques). The knowledge estimator checks to see if the simulation indicates any unforeseen side effects. If the answer is yes, then the system determines what supplementary operations should be performed. If the simulation result is satisfactory, the knowledge is stored in rule form for future use. This process is called knowledge compilation.
Figure 2.10. A Plant Control System Using Deep and Shallow Knowledge
The techniques of model-based reasoning and knowledge compilation have also been employed in an innovative system, called CAD-PC/AI, for automatically generating sequence control programs for programmable controllers. (For further details see Mizutani, Nakayama et al. 1992).
Assessment. Toshiba systems do not now use multiple sources of expertise, but they are trying to do so in their newer systems. Many ESs are implemented with a combination of a shell/tool plus a programming language such as C or LISP. The company has several training courses, ranging from a one-day basic course, to a two- to three-week application development course, to a multi-week advanced topics course. About 10 percent of research funds go into training. An important element of Toshiba methodology is to use task-specific shells, such as PROKAST or DiKAST.
ESs selected for implementation are chosen by a systems engineer or researcher. This technology is used only when conventional DP doesn't work. The prespecified selection criteria are performance and practical value. An economic justification is also sought. Usually the same people are used in all phases of application selection, development, insertion into the operational activity, maintenance and redesign.
Toshiba's largest project to date is a 5,000 rule system for diagnosis and control of an electrical power generator.
NEC has developed about 1,000 ES applications, of which 10 percent are in routine operation. The major task areas are diagnosis, scheduling, design, and software development aids. NEC's biggest success is the crew scheduling system, COSMOS/AI, developed with Japan Air Lines, discussed previously. Other applications include a software debugging advisor; FUSION, an LSI logic design tool; and a system called SOFTEX for synthesizing C/C++ programs from specifications (represented as state transition tables and/or flowcharts). SOFTEX is a 300-rule system built with EXCORE (see Chapter 3), developed by professional programmers and domain experts. The system is still about six months to one year from routine use. In order to make the system appeal to programmers, it has been necessary to incorporate in SOFTEX the functionality to enable customization, so that the generated program can fit each programmer's style.
Assessment. NEC admits to some unsuccessful projects, and attributes the lack of success to a number of reasons, including the knowledge acquisition bottleneck, the difficulty of integration with existing systems, and knowledge base maintenance. Unfortunately, these problems tended to get detected late rather than early.
Future ES applications at NEC are expected to employ technologies such as model-based diagnosis, case-based reasoning for scheduling and for software synthesis, and combining ES methods with algorithmic methods (model-based reasoning is one example).
NTT currently has 36 expert systems under development. Half of these systems perform diagnosis on various components of a communications system. Their most successful ES performs failure diagnosis and support of crossbar switching equipment. A task that typically takes four hours has been reduced to five minutes using the system. However, the main motivations for developing the system were the planned phase-out of crossbars and the need to avoid training new people on an obsolete device. Thus, the expert system's main value is in capturing and preserving expertise.
Nippon Steel has developed 100-130 expert systems for internal use (very few for external use). About 30 percent of these are now in routine use. Although most of the current applications are diagnostic/troubleshooting systems, the fastest growing area is in planning and scheduling.
Diagnostic/Process Control. Nippon Steel selected three representative applications to present to the JTEC panel, two of them diagnostic and one for process control. The first is a system for process diagnosis, used in the Oita works. The system is used in three factories for troubleshooting electrical and mechanical equipment, and has resulted in a reduction of production costs, development costs, and/or plant operators. The knowledge base contains about 160,000 knowledge fragments (comparable to about 50,000 rules). The system was developed with Nippon Steel's own shell, called ESTO, written in C++, and runs on networked Sun workstations. About 20 man-years went into its development, over a two-year period. The economic payback of this system is estimated to be about $2 million annually. The reliability of Sun hardware has been a problem in keeping the systems in use.
The second representative system provides supervision of blast furnace control. This is a large system, with 5,000-6,000 production rules. It was built on top of Hitachi's commercial tool EUREKA plus a neuro simulator tool called AMI, which was developed internally, and runs on a minicomputer. AMI was used to build a neural network for preprocessing (pattern matching) the raw data before it is input to the expert system. The principal paybacks have been improvements in decision making and in quality of product. About 14 man-years were expended in development, over two years. A major problem has been maintenance of the KB, which is not easily understood by people who had not built it.
Design. The third system is a design expert system for designing shaped beams. This is a large system, containing 3000 production rules and 500,000 lines of code, in LISP, FORTRAN and C. The system was built using ART (from Inference Corp.) and runs on networked Sun workstations. Twenty technical people (4 domain experts, 16 knowledge engineers) developed the system over an 18 month period. The principal payback is in reduction of the design cycle time by 85 percent and an increase in design accuracy of 30 percent. The estimated economic return is $200,000 annually. The system is felt to be too expensive, requiring a copy of ART at each new site.
Assessment. When developing systems that use multiple sources of knowledge (experts) the people at Nippon Steel have adopted a structured development method, much the same as used in conventional software development, which they feel is necessary to avoid unnecessary confusion. For diagnostic systems, they use their in-house tool, ESTO, which is designed to accommodate incomplete and inconsistent knowledge from multiple knowledge sources.
Nearly all systems are integrated with other systems, e.g., data processing, and Nippon Steel is working to establish an inter-factory LAN to facilitate this integration. Of 28 systems developed within the past two years, 60 percent can be characterized as using a combination of a rule-based inference engine plus added code written in a conventional language, typically C. A few systems integrate rule-based, fuzzy and neural network methods. Commercial tools were found to be inadequate in the way they permit access to external functions written in conventional languages, which motivated Nippon Steel to develop its own tools. Problems with current technology include slow execution speed for large-scale systems, high cost in time and effort of knowledge maintenance, lack of transparency of the inference process, tedious integration with existing software, and the general problem of knowledge acquisition.
The company cited many reasons for selecting an expert system application, among which are to acquire know-how, to capture and distribute expertise, to improve revenues and to reduce costs.
Most of the systems that have been developed are small (under 100 rules). It was found that the time to develop large projects increases more than linearly with the number of rules. The in-house consultants advise developers to keep their knowledge bases to within 300 rules, and if more are needed to segment the KB into modules each of which is within 300 rules.
Looking ahead several years, Nippon Steel envisions new expert systems that perform planning and scheduling over multiple factories or production lines. Future diagnostic and process control systems will employ model-based and case-based methods for more in-depth problem description and for recovery following diagnosis, with a capability for closed-loop control. Future planning/scheduling systems will be fully automatic and able to plan with multiple objectives. Future tools (infrastructure) will require knowledge engineers, be task-specific within a general problem solving paradigm, use a standard knowledge representation, and have a better user interface.
NKK has 25 ESs in routine operation, and five more in the field testing stage. Of the 37 systems that have been built or are in some stage of development, 16 combine the functions of advising, process control and diagnosis; 20 combine the functions of advising, planning/scheduling, and management integration aid. The two major applications are the blast furnace expert system discussed earlier in this chapter and a steelmaking scheduling system (Tsunozaki, Takekoshi et al. 1987; Takekoshi, Aoki et al. 1989).
All of the fully developed systems are integrated with conventional systems, and also use some high-level language (LISP, FORTRAN, PL-1) in addition to the ES shell (ESHELL for the blast furnace, KT for the planning/scheduling systems).
Rather than emphasize training in knowledge engineering and expert system development, NKK has chosen to train its systems engineers in systems analysis and modeling, which are more important skills for total system development. Expert systems techniques in themselves are of relatively small significance, in NKK's view. On the other hand, the company has developed expert system design tools, used in the Engineering and Construction Division, which embody a methodology for developing ESs. These tools, called NX-7 and NX-8, run on Xerox LISP machines and Sun workstations, and have been applied in developing ESs for operations support of refuse incinerators.
NKK often introduces an ES at the same time as it refurbishes its entire computer system (which itself may be just a part of a larger renewal project), making it difficult to evaluate the impact of the introduction of the ES. However, ESs are introduced only when conventional programming techniques fail to solve the problem at hand.
Regarding future development, NKK sees more use of in-the-loop control, moving from mainframes to engineering workstations and providing intelligent assistance on more advanced tasks of engineering and management. The company sees several problems with current technology: AI tools that are difficult to learn and use; relatively high difficulty in system maintenance; inadequate processing speed; the need to obtain knowledge automatically from data, and the need to solve problems (e.g., scheduling) by using previous cases.
The JTEC team visited the Industrial Electronics and Systems Lab (IESL), a small group especially focused on power industry (electrical) problems. Thus we saw a very small part of the total ES activity at Mitsubishi Electric.
Mitsubishi Electric's single most successful application has been the ES for elevator group control, discussed earlier. Another success story is a fuzzy logic control system for metal machining, which became part of an electron-beam cutting machine that began selling three or four years ago.
Diagnosis. IESL has built three systems for internal use for finance, diagnosis, and planning (all are prototypes). The diagnosis system employs qualitative process modeling to determine problems with a boiler system. It started out as a 200-rule system, but when implemented with DASH is only 70-80 rules (some component knowledge is reusable). The system is fielded at Kansai Electric Power but is not in routine use yet. It reduces the time to make a diagnosis from three to four minutes down to one minute.
Energy Management. IESL is most interested in ES for energy management of electric power distribution networks. It envisions the technology used for diagnosis, restorative operation, reliability assessment, dispatching control, and operations planning. There are currently three energy management systems (EMS) (one from Mitsubishi Electric) in practical use in Japan. The Mitsubishi one is in use at the Kansai power distribution center. The KB is relatively small -- about 200 rules. There are six more systems in field test.
Assessment. Mitsubishi finds that Japanese power companies are very eager to use ES technology. They were led to believe that U.S. power companies were not interested in the technology, even though the Electric Power Research Institute (EPRI) appears interested.
IESL has a lot of experience in network diagnostic problems, so it does not have much failure in this area. In general, where an ES is built as an integral part of a larger system, the failure rate is very low. Mitsubishi considered integration from the very beginning and thus did not experience problems of integrating stand-alone ESs after they were built.
We were given a breakdown of types of ES applications in the power industry world-wide: diagnosis, 25 percent; operations, 25 percent; monitoring, 15 percent; control, 15 percent; planning 10 percent; others (simulators, maintenance, design, system analysis), 10 percent.
TEPCO has developed 30 systems, of which 11 are in routine use. The application domains for these 11 include design, consultation, control, prediction, planning and scheduling, fault location, hot-line service, and computer operations. Three systems are in field test, 14 in the prototyping, and two in the feasibility stage.
Forecasting. The most successful system is the daily maximum load forecasting system. Measures of success have been user satisfaction, a reduction in the absolute forecasting error rate from 2.2 percent to 1.5 percent, and a four-fold speedup in forecast generation. The system is actually quite small, with only about 100 rules, and was built using Toshiba's TDES3 tool. It runs on a Toshiba minicomputer and also on Toshiba workstations (Sun workstation compatible). The forecasting system is one component of, and integrated with, a much larger load forecasting system called ELDAC. The system was developed at a cost of approximately $2 million over a period of about 20 months. Two researchers and two experts at TEPCO designed the system and three system engineers from Toshiba built it. It is now used routinely by load dispatchers. Although the ROI is difficult to estimate, the use of the system precludes the need for a standby generator at a power station.
Assessment. About 50 percent of TEPCO's ES projects advance from the prototype stage to an operational system. The company's AI Technology Department is actively pursuing fuzzy logic, neural networks, genetic algorithms and computer graphics in addition to expert systems. Our TEPCO hosts made it clear that to them "AI" means not only Artificial Intelligence but also Advanced Information Technology.
Obayashi has built 25 expert systems for internal use and one for external use. Of these, six are in routine operation and nine more are at the field testing stage. Most of the systems (14) are classified as advisory systems.
Direction Control. Obayashi's most successful system is an automatic direction control system for shield tunneling (a method of tunnel construction first used in England in the 19th century). This system controls the direction of drilling, which must be accurate to within five centimeters per one kilometer of tunnel length. The non-linearity of the problem precludes the use of a mathematical model. The ES is now in use in some (not all) of Obayashi's drilling operations. The system is built on top of two shells, called AI-DNA and AI-RNA, sold by AdIn, a Japanese AI company. The system uses fuzzy control in its problem solving, is stand-alone, uses the C language, contains about 10,000 lines of code, and runs on a personal computer. It was designed and built by two civil engineers, two mechanical engineers, and one systems engineer (plus programmers), and is maintained by the domain expert and two technicians. Development time was one year, including the testing period. The primary payback has been improvement in the quality of direction control, and in a three to one reduction in personnel required for this task.
Assessment. Obayashi representatives report that 70 percent of ES projects that are started get as far as a prototype, and 30 percent actually get to an operational system. Using existing tools, they can envision building systems up to the size of a few thousand rules. Future systems planned by the corporation include other automatic control systems and intelligent CAD. The primary perceived problems with present technology are: knowledge acquisition; constructing design systems; incorporating model-based and case-based reasoning; and machine learning.