• 전자공학회논문지B
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• 제32B권3호
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• pp.89-99
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• 1995

One of the hardest problems that limit real application of production system is its slowness. One way to overcome this problem is to speed up the matching operation which occupies more than 90% of the total execution time. In this paper, we try to speed up the matching operation with parallel execution of a typical pattern matching algorithm, RETE, in a multiprocessor environment, This requires not only to make partitions of the rules but also to allocate the partitioned rules to processors, respectively. A partition strategy is proposed to make groups of similar rules by evaluating the similarity of rules according to the number of common conditions between rules. An allocation strategy is proposed to make the load of each processor even by assigning the different priority to the group of rules according to the expected amount of time required for matching operation. To compare with the existing methods, we perform simulation using OPS5 sample programs. The simulation results show that the proposed methods can improve the performance of production system.

• 한국경영과학회지
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• 제23권1호
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• pp.161-181
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• 1998

Translating expert knowledge into production rules has been the most difficult and time-consuming when building expert systems (Buchanan et al. 1983). Especially, buidling hierarchical structure, i. e. developing sequential or dominant relationship among production rules is one of the most important and difficult processes. Hierarchical relationship among rules has been typically determined in the course of interviewing human experts. Since this interviewing procedure is rather subjective, however, the hierarchically structured rules produced in terms of interviewing is widely exposed to the severe discussion about their validity (Nisbett and Wilson 1977 : Ericsson and Simon 1980 : Kellog 1982). We thus need an objective method to effectively translate human expert knowledge into structured rules. As such a method, this paper suggests the order anlaysis technique that has been studied in psychometries (Cliff 1977 : Reynolds 1981 : Wise 1983). In this paper we briefly introduce the order analysis and explain how it can be applied to building hierarchical structure of production rules. We also illustrate how bankrupcy prediction rules of small-medium companies can be developed using this order analysis technique. Further, we validata the effectiveness of these rules developed by the order analysis, in comparison with those built by other methods. The rules developed by the proposed outperform those of the other traditional methods in effectively screening the bankrupted firms.

• 대한산업공학회지
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• 제23권1호
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• pp.197-213
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• 1997

It is not easy to find a good production schedule which can be used in practice. Therefore, production scheduling simulation with a simple dispatching rule or a set of dispatching rules is used. However, a simple dispatching rule may not create a robust schedule, for the same rule is blindly applied to all internal production processes. The presumption is that there might be a specific combination of appropriate rules that can improve the efficiency of a total production system for a certain type of orders. In order to acquire a better set of dispatching rules, simulation is used to examine the performance of various combinations of dispatching rule sets. There are innumerable combination of rule sets. Hence it takes too much computer simulation time to find a robust set of dispatching rule for a specific production system. Therefore, we propose a concept of the knowledge based simulation to circumvent the problem. The knowledge based simulation consists of knowledge bases, an inference engine and a simulator. The knowledge base is made of rule sets that is extracted from both simulation and human intuition obtained by the simulation studies. For a certain type of orders, the proposed system provides several sets of dispatching rules that are expected to generate better results. Then the scheduler tries to find the best by simulating all proposed set of rules with the simulator. The knowledge-based simulator armed with the acquired knowledge has produced improved solutions in terms of time and scheduling performance.

• 정보처리학회논문지B
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• 제10B권7호
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• pp.757-768
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• 2003

본 논문에서는 가중 퍼지 Pr/T 네트에 기반을 둔 규칙기반시스템을 위한 가중 퍼지 추론알고리즘을 제안한다. 이때 퍼지 생성규칙의 확신도, 규칙에 나타나는 술어의 진리값과 술어의 중요도를 나타내는 가중값을 퍼지 숫자로 표현한다. 제안한 추론알고리즘은 퍼지 생성규칙에 있는 술어의 중요도에 따라 부여한 가중값을 이용하여 추론하기 때문에 $\circled1$ 술어의 가중값 없이 퍼지 생성규칙의 확신도만을 기반으로 단순하게 min과 max 연산을 하거나[10], $\circled2$ 술어의 가중값 없이 퍼지 생성규칙에 있는 퍼지 개념에 따라 믿음값 평가함수로 퍼지 생성규칙의 믿음값을 평가하는[12] 방법보다 더 유연하고 사람의 직관과 추론에 가깝다.

• 산업경영시스템학회지
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• 제38권3호
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• pp.78-86
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• 2015

Up-to-date business environment for manufacturers is very complex and rapidly changing. In other words, companies are facing a variety of changes, such as diversifying customer requirements, shortening product life cycles, and switching to small quantity batch production. In this situation, the companies are introducing the concept of JIT (just-in-time) to solve the problem of on-time production and on-time delivery for survival. Though many companies have introduced ERP (enterprise resource planning) systems and MRP (material requirement planning) systems, the performance of these systems seems to fall short of expectations. In this paper, the case study on introducing an APS (advanced planning and scheduling) system based on dispatching rules to a machining company and on finding a method to establish an efficient production schedule is presented. The case company has trouble creating an effective production plan and schedule, even though it is equipped with an MRP-based ERP system. The APS system is applied to CNC (computer numerical control) machines, which are key machines of the case company. The overall progress of this research is as follows. First, we collect and analyze the master data on individual products and processes of the case company in order to build a production scheduling model. Second, we perform a pre-allocation simulation based on dispatching rules in order to calculate the priority of each order. Third, we perform a set of production simulations applying the priority value in order to evaluate production lead time and tardiness of pre-defined dispatching rules. Finally, we select the optimal dispatching rule suitable for work situation of the case company. As a result, an improved production schedule leads to an increase in production and reduced production lead time.

• 대한산업공학회지
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• 제1권2호
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• pp.27-38
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• 1975

This paper explores a quantitative decision-making system for planning production, inventories and work-force in a multi-item production system. The Multi-item Parametric Decision Rule (MPDR) model, which assumes the existence of two types of linear feed-back rules, one for work-force level and one for production rates, is basically an extension of the existing method of Parametric Production Planning (PPP) proposed by C.H. Jones. The MPDR model, however, explicitly considers the effect of manufacturing progress and other factors such as employee turn-over, difference in work-days between month etc., and it also provides decision rules for production rates of individual items. First, the cost relations of the production system are estimated in terms of mathematical functions, and then decision rules for work-force level and production rates of individual items are establised based upon the estimated objective cost function. Finally, a direct search technique is used to find a set of parameters which minimizes the total cost of the objective function over a specified planning horizon, given estimates of future demands and initial values of inventories and work-force level. As a case problem, a hypothetical decision rule is developed for a particular firm (truck assembly factory).

• 산업공학
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• 제12권3호
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• pp.437-447
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• 1999

Modeling and system development for the fabrication process in the semiconductor manufacturing is presented in this paper. Maximization of wafer production can be achieved by the wafer flow balance under high utilization of bottleneck machines. Relatively simpler model is developed for the fabrication line by considering main characteristics of logistics. Simulation system is developed to evaluate the line performance such as balance rate, utilization, WIP amount and wafer production. Scheduling rules and input rules are suggested, and tested on the simulation system. We have shown that there exists good combination of scheduling and input rules.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1326-1329
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• 1993

This work presents a net-based structure to model approximate reasoning using fuzzy production rules, the Fuzzy Petri Net model. The Fuzzy Petri Net model is formally defined as a n-uple of elements. It allows for the representation of simple and complex forms of rules such as rules with conjunction in the antecedent and qualified rules. Parallel rules and conflicting rules can be modeled as well. We also developed an analysis method based on state equations and two fuzzy reasoning algorithms. Finally, the proposed method is applied to an example.

• 정보처리학회논문지B
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• 제9B권6호
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• pp.783-790
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• 2002

본 논문에서는 구간값 퍼지집합 추론의 퍼지 Pr/T 네트 표현을 제안한다. 여기에서 퍼지생성규칙은 지식표현을 위해 사용하고, 퍼지생성규칙의 믿음값은 구간값 퍼지집합으로 표현한다. 제안한 구간값 퍼지집합 추론 알고리즘은 퍼지생성규칙의 전제부와 결론부에 있는 퍼지개념에 따라서 적절한 믿음값평가함수를 사용하기 때문에 다른 방법보다 사람이 사용하는 직관과 추론에 더 가깝다.

• Journal of Mechanical Science and Technology
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• 제14권6호
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• pp.655-665
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• 2000

We propose an efficient algorithm for the purpose of satisfying a wide range of design constraints represented with equality and inequality equations as well as production rules. The algorithm employs simulated-annealing and a production rule inference engine and works on design constraints represented with networks. The algorithm fulfills equality constraints through constraint satisfaction processes like variable elimination while taking into account inequality constraints and inferring production rules. It can also reduce the load of the optimization procedure if necessary. We demonstrate the implementation of the algorithm with the result on machine tool design.