| Research Abstract |
1) The research result in applying the Gray Theory to production process.
1) The problem of the cumulative flow curve was analyzed using the gray theory. As this result, the relationship between inventory quantity and lead time in the production process was clarified. Especially, the relationship between lead time and inventory quantity was formulated from the theoretical formula. In addition, the production process developed theoretical formula, when there were several. 2) By stock information and production condition in production start point of time, the method for classifying the cumulative flow curve was proposed. And, discrete variant and continuous volume expression of the cumulative flow curve were early clarified from inventory quantity and inflow. In the relationship between inflow of the cumulative flow curve and accumulation value of runoff rate, the equation of average requirement days (lead time) in which the convention had experientially said was theoretically proven. 3)
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Using GM(1,1) model of the gray theory, the relation between gradient of the accumulation line and work capacity of production process was analyzed. Parameter A of GM(1,1) and shape of the cumulative flow curve were clarified, when the primitive data showed upward trend and descent tendency. The relationship between GM(1,1) model and production rate was examined. And, the relationship between inventory quantity and throughput time was clarified on acceptance ability of the cumulative flow curve and shape of the graph of the payment ability and characteristic from the theoretical formula. In addition, it was shown that the cumulative flow curve could apply to a grasp of the controlled state of production process.
2) The research result of analysis by gray theory of the EIQ method and the relation.
1) The method for theoretically analyzing the EIQ method using the gray theory was proposed. The EIQ method was shown according to the GM(1,1) model in the theoretical formula, and largest shipment and item number with the optional multiple and user were examined. And, the shape of the graph was clarified from parameter of accumulation IQ data and accumulation EQ data. And, the characteristic of the graph was clarified on the curvature of the curve. And, the relationship between ratio u/a and initial data of parameter of GM(1,1) was shown in the theorem style. The equation which theoretically calculated item number and customer number which come in within two designated Q1 and Q2 accumulation shipment was proposed. The equation required from u,a of the accumulation IQ model and u,a of accumulation EQ for the decision of basic scale in the physical distribution center was proposed. 2) The method for theoretically requiring order picking system for experientially deciding until now from the EIQ table was proposed. The characteristic in the work time was clarified on single picking, batch picking, zone picking system. And, the theoretical formula was proposed on which system should be theoretically adopted on the each picking system. 3) Shipping characteristic of goods in the physical distribution center is irregular, and the conventional time series analysis can not be applied. Therefore, storage and shipping work of goods, etc. are affected. In this research, the method for classifying goods from distance between accumulation data and value of 2 bits and clearance variable and fuzzy clustering was proposed.
3) The research result of containing production process, the range of the logistics.
1) The algorithm for solving unrelated parallel machine scheduling problem with the fuzzy work time was proposed. 2) In the logistics problem, in making the case with the unclear distance to be a fuzzy value, the theory for newly solving the fuzzy shortest route problem was proposed with the algorithm.
4) Logistics and result of the recycling problem.
1) The decomposition and work can be expressed in the graph theory. Here, the application that proposed and concretizes the combination graph with the liaison graph was shown in respect of the decomposition work. Next, the minute dance work of the product is expressed by ISM. The procedure for making the breakdown graph from the graph of ISM was shown. 2) The work time is made to be a fuzzy value, when the time of the decomposition work is unclear. And, the procedure in search of the fuzzy minimum time of the decomposition work was shown. And, the method for expressing in Bayes theorem and Petri net was proposed in the decomposition work. Less
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