Abstract: A data analyzing device, a data analyzing method, and a quality improvement system are provided. The data analyzing device includes a combination generating module, a ratio calculation module, and a weighting calculation module. The data analyzing device performs relevance analysis of to-be-analyzed data associated with a production operation procedure to generate relevance information. The ratio calculation module calculates a ratio parameter according to a total outlier product quantity corresponding to risky combinations in the relevance information and a total product quantity in the to-be-analyzed data. The weighting calculation module calculates a weighting parameter according to a number of the risky combinations in the relevance information and a total number of combinations of production control factors in the to-be-analyzed data. A production equipment selectively adjusts settings of the production operation procedure according to the ratio parameter and the weighting parameter.

Abstract: A dispatching method and system based on multiple levels of steady state production rate in working benches are provided. The dispatching method includes the following steps: receiving a plurality of real-time streaming data regarding a plurality of products being produced by a plurality of productive working benches; grouping the production rate values comprised in each real-time streaming data according to a first data binning technique, so as to produce a first steady state production rate value corresponding to each real-time streaming data; grouping the production rate values comprised in each real-time streaming data according to a second data binning technique, so as to produce a second steady state production rate value corresponding to each real-time streaming data; and determining a dispatching message of a to-be-produced product according to a portion of the first steady state production rate values and a portion of the second steady state production rate values.

Abstract: An apparatus and method for determining a target adjustment route for a preset control condition set of a production line are provided. The apparatus establishes at least one candidate adjustment route for the preset control condition set according to the historical control condition sets. Each candidate adjustment route includes at least one adjustment control condition set arranged in an adjustment order. Each adjustment control condition set is one of the historical control condition sets. Within the same candidate adjustment route, the historical yield related values corresponding to the adjustment control condition sets are all greater than the preset yield related value and increase in the adjustment order. Within the same candidate adjustment route, the numbers of the adjustment control condition(s) included in the adjustment sets increase in the adjustment order. The apparatus selects one of the candidate adjustment route(s) as the target adjustment route.

Abstract: An apparatus and method for detecting impact factors for an operating environment. The apparatus generates a detection result for each of the first factors of a plurality of first historical records by analyzing a dissimilarity degree of the plurality of first data corresponding to each first factor. Each detection result is a continuous data type or a discrete data type. The apparatus trains a data type recognition model according to the first historical records and the detection results. The apparatus establishes a basic prediction model by a training set of a plurality of second historical records, generates a comparison set by rearranging the second data corresponding to a specific factor in the training set, establishes a comparison prediction model by the comparison set, and determines a degree of importance of the specific factor by comparing the accuracies of the basic prediction model and the comparison prediction model.

Abstract: An apparatus and method for determining a target adjustment route for a preset control condition set of a production line are provided. The apparatus establishes at least one candidate adjustment route for the preset control condition set according to the historical control condition sets. Each candidate adjustment route includes at least one adjustment control condition set arranged in an adjustment order. Each adjustment control condition set is one of the historical control condition sets. Within the same candidate adjustment route, the historical yield related values corresponding to the adjustment control condition sets are all greater than the preset yield related value and increase in the adjustment order. Within the same candidate adjustment route, the numbers of the adjustment control condition(s) included in the adjustment sets increase in the adjustment order. The apparatus selects one of the candidate adjustment route(s) as the target adjustment route.

Abstract: An apparatus and a method thereof for determining a control condition set of a production line. The apparatus divides several historical control condition sets into several groups, wherein the historical control conditions corresponding to the same control factor are the same in each group. For each group, the apparatus calculates a measurement of central tendency according to the historical yield related values in the group. The apparatus decides a subset of the groups. For each group in the subset, the apparatus calculates a degree of variation and a number regarding the different control conditions between the control condition set and the group. The apparatus calculates weight scores. Based on the measurements of central tendency and the weight scores, the apparatus selects one of the groups as a selected group and assigns the historical control conditions of the selected group as the control conditions of the control condition set.

Abstract: An apparatus and a method thereof for determining a control condition set of a production line. The apparatus divides several historical control condition sets into several groups, wherein the historical control conditions corresponding to the same control factor are the same in each group. For each group, the apparatus calculates a measurement of central tendency according to the historical yield related values in the group. The apparatus decides a subset of the groups. For each group in the subset, the apparatus calculates a degree of variation and a number regarding the different control conditions between the control condition set and the group. The apparatus calculates weight scores. Based on the measurements of central tendency and the weight scores, the apparatus selects one of the groups as a selected group and assigns the historical control conditions of the selected group as the control conditions of the control condition set.

Abstract: The disclosure generally relates to reactive electrochemical membranes (REMs); and in particular, to asymmetric reactive electrochemical membranes to be used for aqueous separations and membrane fouling regeneration.

Abstract: A dispatching method and system based on multiple levels of steady state production rate in working benches are provided. The dispatching method includes the following steps: receiving a plurality of real-time streaming data regarding a plurality of products being produced by a plurality of productive working benches; grouping the production rate values comprised in each real-time streaming data according to a first data binning technique, so as to produce a first steady state production rate value corresponding to each real-time streaming data; grouping the production rate values comprised in each real-time streaming data according to a second data binning technique, so as to produce a second steady state production rate value corresponding to each real-time streaming data; and determining a dispatching message of a to-be-produced product according to a portion of the first steady state production rate values and a portion of the second steady state production rate values.

Abstract: A plastic extrusion process control method includes: receiving a plurality of historical process data of a plastic extrusion process from a database, in which each of the historical process data includes a plurality of critical parameters and a plurality of quality value; dividing each of the critical parameters into a plurality of levels; grouping the historical process data according to the levels of the critical parameters to obtain a plurality of parameter sets; calculating a quality indicator of each of the parameter sets to build an empirical response surface according to the historical process data corresponding to the parameter sets; and configuring the critical parameters of the plastic extrusion process to an automatic manufacturing system according to the empirical response surface, such that the automatic manufacturing system performs the plastic extrusion process according to the critical parameters.

Abstract: A plastic extrusion process control method includes: receiving a plurality of historical process data of a plastic extrusion process from a database, in which each of the historical process data includes a plurality of critical parameters and a plurality of quality value; dividing each of the critical parameters into a plurality of levels; grouping the historical process data according to the levels of the critical parameters to obtain a plurality of parameter sets; calculating a quality indicator of each of the parameter sets to build an empirical response surface according to the historical process data corresponding to the parameter sets; and configuring the critical parameters of the plastic extrusion process to an automatic manufacturing system according to the empirical response surface, such that the automatic manufacturing system performs the plastic extrusion process according to the critical parameters.

Abstract: The disclosure generally relates to reactive electrochemical membranes (REMs); and in particular, to asymmetric reactive electrochemical membranes to be used for aqueous separations and membrane fouling regeneration.

Abstract: A stable manufacturing efficiency generating method includes the steps: generating a real-time grouping parameter set according to a plurality of historical efficiency values; grouping a plurality of real-time efficiency values corresponding to a product to generate a plurality of real-time efficiency groups according to the real-time grouping parameter set; selecting one of the real-time efficiency groups having most real-time efficiency values as a stable efficiency group; and generating a stable manufacturing efficiency value according to an average value of the real-time efficiency values in the stable efficiency group.