以資料視覺輔助產能規劃的決策

Visualization Assisted Decision Support for Capacity Planning

郭玟琳(Wen-Lin Kuo)

指導教授 ： 孫天龍博士

元智大學/工程學院/工業工程與管理學系/碩士(1998年)

摘要

在動態的環境中做生產規劃，必須考慮許多不斷變動的、不確定性的及相互影響的變數，例如成本、產品生命週期、生產技術、市場趨勢、企業資源配置方法及政治等因素。想要建立一數學模式來評估這些動態變數並找到一最佳方案是非常困難的，故現行的決策過程還是必須靠人來解決。為了讓人更容易瞭解資料含意，通常會將資料轉換成圖形。圖形化的資料呈現利用人類與生俱來的快速視覺特徵辨識能力，讓人更容易、更快速的觀察及瞭解大量而複雜的資料並做出決策。
本研究利用2D格狀圖來將生產計畫及其相對應的機器閒置成本之表格資料視覺化。在生產資料的視覺中我們通常希望將圖形中相鄰且值相近的點指定成同一色，以便觀察如“在規劃期間內產品i的產量形成兩大類別”及“從月份a到b，產品i到j的產量相近” 等的生產特徵。為達此目的，本研究給予格狀圖上每點一權重，權重的計算方式為：若點之同色相鄰點愈多，則權重愈大，並將圖上顏色為C的點之權重總和定義為顏色C的加權面積， 利用模擬退火法將讓每一顏色有近似的加權面積之色值對應找出。在此色值對應下，格狀圖上相鄰且數值相近的點會被指定成同一色。本研究並以實例探討說明發展出之色值對應法在生產計畫資料視覺上之應用。
本研究所探討的另一個問題為格狀圖相似性的評估。在電腦螢幕的大小會限制展現的圖形數目之限制下，通常只能展現與使用者有興趣的特徵指定圖相類似的生產計畫圖形。本研究提出巢狀字串比對法來評估格狀圖的相似性，令GQ為特徵指定圖，GC為比較圖。此法首先利用水平方向字串比對將GC每一列的點轉換到GQ每一列的點，應用水平方向比對結果，第二步的字串比對沿著垂直方向將GC的列轉換到GQ的列。我們以實例驗證此巢狀字串比對法在格狀圖相似性的效益。

關鍵字

資料視覺 ； 產能規劃

並列摘要

Production planning in a dynamic environment involves the evaluation of many ever changing, uncertain, and mutually interacting variables such as cost, product life cycle, manufacturing technology, market trend, enterprise resource allocation strategy, politics and many others. It is very difficult to build a computational model to automatically evaluate these dynamic variables and select the best plans. Current practice still requires human being to be involved in the decision-making process. To assist human planner comprehend the data, visualization of graphical display of the data is often employed. Visualization of data takes advantages of people’s natural strength in rapid visual pattern recognition and enables human planner to quickly and easily examine and comprehend different plans.
In this work, 2D grid graphs are employed to visualize tabular data of production plans and their corresponding idle cost. In this content, it is often desired to assign adjacent points in the graph whose values are close the same color so that production patterns such as “the production amount of product i forms two clusters during the planning period” and “from month a to b, the production amount of products i to j are close” could be easily visualized. To do so, we assign each point in the graph a weight based on its adjacent points that have the same color. The summation of weights of points in the graph whose color is C is then defined as the “weighted area” of C. By finding a color-value mapping that assigns each color near-uniform weighted area through a combinatorial optimization using simulation annealing, the resulted color-value mapping would assign adjacent points in the graph whose values are close the same color.
Another problem we addressed in this work is the development of a graph similarity measure to display multiple grid graphs according to their similarity to a query graph. Due to the screen size restriction, only a limited number of graphs could be displayed in a screen. A useful approach thus is to display only those graphs that are similar to a query graph which represents a production plan that have certain production patterns the user is interesting in. We propose a nested string matching method to access the similarity of grid graphs. Let GQ be a query graph and GC be a compared graph. The method first transform or edit points in each row of GC to points in each row of GQ, which is accomplished by a string matching along the horizontal direction. The match results are then employed in the second string matching which transforms rows of GC to rows of GQ along the vertical direction. Experimental case study is provided to show the effectiveness of the proposed method.

並列關鍵字

data visualization ； capacity planning

參考文獻

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