Improving constructibility with optimal overlapping locations of steel bars
鋼筋裁切 ； 鋼筋搭接 ； k-means分群演算法 ； 線性規劃 ； Steel Cutting ； Steel Overlapping ； K-means Clustering Algorithm ； Linear Programming
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近年來由於國際間原物料價格波動劇烈，至 97年 6月份時，國內鋼筋指數達到高峰，而鋼筋對於營建工程來說屬於大宗材料，因此思考如何減低其耗損與浪費，已變成是營建管理研究上極具潛力的一個課題。 一般在工程實務上，鋼筋工程於發包後，有關繪製鋼筋施工圖以及揀料單之工作，多半交由鋼筋分包廠商中工程經驗較為豐富之鋼筋師傅處理，其往往為了鋼筋便於裁切、考慮施工性及材料管理方便，常強制需求鋼筋長度成為尾數為5或10cm的倍數，藉以降低尺寸之多樣性，甚至是為了配合揀料單中需求數量較多之鋼筋尺寸，將需求鋼筋長度加大。另外隨著工程規模增加，需求鋼筋尺寸種類也越加繁複，所以在鋼筋施工及搭接綁紮時，因鋼筋尺寸混淆，錯以長度較長之鋼筋，取代原有長度較短鋼筋之情形，屢見不鮮，也因此造成鋼筋材料無謂之浪費。然而回顧以往對於鋼筋材料支出控制的相關文獻，僅以工程初期的鋼筋裁切問題作為研究範疇，缺乏針對工程實際鋼筋配筋的需求問題作探討，故上述於實作時所產生材料浪費之情形，迄今仍未獲得有效之改善。 因此，本研究以建築工程樓版配筋為例，利用鋼筋搭接位置的調整，改變原有需求鋼筋尺寸，並採用k-means分群演算法，建構鋼筋分群模式，減少鋼筋繁雜眾多的尺寸，再運用線性規劃方式，求解在不增加原有成本目標下之最佳分群結果。 在本研究中，以一真實建築個案作為範例，該案例為一RC構造建築物，基地面積長約65.4公尺，寬約59.7公尺，建築規模為地下4層、地上7層，而每層樓版之橫向或縱向跨度最多均為14個，經揀料結果，原有相同號數、形狀之需求鋼筋樣本數為694個，以長度分類，可分為41個群組；經本研究所撰寫程式分群演算結果，鋼筋群組數降低為16組，大大增進其工作性，證明本研究之論述，確實可以運用於工程實務上，達到降低鋼筋長度樣態、減少施工錯誤、提昇施工便利性之目的。
Due to violent fluctuation of raw material prices in the international market, the domestic steel bar index reached its peak in June 2008. As steel bars are massive materials required for constructional engineering, it has become an urgent potential issue in the research of construction management by considering how to minimize their consumption and waste. In engineering practice, the experienced steel bar engineer of the subcontractor is usually assigned to prepare the construction drawing and the material selection list. Taking account of the easier cutting of steel bars, convenient workability and material management, it is frequently required that the length of steel bars should be processed into a number that is a multiple of 5cm or 10cm so as to minimize the diversity of sizes; sometimes, the required length of steel bars is also lengthened to match the size of steel bars with a larger quantity in the Material Selection List. Along with the expansion of construction scale, the type of steel bar size is also becoming more complicated. It is frequently seen that shorter bars are wrongly replaced by longer ones due to the confusion of steel bar sizes during steel bar erection, overlapping and binding, this has lead to waste of steel bar material. Since relevant literature relating to steel bar material expenditure and control only deal with the steel bar cutting issues at the initial construction stage, but lacks the steel bar arrangement required by practical construction, the aforesaid waste during field construction has not been effectively improved until now. For this reason, the floor deck steel bar arrangement of the building construction will be selected as the example for this Research. By adjusting the steel bar splicing position, the size of originally required steel bars will be changed. Further, the “K-means Clustering Algorithm” is also used to configure the steel bar clustering mode so as to reduce the diversified sizes of steel bars. As a further step, the Linear Programming Method will be employed to acquire the optimal clustering result without increasing the original cost. In this Research, a physical building case will be selected as the example. The said case belongs to an RC structure in which the foundation area size is 65.4m (L) x 59.7m (W) and is constructed into 4 underground levels and 7 above-ground floors, and each floor is provided with a maximum of 14 horizontal or longitudinal spans. The material selection result indicates that the steel bar samples having the same number and shape is 694 pieces and this has been divided into 41 groups by length. According to the program-based clustering computation written for this Research, the result indicates that the steel group count will be reduced to 16 groups and the workability will be significantly enhanced accordingly. With the above information, it can be seen that the statement of this Research is justified and can really be implemented in the practical construction field to achieve the purpose of reducing the steel bar length types,minimizing construction error and alleviating the work accessibility.
工程學 > 土木與建築工程