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Ritalv
Community Manager Community Manager
JMP讓可靠度管理更高效

近年來,越來越多的企業開始注重提升產品的可靠度。可靠度已經成為衡量產品品質的重要指標之一。所謂可靠度是指在規定的使用條件下,規定的時間內產品完成規定功能的機率。很多企業在實施可靠度管理時碰到的一個問題是當產品的可靠度管理發展到一定階段,必定會用到統計建模方法,而由於可靠度統計建模方法相對更複雜,很多號稱六標準差黑帶大師的諮詢師都不敢輕易碰它,這無形中給可靠度分析蒙上了一層神秘的面紗。

品質管理大師朱蘭在研究產品的品質元素時,曾將各種不同的品質特性歸納總結,分為三個大類:第一,技術特性,如強度、硬度、電壓等;第二,心理特性,如知覺、視覺、味覺等;第三,與時間相關的特性,如可靠度、可維修性等。由此可見,可靠度是品質管制中不可或缺的重要內容。

 許多知名汽車廠家已開展可靠度工作多年,通用公司就是最早引入可靠度概念進行產品設計生產的公司之一。經過了長期的可靠度工作開展後,通用汽車的可靠度水準顯著上升。最近幾年美國權威汽車研究機構J.D.Power公佈的北美地區汽車車輛可靠度(VDS)調查報告顯示,通用汽車旗下別克品牌長期位居三甲,表現非常穩定。

除了汽車行業,可靠度工程在其他製造業內也有廣泛的應用。留心觀察英特爾、陶氏化學等公司將可靠度工具融入企業原有的“研發、生產和顧客現場使用”價值鏈中的寶貴經驗,不難發現,其成功的關鍵因素之一就是讓可靠度不再成為少數研發精英的專寵,而是將可靠度分析視覺化、簡單化,使之成為眾多技術人員都可以使用的尋常工具,可以從中獲取決策依據的改善利器。

平心而論,十幾年前,要實現這一點還是具有相當難度的,普通企業的感覺是可靠度“可望而不可及”。然而,近年來現代電腦技術的迅猛發展和成熟使企業具備了跨越傳統技術障礙的前提條件,以專業品質管制統計軟體JMP為代表的諸多可靠度工具載體,開創了互動性、視覺化的先進分析模式,兼具操作簡易、分析高效的優點,讓可靠度走下神壇,走向“平民化”。

下面將著重介紹可靠度分析的幾個主要應用方向,以及JMP互動式視覺化的可靠度分析帶給企業的幫助。

 

l   壽命資料分佈

    在可靠度工程中,如果能夠將產品的壽命資料擬合為某一機率的分佈,就可以利用這個分佈的特性進行產品設計、製造的評估決策。但是困難的是,可靠度資料存在著設限特性,其機率分佈比一般資料的分佈擬合要複雜得多,也難理解得多。而借助JMP軟體,工程師只要輕鬆點擊滑鼠,即可在幾秒內從Weibull、對數正態、指數等十餘種分佈中進行智慧識別,尋找出最匹配的壽命資料的分佈類型,以便我們精確地預測產品的使用壽命、失效機率、失效機率密度和故障率等。

壽命資料分佈壽命資料分佈

l   可靠度預測

     在瞭解壽命資料的分佈情況之後,我們還可以進一步做可靠度預測。JMP可以幫助我們預測將來失效的次數。使用互動式圖形,調整將來產量和契約期限之類的因子,就可以估計將來的失效。

可靠度預測可靠度預測

 

l  加速壽命試驗

  如果想進一步量化地了解不同的負載條件可能對產品產生的影響,則需要用到比傳統的一元回歸分析要複雜得多的統計方法。JMP軟體將這個分析過程化繁為簡,把複雜的統計學原理轉化為一系列圖形組合,栩栩如生地展現出加速壽命因子(如本例中的溫度等)在不同水準時對產品壽命的影響程度。

加速壽命試驗加速壽命試驗

l   參數生存模型

    很多情況下,影響產品壽命的還不僅僅只有溫度一個負載條件,還可能包括濕度、振動、輻射、壓力、化學物質、沙塵、電壓、電流和人為因素等。怎樣才能綜合、直觀地表現所有因素對產品壽命的影響呢?在JMP中,這個問題的解決方案是用一種簡單易懂的“模型刻畫器”形式來精確地表現各個影響因素(如本例中的塗層、攝氏溫度等)與產品可靠度的關係,暫態同步地預測不同條件下的失效機率和產品使用壽命。

參數生存模型參數生存模型

 

l   產品老化分析

     如果要對產品的品質特性有更加深入的認識,我們不能僅僅用“失效”、“沒有失效”來表示產品的品質狀態,還要盡可能用一個連續變數來描述產品的特性變化。只要記錄了相關的資料,工程師使用JMP就能通過線性或非線性形式對產品特性(如本例中的Current等)的老化過程進行更加精確的模型擬合,並以此為基礎預測產品失效的發生時間,以及產品特性隨時間變化的規律。
產品老化分析產品老化分析

 

l   可靠度實驗設計

    可靠度分析的資料主要來源於可靠度實驗,可靠度實驗的時間一般較長,而且對產品都有破壞性。為了降低成本,我們需要用最少的實驗樣品、最短的實驗時間來最大限度地獲取資訊。JMP是一款在實驗設計領域享有聲譽的軟體,工程師可以靈活方便地計算開展可靠度檢驗實驗和可靠度驗證實驗所需的樣本數量和時間長度,還可以設置開展考慮因子間交互作用的單因子(如本例中的扭矩等)或雙因子加速壽命實驗時的實驗條件組合,以及計算每種實驗條件下的樣本數量。可靠度實驗設計可靠度實驗設計

Last Modified: Jun 12, 2019 7:12 AM