第四章 實例分析
第二節 實例研究
第二節 實例研究
壹、應用價值工程建立 VMI 主、次要機能層級架構
由於 VMI 屬於物流的一部分，以物流的功能依據價值工程對主要機能的定義，將 其作為 VMI 的主要機能，將其整理如表 4.1 所示。
表 4.1 物流的功能
功能 執行
供應管理 採購訂單的設計、輸入、處理、追蹤、供應商管理。
顧客回應 訂單輸入、處理、客戶接觸管理、顧客獲利管理及訂價、顧客追 蹤、退貨處理、服務電話安排、訂單狀態。
存貨管理 週期計算、供應量與承諾度、生產排程、批量追蹤
倉儲管理 越庫作業、裝卸管理、進出貨、儲藏、揀貨、貨運、退貨。
資料來源：何應欽編審(2005)
再以文獻探討，收集與執行 VMI 相關的文獻，將其整理如表 4.2 所示：
表 4.2 VMI 文獻整理
Cottrill (1997) 需求預測、資訊分享。
Kaipia et al.(2002) 存貨水準、顧客需求、POS、EOS。
Tyan & Wee (2003) 存貨控制、補貨計畫、商品條碼、資訊技 術、POS。
Kuk (2004) 銷售資訊、資訊技術(EDI、POS、EOS)。
De Toni & Zamolo (2005) 銷售預測、銷售資料、庫存水準、運送計 畫。
Gronalt & Rauch (2007) 運送方式、銷售資料。
Claaseen et al.(2008) 資訊分享(存貨水準、需求資訊、存貨資 料)、資訊技術、存貨控制。 回收的數據，依照 Zhu、Jing 與 Chang (1999)提出模糊層級分析法的方式計算，其計算 步驟如下：
一、建立模糊正倒值矩陣
將 VMI 主、次要機能以成對比較的方法求取重要度，依此模式設計為問卷的方
存貨管理 (0.393,0.509,0.664) 倉儲管理 (0.038,0.046,0.061) 資料來源：本研究整理
同理，次要機能的模糊重要度的計算方式，如同主要機能的模糊重要度的計算方 式，本研究將次要機能模糊重要度整理如表 4.4：
表 4.4 次要機能之模糊重要度
主要機能 次要機能 次要機能模糊重要度 存貨資料共享 (0.109,0.177,0.285) 配送時機規劃 (0.049,0.066,0.095) 需求資料共享 (0.250,0.379,0.569) 供應管理
銷售資料共享 (0.250,0.379,0.569) 建議補貨量 (0.192,0.250,0.353) 顧客回應
運送規劃 (0.462,0.750,1.177) 電子訂購系統 (0.178,0.292,0.471) 商品條碼 (0.384,0.605,0.943) 存貨管理
銷售點資訊系統 (0.078,0.103,0.150) 規劃補貨計畫 (0.254,0.369,0.526) 存貨控制 (0.381,0.517,0.701) 倉儲管理
通知出貨信息 (0.089,0.113,0.153) 資料來源：本研究整理
三、檢驗一致性
對於公司專家填寫問卷需檢驗是否具有一致性，應用公式(3.2-3.4)作檢驗。以整 合專家意見所填寫主要機能問卷的數據為例，做一致性檢驗，其檢驗過程如下。
1 5 1 5
3 0.320 1.344
1 1
1 1.344 0.430 2.510 0.209
( ) 4.268
4 0.32 0.124 0.509 0.046
λ
= + + + =. . (4.268 4) (4 1) 0.089
(0.227, 0.32, 0.442)⊗(0.109, 0.177, 0.285)=(0.025, 0.057, 0.126)
同理，其餘項目的次要機能也應用此公式修正模糊重要度，修正結果如表 4.6 所 示：
表 4.6 修正次要機能之模糊重要度
主要機能 次要機能 修正次要機能模糊重要度 存貨資料共享 (0.025,0.057,0.126) 配送時機規劃 (0.011,0.021,0.042) 需求資料共享 (0.057,0.121,0.252) 供應管理
銷售資料共享 (0.057,0.121,0.252) 建議補貨量 (0.016,0.031,0.064) 顧客回應
運送規劃 (0.038,0.093,0.215) 電子訂購系統 (0.070,0.148,0.313) 商品條碼 (0.151,0.308,0.626) 存貨管理
銷售點資訊系統 (0.031,0.052,0.100) 規劃補貨計畫 (0.010,0.017,0.032) 存貨控制 (0.014,0.024,0.043) 倉儲管理
通知出貨信息 (0.003,0.005,0.009) 資料來源：本研究整理
参、建立評估因素項目
依據 Nydick & Hill (1992)提出的選擇供應商的 23 個構面，如表 4.7。
表 4.7 選擇供應商的 23 個構面
品質 交期 過去績效 價格 訓練
管理與組織 管理控制 維修服務 服務態度 過去印象
技術能力 財務狀況 勞資關係 溝通系統 業界聲譽
包裝能力 商業關係 過去營業額 相互間協商 地理位置 保證與客訴政策 生產設備與產能 客訴處裡程序
資料來源：Nydick & Hill (1992)
與 Chou、Shen 與 Chang (2007)所提出的供應商評選的準則做為基礎，如表 4.8。
表 4.8 供應商評選的準則
準則 次準則
營運 生產設備與產能
回應(即時運送、發展速度、週期時間) 供應商與次供應商的技術支援
彈性(降低價格、訂購頻率、運費、數量) 地理位置
品質 品質保證系統(ISO9000)
生產品質
關係 與買方公司的相容性 商業關係維護能力 組織 供應商的顧客群
創新 EDI 能力
資料來源: Chou、Shen 與 Chang (2007)
根據表 4.7 與表 4.8，設計為問卷方式如附錄一，經由公司專家的意見，訂立了 14 項與 VMI 次要機能有相關性的供應商評估因素，其 14 項評估因素如表 4.9 所示。
表 4.9 供應商評估因素 評估因素
C1 品質
C2 交期
C3 價格
C4 生產規劃 C5 電子資訊交換能力 C6 財務管理 C7 溝通系統 C8 管理組織 C9 管理控制 C10 服務品質 C11 即時裝運 C12 地理位置 C13 快速回應 C14 相互間協商 資料來源：本研究整理
肆、決定次要機能與評估因素相關程度
將次要機能與評估因素相關程度製作成問卷方式，其問卷至於附錄二的第二部份。
本研究的問卷為整合專家的意見所填寫，給予次要機能與評估因素間一個適當的語意 值，則語意值可依據表 3.3 轉換為相對應的模糊數，其語意值符號整理如表 4.10 所示。
表 4.10 次要機能與評估因素之相關性
(0.025,0.057,0.126)⊗(0.2,0.4,0.6)⊕(0.011,0.021,0.042)⊗(0.4,0.6,0.8)⊕(0.057,0.121, 0.252)⊗(0.2,0.4,0.6)⊕(0.057,0.121,0.252)⊗(0.2,0.4,0.6)⊕(0.038,0.093,0.215)⊗(0.4,0.6,0.
8)⊕(0.014,0.024,0.043)⊗(0.4,0.6,0.8)=(0.053,0.203,0.618)
同理，可求得其餘評估因素的模糊權重，本研究將其整理如表 4.11 所示：
表 4.11 評估因素之模糊權重 C10 (0.005,0.019,0.051) C11 (0.033,0.115,0.345) C12 (0.099,0.673,0.812) C13 (0.014,0.047,0.134) C14 (0.073,0.249,0.495) 資料來源：本研究整理
電子資訊交換能力 ○ ○ ○ ○ ○ 財務管理
溝通系統 △ △ △ △ ○ ○
管理組織 ◎ ◎ ○
管理控制 ○ ○ ○
服務品質 ○ △ ◎ ○
即時裝運 ○ ◎ ◎
地理位置 ◎
快速回應 ◎
相互間協商 資料來源：本研究整理
柒、計算評估因素調整後的模糊權重
根據步驟伍、陸求得「評估因素權重」與「評估因素間相關程度」，應用公式(3.7) 可計算調整後的評估因素權重。以「品質」為例，計算調整後模糊權重。
「品質」評估因素調整後之模糊權重：
(0.053, 0.203, 0.618) 1 [(0.069, 0.237, 0.689) (0.6, 0.8,1) (0.01, 0.034, 0.101)
⊕13 ⊗ ⊕ ⊗
(0.6, 0.8, 0.1)⊕(0.06, 0.031, 0.085)⊗(0.6, 0.8,1)⊕(0.026, 0.067, 0.169)⊗(0.6, 0.8,1) (0.073, 0.249, 0.49) (0.68, 0.8,1)] (0.062, 0.241, 0.737)
⊕ ⊗ =
同理，可計算其餘的評估因素調整之後的模糊權重，本研究將其結果整理如表 4.13 所示。
表 4.13 調整後評估因素之模糊權重 評估因素 調整後模糊權重
C1 (0.062,0.241,0.737) C2 (0.141,0.461,1.314) C3 (0.076,0.294,0.889) C4 (0.024,0.115,0.357) C5 (0.166,0.491,1.332) C6 (0.013,0.055,0.193) C7 (0.061,0.2680.841)
C8 (0.027,0.112,0.386) C9 (0.039,0.131,0.413) C10 (0.024,0.121,0.384) C11 (0.048,0.202,0.609) C12 (0.11,0.726,1.013) C13 (0.038,0.173,0.489) C14 (0.094,0.36,0.811) 資料來源：本研究整理
捌、確認可做為公司的供應商
個案公司尋找到所需的六家供應商，六家供應商分別為日系廠商兩家、中東廠商一 家、美系廠商一家、歐系廠商一家、台灣廠商一家，針對這六家工程塑膠原料的供應商，
做進階的評選分析，作為最後的驗證。
玖、建立 IF-THEN 的規則
為使公司有效率的做初步刪除不適合的供應商，利用表 4.9 所示的評估因素，經過 公司專家討論，主要在供應商評選時還是較注重的評估因素有：價格、品質、交期、財 務管理、相互間協商、地理位置。
因此，應用上述的評估因素訂立規則，評估因素的程度可使用語意變數的方式，語 意變數也可轉換為相對應的模糊數如表 3.3 與表 3.4 所示，在由公司專家訂立 IF-THEN 的 19 條規則，以前 6 條規則為例，其餘規則放置於附錄四。
規則一：IF 價格是很差的，THEN 供應商強絕對刪除。
規則二：IF 價格是差的，AND 品質是差的，AND 相互間協商是很差的，
THEN 供應商刪除。
規則三：IF 價格是差的，AND 品質是很差的，AND 地理位置是差的，
THEN 供應商刪除。
規則四：IF 價格是很差的，AND 品質是差的，THEN 供應商絕對刪除。
規則五：IF 價格是很差的，AND 品質是很差的，THEN 供應商絕對刪除。
規則六：IF 價格是差的，AND 交期是差的，AND 相互間協商是很差的，THEN 供 應商刪除。
#
拾、模糊推論
整合公司專家的意見給予供應商語意評估值，其問卷至於附錄二第四部份，其評估 值如表 4.14 所示，此問卷中的語意值可轉換為如表 3.3 所相對應的三角模糊數。
表 4.14 供應商的評估值
評估因素 A1 A2 A3 A4 A5 A6
C1 很好 好 好 很好 普通 稍好 C2 很好 好 稍差 普通 稍好 普通 C3 好 稍好 差 很差 普通 很好 C4 好 差 很好 稍好 很好 普通 C5 很好 好 好 好 稍好 普通 C6 很好 好 差 差 稍好 普通 C7 好 很好 稍好 普通 普通 稍差 C8 好 稍好 好 好 很好 普通 C9 差 稍好 普通 稍好 稍差 普通 C10 好 很好 很好 普通 稍好 普通 C11 好 稍好 稍好 普通 普通 很好 C12 普通 好 差 稍差 稍差 很好 C13 普通 好 很差 很好 稍差 稍好 C14 很好 好 差 稍好 稍好 稍差 資料來源：本研究整理
接著，檢視供應商實際評估值有哪些項目與 IF-THEN 的規則相符合，找出相符合 的規則之後，應用 Mamdanai(1975)推論。以 A3供應商為例，其符合的規則有規則六、
規則十與規則十八。
規則六：
IF 價格是差 AND 交期是差 AND 相互間協商是很差 THEN 供應商刪除。
如果反模糊化所得之明確數值大於或等於門檻值則被刪除，以 A3供應商為例。
* 1 0.8 0.33 0.8 0.57 0.8 1 0.33 0.57 0.8
Z
= × + × + × = =δ+ + ，被刪除。
同理，其他供應商也是依此步驟做初步的篩選，本研究將其結果整理如表 4.15 所示。
表 4.15 供應商初步篩選 供應商 Z* 篩選結果
A1 0 保留 A2 0 保留 A3 0.8 刪除 A4 0.87 刪除 A5 0 保留 A6 0 保留 資料來源：本研究整理
拾貳、建立模糊決策矩陣
在上一步驟保留下的供應商，在表 4.14 所示的評估值轉換為三角模糊數 其轉換如 表 4.16 所示。
表 4.16 保留下的供應商評估值
評估因素 A1 A2 A5 A6
C1 (0.8,1,1) (0.7,0.85,1) (0.3,0.5,0.7) (0.5,0.65,0.8) C2 (0.8,1,1) (0.7,0.85,1) (0.5,0.65,0.8) (0.3,0.5,0.7) C3 (0.7,0.85,1) (0.5,0.65,0.8) (0.3,0.5,0.7) (0.8,1,1) C4 (0.7,0.85,1) (0,0.15,0.3) (0.8,1,1) (0.3,0.5,0.7) C5 (0.8,1,1) (0.7,0.85,1) (0.5,0.65,0.8) (0.3,0.5,0.7) C6 (0.8,1,1) (0.7,0.85,1) (0.5,0.65,0.8) (0.3,0.5,0.7) C7 (0.7,0.85,1) (0.8,1,1) (0.3,0.5,0.7) (0.2,0.35,0.5) C8 (0.7,0.85,1) (0.5,0.65,0.8) (0.8,1,1) (0.3,0.5,0.7) C9 (0,0.15,0.3) (0.5,0.65,0.8) (0.2,0.35,0.5) (0.3,0.5,0.7) C10 (0.7,0.85,1) (0.8,1,1) (0.5,0.65,0.8) (0.3,0.5,0.7) C11 (0.7,0.85,1) (0.5,0.65,0.8) (0.3,0.5,0.7) (0.8,1,1) C12 (0.3,0.5,0.7) (0.7,0.85,1) (0.2,0.35,0.5) (0.8,1,1) C13 (0.3,0.5,0.7) (0.7,0.85,1) (0.2,0.35,0.5) (0.5,0.65,0.8) C14 (0.8,1,1) (0.7,0.85,1) (0.5,0.65,0.8) (0.2,0.35,0.5)
資料來源：本研究整理
(0.8,1,1) (0.8,1,1) (0.7,0.85,1) (0.7,0.85,1) (0.8,1,1) (0.8,1,1) (0.7,0.85,1) (0.7,0.85,1) (0.7,0.85,1) (0.5,0.65,0.8) (0,0.15,0.3) (0.7,0.85,1) (0.7,0,85,1) (0.8,1,1) (0.3,0.5,0.7) (0.5,0.65,0.8) (0.3,0.5,0.7) (0.8,1,1) (0.5,0.65,0.8) (0.5,0.65,0.8) (0.3,0.5,0.7) (0.5,0.65,0.8) (0.3,0.5,0.7) (0.8,1,1) (0.3,0.5,0.7) (0.3,0.5,0.7) (0.3,0.5,0.7) (0.2,0.35,0.5)
⎡⎢
(0.7,0.85,1) (0,0.15,0.3) (0.7,0.85,1) (0.7,0.85,1) (0.3,0.5,0.7) (0.3,0.5,0.7) (0.8,1,1) (0.5,0.65,0.8) (0.5,0.65,0.8) (0.8,1,1) (0.5,0.65,0.8) (0.7,0.85,1) (0.7,0.85,1) (0.7,0.85,1)
(0.8,1,1) (0.2,0.35,0.5) (0.5,0.65,0.8) (0.3,0.5,0.7) (0.2,0.35,0.5) (0.2,0.35,0.5) (0.5,0.65,0.8) (0.3,0.5,0.7) (0.3,0.5,0.7) (0.3,0.5,0.7) (0.8,1,1) (0.8,1,1) (0.5,0.65,0.8) (0.2,0.35,0.5)
⎤⎥
1 2 3 4 5 6 7
(0,0,0.2) (0,0,0.2) (0,0.15,0.3) (0,0.15,0.3) (0,0,0.2) (0,0,0.2) (0,0.15,0.3) (0,0.15,0.3) (0,0.15,0.3) (0.2,0.35,0.5) (0.7,0.85,1) (0,0.15,0.3) (0,0.15,0.3) (0,0,0.2) (0.3,0.5,0.7) (0.2,0.35,0.5) (0.3,0.5,0.7) (0,0,0.2) (0.2,0.35,0.5) (0.2,0.35,0.5) (0.3,0.5,0.7) (0.2,0.35,0.5) (0.3,0.5,0.7) (0,0,0.2) (0.3,0.5,0.7) (0.3,0.5,0.7) (0.3,0.5,0.7) (0.5,0.65,0.8)
⎡⎢
⎢⎢
⎢⎣
8 9 1 0 1 1 1 2 1 3 1 4
C C C C C C C
(0,0.15,0.3) (0.7,0.85,1) (0,0.15,0.3) (0,0.15,0.3) (0.3,0.5,0.7) (0.3,0.5,0.7) (0,0,0.2) (0.2,0.35,0.5) (0.2,0.35,0.5) (0,0,0.2) (0.2,0.35,0.5) (0,0.15,0.3) (0,0.15,0.3) (0,0.15,0.3)
(0,0,0.2) (0.5,0.65,0.8) (0.2,0.35,0.5) (0.3,0.5,0.7) (0.5,0.65,0.8) (0.5,0.65,0.8) (0.2,0.35,0.5) (0.3,0.5,0.7) (0.3,0.5,0.7) (0.3,0.5,0.7) (0,0,0.2) (0,0,0.2) (0.2,0.35,05) (0.5,0.65,0.8)
⎤⎥
(0.000,0.000,0.147) (0.000,0.000,0.263) (0.000,0.044,0.267) (0.000,0.017,0.107) (0.000,0.000,0.266) (0.000,0.000,0.039) (0.000,0.040,0.252) (0.000,0.036,0.221) (0.000,0.069,0.394) (0.015,0.103,0.444) (0.017,0.098,0.357) (0.000,0.074,0.400) (0.000,0.008,0.058) (0.000,0.000,0.168) (0.019,0.120,0.516) (0.028,0.161,0.657) (0.023,0.147,0.622) (0.000,0.000,0.071) (0.033,0.172,0.666) (0.003,0.019,0.096) (0.018,0.134,0.588) (0.012,0.084,0.368) (0.042,0.231,0.920) (0.000,0.000,0.178) (0.007,0.058,0.250) (0.050,0.245,0.932) (0.004,0.027,0.135) (0.030,0.174,0.672)
⎡⎢
⎢⎢
⎢⎣
8 9 1 0 1 1 1 2 1 3 1 4
C C C C C C C
(0.000,0.017,0.116) (0.027,0.111,0.413) (0.000,0.018,0.115) (0.000,0.030,0.183) (0.033,0.363,0.709) (0.011,0.087,0.342) (0.000,0.000,0.162) (0.005,0.039,0.193) (0.008,0.046,0.207) (0.000,0.000,0.077) (0.010,0.071,0.305) (0.000,0.109,0.304) (0.000,0.026,0.147) (0.000,0.054,0.243) (0.000,0.000,0.077) (0.020,0.085,0.331) (0.005,0.042,0.192) (0.014,0.101,0.426) (0.055,0.472,0.810) (0.019,0.113,0.391) (0.019,0.126,0.406) (0.008,0.056,0.270) (0.012,0.065,0.289) (0.007,0.061,0.269) (0.000,0.000,0.122) (0.000,0.000,0.203) (0.008,0.061,0.244) (0.047,0.234,0.649)
⎤⎥
⎥⎥
⎥⎦
拾伍、建立權重排名矩陣
C7 3 4 2 1
1 s t 2 n d 3 r d 4 t h
(0.019,0.120,0.516) (0.012,0.084,0.368) (0.000,0.036,0.221) (0.000,0.000,0.147) (0.042,0.231,0.920) (0.028,0.161,0.657) (0.000,0.069,0.394) (0.000,0.000,0.263) (0.023,0.147,0.622) (0.015,0.103,0.444) (0.000,0.044,0.267) (0.000,0.000,0.178) (0.017,0.098,0.357) (0.007,0.058,0.250) (0.000,0.017,0.107) (0.000,0.000,0.071) (0.050,0.245,0.932) (0.033,0.172,0.666) (0.000,0.074,0.400) (0.000,0.000,0.266) (0.004,0.027,0.135) (0.003,0.019,0.096) (0.000,0.008,0.058) (0.000,0.000,0.039) (0.030,0.174,0.672) (0.018,0.134,0.588) (0.000,0.040,0.252) (0.000,0.000,0.168) (0.008,0.056,0.270) (0.005,0.039,0.193) (0.000,0.017,0.116) (0.000,0.000,0.077) (0.027,0.111,0.413) (0.020,0.085,0.331) (0.012,0.065,0.289) (0.008,0.046,0.413) (0.007,0.061,0.269) (0.005,0.042,0.192) (0.000,0.018,0.115) (0.000,0.000,0.077) (0.014,0.101,0.426) (0.010,0.071,0.305) (0.000,0.030,0.183) (0.000,0.000,0.122) (0.055,0.472,0.810) (0.033,0.363,0.709) (0.000,0.109,0.304) (0.000,0.000,0.203) (0.019,0.113,0.391) (0.011,0.087,0.342) (0.008,0.061,0.244) (0.000,0.026,0.147) (0.047,0.234,0.649) (0.019,0.126,0.406) (0.000,0.054,0.243) (0.000,0.000,0.162)
⎡ ⎤ (0.044, 0.450,1.051)=
同理，可以計算出各供應商整合權重，本研究將之整理如下：
1
s t
2n d
3r d
4t h
(0.027,0.111,0.413) (0.044,0.450,1.051) (0.000,0.167,1.040) (0.000,0.000,0.877) (0.017,0.098,0.357) (0.030,0.213,0.942) (0.012,0.416,1.909) (0.000,0.026,0.391) (0.130,0.953, 2.765) (0.125,0.740, 2.936) (0.000,0.000,0.000) (0.000,0.000,0.149) (0.189,1.028,3.848) (0.019,0.142,0.618) (0.008,0.061,0.244) (0.008,0.046,0.915)
⎡ ⎤
(0.027,0.111,0.413) (0.044,0.450,1.051) (0,0.167,1.040) (0,0,0.877)
(0.017,0.098,0.357) (0.03,0.213,0.942) (0.012,0.416,1.909) (0,0.026,0.391) (0.130,0.953,2.765) (0.125,
0.74,2.936) (0,0,0) (0,0,0.149)
(0.189,1.028,3.848) (0.019,0.142,0.618) (0.008,0.061,0.244) (0.008,0.046,0.915)
t t t
本研究採用 Verdegay(1983)所提出的方法，將原本三角模糊數轉變為一區間，以 A1
的 1st 為例，其轉換方式如下：
從定義中可知道 k
11( ) 1
u
ADx
≥ − ，藉由此定義可做轉換為區間，其過程如下： α 0.0270.111 0.027 1
0.027 (1 )(0.111 0.027) 0.111 0.084 0.413 0.111 1
0.413 (1 )(0.413 0.111) 0.111 0.303
1st 2nd 3rd 4th