Power BI 的供應商品質分析範例:導覽Supplier Quality Analysis sample for Power BI: Take a tour

供應商品質分析範例的簡要概觀A brief overview of the Supplier Quality Analysis sample

這個產業範例的儀表板和基礎報表,著重在傳統供應鏈的其中一項挑戰 — 供應商品質的分析。This industry sample dashboard and underlying report focus on one of the typical supply chain challenges — supplier quality analysis. 有兩個主要的計量會在此分析中發揮作用:缺失總數和缺失所造成的停工期總計。Two primary metrics are at play in this analysis: total number of defects and the total downtime that these defects caused. 此範例有兩個主要目標:This sample has two main objectives:

  • 了解就品質而言,哪家供應商最好,而哪家供應商最差Understand who the best and worst suppliers are, with respect to quality
  • 找出哪些工廠在找出及淘汰瑕疵品的工作表現較佳,以縮短停工時間Identify which plants do a better job finding and rejecting defects, to minimize downtime

此範例是系列中的一部分,該系列說明您可如何使用 Power BI 的商業導向資料、報表及儀表板。This sample is part of a series that illustrates how you can use Power BI with business-oriented data, reports, and dashboards. 此為來自 obviEnce 的匿名真實資料 (www.obvience.com)。This is real data from obviEnce (www.obvience.com) that has been anonymized.

先決條件Prerequisites

您必須先將範例下載為內容套件、.pbix 檔案或 Excel 活頁簿,才能使用範例。Before you can use the sample, you must first download it as a content pack, .pbix file, or Excel workbook.

取得此範例的內容套件Get the content pack for this sample

  1. 開啟 Power BI 服務 (app.powerbi.com) 並登入。Open the Power BI service (app.powerbi.com) and log in.
  2. 在左下角選取 [取得資料]。In the bottom left corner select Get data.

  3. 在顯示的 [取得資料] 頁面上,選取 [範例]。On the Get Data page that appears, select the Samples icon.

  4. 選取 [供應商品質分析範例],然後選擇 [連線]。Select the Supplier Quality Analysis Sample, then choose Connect.

    供應商品質分析範例

  5. Power BI 會匯入內容套件,並將新的儀表板、報表及資料集新增到您目前的工作區。Power BI imports the content pack and adds a new dashboard, report, and dataset to your current workspace. 新的內容會以黃色星號標示。The new content is marked with a yellow asterisk.

    星號

取得此範例的 .pbix 檔案Get the .pbix file for this sample

或者,您可以下載此範例為 .pbix 檔案,其設計目的是要用於 Power BI Desktop。Alternatively, you can download the sample as a .pbix file, which is designed for use with Power BI Desktop.

取得此範例的 Excel 活頁簿Get the Excel workbook for this sample

您也可以只下載此範例的資料集 (Excel 活頁簿)You can also download just the dataset (Excel workbook) for this sample. 活頁簿包含的 Power View 工作表可供您檢視及修改。The workbook contains Power View sheets that you can view and modify. 若要查看未經處理的資料,請選取 [Power Pivot] > [管理]。To see the raw data select Power Pivot > Manage.

用料瑕疵所造成的停工時間Downtime caused by defective materials

讓我們來分析用料瑕疵所造成的停工時間並查看應由哪些廠商負責。Let’s analyze the downtime caused by defective materials and see which vendors are responsible.

  1. 在儀表板中,選取 [瑕疵品總數] 數字圖格或 [停工時間總分鐘數] 數字圖格。On the dashboard, select the Total Defect Quantity number tile or the Total Downtime Minutes number tile.

    [供應商品質分析範例] 報表即會開啟 [停工時間分析] 頁面。The “Supplier Quality Analysis Sample” report opens to the “Downtime Analysis” page. 請注意我們有 3300 萬個瑕疵品,而這些瑕疵品所造成的停工時間為 77000 分鐘。Notice we have 33M total defective pieces, and the total downtime caused by these defective pieces is 77K minutes. 雖然有些用料的瑕疵品較少,但因為它們會導致嚴重延誤,亦導致停工時間更長。Some materials have fewer defective pieces but they can cause a huge delay resulting in larger downtime. 讓我們在報表頁面上瀏覽這些項目。Let’s explore them on the report page.

  2. 查看 [依用料類型的瑕疵品和停工時間 (分鐘)] 組合圖中的 [停工時間總分鐘數] 一行,我們發現瓦楞紙用料會導致最多的停工時間。Looking at the Total Downtime Minutes line in the Defects and Downtime (min) by Material Type combo chart, we see corrugate materials cause the most downtime.
  3. 選取相同組合圖中的 [瓦楞紙] 資料行,以查看哪些工廠受此瑕疵的影響最大,以及哪些廠商應負責。Select the Corrugate column in the same combo chart to see which plants are impacted most by this defect and which vendor is responsible.

  4. 選取地圖中的個別工廠,以查看哪家廠商或用料該為這家工廠的停工時間負責。Select individual plants in the map to see which vendor or material is responsible for the downtime at that plant.

哪家是最差的供應商?Which are the worst suppliers?

我們想要找出最差的八家供應商,並決定他們的停工時間百分比責任歸屬。We want to find the worst eight suppliers and determine what percentage of the downtime they are responsible for creating. 我們可以將 [依廠商的停工時間 (分鐘)] 區域圖變更為樹狀圖,以進行這項作業。We can do this by changing the Downtime (min) by Vendor area chart to a treemap.

  1. 在報表的第 3 頁 [停工時間分析] 中,選取左上角的 [編輯報表] 。On page 3 of the report, “Downtime Analysis,” select Edit Report in the upper-left corner.
  2. 選取 [依廠商的停工時間 (分鐘)] 區域圖,並在 [視覺效果] 窗格中選取 [樹狀圖]。Select the Downtime (min) by Vendor area chart, and in the Visualizations pane select Treemap.

    樹狀圖會自動將 [廠商] 欄位做為 [群組] 。The treemap automatically puts the Vendor field as the Group.

    從此樹狀圖中,我們可以看到前八個廠商是樹狀圖左側的八個區塊。From this tree map, we can see the top eight vendors are the eight blocks on the left of the tree map. 我們也可以發現它們應為約 50% 的停工時間總分鐘數承擔責任。We can also see they account for about 50% of all downtime minutes.

  3. 選取導覽列頂端的 [供應商品質分析範例],返回儀表板。Select Supplier Quality Analysis Sample in the top navigation bar to go back to the dashboard.

比較工廠Comparing plants

現在讓我們來探索哪些工廠有妥善管理瑕疵用料,以確保較短的停工時間。Now let’s explore which plant does a better job managing defective material, resulting in less downtime.

  1. 選取 [依工廠、瑕疵品類型的總瑕疵報表] 地圖底圖。Select the Total Defect Reports by Plant, Defect Type map tile.

    報表即會開啟 [供應商品質] 分頁。The report opens to the “Supplier Quality” page.

  2. 在地圖圖例中,選取 [影響] 圓形。In the map legend, select the Impact circle.

    請注意,泡泡圖中的 [物流] 是最糟糕的類別目錄 – 它在瑕疵品總量、總瑕疵報表和停工時間總分鐘數都居最高位置。Notice in the bubble chart that Logistics is the most troubled category – it’s the largest in terms of total defect quantity, total defect reports, and total downtime minutes. 讓我們來進一步瀏覽此類別目錄。Let’s explore this category more.

  3. 在泡泡圖中選取 [物流] 泡泡,並觀察伊利諾州春田市和內珀維爾市的工廠。Select the Logistics bubble in the bubble chart and observe the plants in Springfield, IL and Naperville, IL. 內珀維爾市似乎在管理瑕疵供貨方面做得更好,因為它的退貨量較高,影響量也較小,而春田市的影響量就較大。Naperville seems to be doing a much better job of managing defective supplies as it has a high number of rejects and few impacts, compared to Springfield’s large number for impacts.

  4. 選取導覽列頂端的 [供應商品質分析範例],返回您的使用中工作區。Select Supplier Quality Analysis Sample in the top navigation bar to return to your active workspace.

哪種類型的用料管理最佳?Which material type is best managed?

管理最佳的用料類型是指不論瑕疵品數量為何,皆具有最低的停工時間或不造成任何影響的類型。The best managed material type is the one with lowest downtime or no impact, regardless of defect quantity.

  • 在儀表板上,查看 [依物料類型的瑕疵品總數、瑕疵類型] 磚。In the dashboard, look at the Total Defect Quantity by Material Type, Defect Type tile.

請注意 [原料] 的瑕疵品總數很多,但大多數的瑕疵品都會被退貨或不具影響。Notice that Raw Materials have a lot of total defects, but most of the defects are either rejected or have no impact.

讓我們確認儘管瑕疵品數量高,原料仍不會造成大量的停工時間。Let’s verify that raw materials don’t cause a lot of downtime, despite high defect quantity.

  • 在儀表板上,查看 [依物料類型的瑕疵品總數、停工時間總分鐘數] 圖格。In the dashboard, look at the Total Defect Qty, Total Downtime Minutes by Material Type tile.

很顯然,原料受到妥善管理:它們的瑕疵品雖然更多,但停工時間總分鐘數較低。Apparently raw materials are well managed: they have more defects, but lower total downtime minutes.

依年度比較瑕疵品與停工時間的關係Compare defects to downtime by year

  1. 選取 [依工廠、瑕疵品類型的總瑕疵報表] 地圖底圖,將報表開啟至第一個報表分頁 [供應商品質]。Select the Total Defect Reports by Plant, Defect Type map tile to open the report to the first report page, Supplier Quality.
  2. 請注意,2014 年的 [瑕疵品數量] 比 2013 年高。Notice that Defect Qty is higher in 2014 than in 2013.

  3. 瑕疵品多代表停工時間一定也更多嗎?Do more defects translate into more downtime? 我們可以在問與答方塊提問以找出答案。We can ask questions in the Q&A box to find out.
  4. 選取導覽列頂端的 [供應商品質分析範例],返回儀表板。Select Supplier Quality Analysis Sample in the top navigation bar to go back to the dashboard.
  5. 既然我們知道 [原料] 具有最高數量的瑕疵品,可在問題方塊中輸入:顯示物料類型、年份和瑕疵品總數。Since we know Raw Materials have the highest number of defects, in the question box, type “show material types, year and total defect qty”.

    2014 年的原料瑕疵品數量比 2013 年高很多。There were many more raw materials defects in 2014 than in 2013.

  6. 現在,將問題變更為:顯示物料類型、年份和停工時間總分鐘數。Now change the question to “show material types, year and total downtime minutes”.

雖然 2014 年的原料瑕疵品更多,但 2013 年和 2014 年的原料停工時間差不多。Raw materials downtime was about the same in 2013 and 2014, even though there were many more raw materials defects in 2014.

因此,即使 2014 年原料瑕疵品較多,也不會導致 2014 年的原料停工時間更長。It turns out more raw materials defects in 2014 didn’t lead to much more raw materials downtime in 2014.

依月份比較瑕疵品與停工時間的關係Compare defects to downtime month to month

讓我們看看另一個與瑕疵品總數相關的儀表板圖格。Let’s look at another dashboard tile related to total defective quantity.

  1. 選取問題方塊上方左上角的 [上一頁] 箭頭 ,回到儀表板。Select the back arrow in the upper-left corner above the question box to get back to the dashboard.

    進一步查看 [依月份、年度的瑕疵品總數] 圖格,可發現 2014 年上半年的瑕疵品數與 2013 年非常接近,但 2014 年下半年瑕疵品數大幅激增。Looking more closely at the Total Defect Quantity by Month, Year tile shows that the first half of 2014 had a similar number of defects as 2013, but in the second half of 2014, the number of defects jumped significantly.

    我們來看看瑕疵品數的增加是否會導致停工時間分鐘數也跟著增加。Let’s see if this increase in defect quantity led to an equal increase in downtime minutes.

  2. 在問題方塊中輸入:依月份和年份的停工時間總分鐘數折線圖。In the question box, type “total downtime minutes by month and year as a line chart”.

    在 6 月和 10 月間,我們發現停工時間分鐘數大增,但除此之外,瑕疵品數並沒有明顯導致更長的停工時間。We do see a jump in downtime minutes during June and Oct, but other than that, the jump in the number of defects didn’t result in significantly more downtime. 這意謂著我們管理瑕疵品的成效很好。This shows we’re managing defects well.

  3. 若要將這個圖表釘選至儀表板,請選取問題方塊右側的釘選圖示 To pin this chart to your dashboard, select the pin icon to the right of the question box.
  4. 若要瀏覽極端值月份,可提出問題:10 月工廠的停工時間總分鐘數,以依物料類型、工廠地點、類別目錄等查看 10 月的停工時間分鐘數。To explore the outlier months, check out the downtime minutes during Oct by material type, plant location, category, etc. by asking questions such as "total downtime minutes in October by plant".
  5. 選取問題方塊上方左上角的 [上一頁] 箭頭 ,回到儀表板。Select the back arrow in the upper-left corner above the question box to get back to the dashboard.

這是安全的作業環境。This is a safe environment to play in. 您一律可以選擇不儲存變更。You can always choose not to save your changes. 但如果儲存了變更,您也可以隨時移至 [取得資料] ,重新複製此範例。But if you do save them, you can always go to Get Data for a new copy of this sample.

下一步:連接到您的資料Next steps: Connect to your data

我們希望本教學已示範 Power BI 儀表板、問與答和報表如何讓您深入了解供應商品質的資料。We hope this tour has shown how Power BI dashboards, Q&A, and reports can provide insights into supplier quality data. 現在輪到您了 — 連接到您自己的資料。Now it’s your turn — connect to your own data. 您可以透過 Power BI 連接到各式各樣的資料來源。With Power BI you can connect to a wide variety of data sources. 深入了解開始使用 Power BI.Learn more about getting started with Power BI.