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

這個產業範例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:瑕疵總數和瑕疵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.
  • 指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.

[供應商品質分析範例] 儀表板

此範例是系列中的一部分,說明您可如何使用 Power BI 的商業導向資料、報表與儀表板。This sample is part of a series that shows how you can use Power BI with business-oriented data, reports, and dashboards. 它是由 obviEnce 使用真實資料 (已匿名化) 所建立。It was created by obviEnce with real data, which has been anonymized. 資料會以數種格式提供:內容套件、.pbix Power BI Desktop 檔案,或 Excel 活頁簿。The data is available in several formats: content pack, .pbix Power BI Desktop file, or Excel workbook. 請參閱 Power BI 範例See Samples for Power BI.

此教學課程探索 Power BI 服務中的供應商品質分析範例內容套件。This tutorial explores the Supplier Quality Analysis sample content pack in the Power BI service. 因為 Power BI Desktop 和服務中報表的使用體驗皆非常類似,因此您也可以在 Power BI Desktop 中使用範例 .pbix 檔案來進行教學課程。Because the report experience is similar in Power BI Desktop and in the service, you can also follow along by using the sample .pbix file in Power BI Desktop.

您不需要 Power BI 授權,即可在 Power BI Desktop 中瀏覽範例。You don't need a Power BI license to explore the samples in Power BI Desktop. 如果您沒有 Power BI Pro 授權,則可以將範例儲存到 Power BI 服務中的 [我的工作區]。If you don't have a Power BI Pro license, you can save the sample to your My Workspace in the Power BI service.

取得範例Get the sample

您必須先將範例下載為內容套件.pbix 檔案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,然後開啟您要儲存範例的工作區。Open the Power BI service (app.powerbi.com), sign in, and open the workspace where you want to save the sample.

    如果您沒有 Power BI Pro 授權,則可以將範例儲存到 [我的工作區]。If you don't have a Power BI Pro license, you can save the sample to your My Workspace.

  2. 在左下角選取 [取得資料] 。In the bottom-left corner, select Get Data.

    選取 [取得資料]

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

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

    連線至範例

  5. Power BI 會匯入內容套件,然後將新儀表板、報表和資料集新增至您目前的工作區。Power BI imports the content pack and then adds a new dashboard, report, and dataset to your current workspace.

    供應商品質分析範例項目

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

或者,您可以將供應商品質分析範例下載為 .pbix 檔案,其設計目的是要用於 Power BI Desktop。Alternatively, you can download the Supplier Quality Analysis 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

如果您想要檢視此範例的資料來源,其也有可用的 Excel 活頁簿 格式。If you want to view the data source for this sample, it's also available as an Excel workbook. 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. 若要查看未經處理資料,請啟用「資料分析」增益集,然後選取 [Power Pivot] > [管理] 。To see the raw data, enable the Data Analysis add-ins, and then select Power Pivot > Manage. 若要啟用 Power View 和 Power Pivot 增益集,請參閱從 Excel 本身檢視 Excel 範例以了解詳情。To enable the Power View and Power Pivot add-ins, see Take a look at the Excel samples from inside Excel itself for details.

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] 或 [停工時間總分鐘數] 磚。On the dashboard, select the Total Defect Quantity or the Total Downtime Minutes tile.

    選取磚以開啟報表

    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 3,300 萬個瑕疵品,總共造成 77,000 分鐘的停工時間。Notice we have 33 million defective pieces, causing a total downtime of 77,000 minutes. 雖然有些物料的瑕疵品較少,但因為它們會造成延誤而導致更長的停工時間。Although some materials have fewer defective pieces, they can cause delays, which result in more 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. 如果查看 [依物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,我們會發現瓦楞紙物料會導致最長的停工時間。If we look at the Total Downtime Minutes line in the Defects and Downtime (min) by Material Type combo chart, we can see that corrugate materials cause the most downtime.

  3. 選取 [瓦楞紙] 資料行,以查看哪些工廠受此瑕疵品的影響最大,以及哪些廠商應負責。Select the Corrugate column to see which plants are affected most by this defect and which vendor is responsible.

    選取 [瓦楞紙] 資料行

  4. 在 [依工廠的停工時間 (分鐘)] 地圖中,依序選取個別工廠,以查看哪家廠商或物料該為這家工廠的停工時間負責。In the Downtime (min) by Plant map, select individual plants in turn 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're responsible for creating. 我們可以將 [依廠商的停工時間 (分鐘)] 區域圖變更為矩形式樹狀結構圖,以進行這項作業。We can do so by changing the Downtime (min) by Vendor area chart to a treemap.

  1. 在報表的 [停工時間分析] 頁面中,選取左上角的 [編輯報表] 。On the Downtime Analysis page of the report, 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] 窗格中選取矩形式樹狀結構圖圖示。Select the Downtime (min) by Vendor area chart, and in the Visualizations pane, select the Treemap icon.

    選取矩形式樹狀結構圖圖示

    矩形式樹狀結構圖會自動將 [廠商] 欄位設定為 [群組] 。The treemap automatically sets the Vendor field as the Group.

    依廠商的停工時間 (分鐘) 矩形式樹狀結構圖

    從此矩形式樹狀結構圖中,我們可以看到前八個廠商是矩形式樹狀結構圖左側的八個區塊。From this treemap, we can see the top eight vendors are the eight blocks on the left of the treemap. 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. 選取頂端導覽窗格的 [供應商品質分析範例] ,以返回儀表板。Select Supplier Quality Analysis Sample in the top nav pane to return 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. 在儀表板中,選取 [依工廠、瑕疵品類型的總瑕疵報表] 地圖磚。On the dashboard, select the Total Defect Reports by Plant, Defect Type map tile.

    [依工廠、瑕疵類型的總瑕疵報表] 磚

    報表會隨即開啟 [供應商品質分析] 頁面。The report opens to the Supplier Quality Analysis page.

  2. 在 [依工廠和瑕疵品類型的總瑕疵報表] 的圖例中,選取 [影響] 圓形。In the legend of the Total Defect Reports by Plant and Defect Type, select the Impact circle.

    選取 [影響]

    請注意,泡泡圖中的 [物流] 是最糟糕的類別。Notice in the bubble chart that Logistics is the most troublesome category. 它在瑕疵品總數、瑕疵報表和停工時間分鐘數都位居最高位置。It’s the largest in terms of total defect quantity, defect reports, and 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 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.

    選取 [物流]

  4. 選取頂端導覽窗格的 [供應商品質分析範例] ,以返回儀表板。Select Supplier Quality Analysis Sample in the top nav pane to return to the dashboard.

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.

  1. 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.

    [依物料類型、瑕疵品類型的瑕疵品總數] 磚

    請注意,雖然 [原料] 物料類型的瑕疵品總數很多,但大多數的瑕疵品都會被退回或不具影響。Notice that although Raw Materials material type has many total defects, most of those defects are either rejected or have no impact.

    讓我們確認儘管瑕疵品數量高,此物料類型仍不會造成大量的停工時間。Let’s verify that this material type doesn't cause much downtime, despite high defect quantity.

  2. 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.

    [依物料類型的瑕疵品總數、停工時間總分鐘數] 磚

    原料似乎經妥善管理;雖然它們有更多的瑕疵品,但停工時間總分鐘數卻較低。Raw materials appear to be well managed; although they have more defects, they have 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] 地圖磚,報表會隨即開啟 [供應商品質分析] 頁面。Select the Total Defect Reports by Plant, Defect Type map tile to open the report to the Supplier Quality Analysis page.

  2. 在 [依月份和年度的瑕疵品總數] 圖表中,注意 2014 年的瑕疵品數量比 2013 年高。In the Total Defect Qty by Month and Year chart, notice that defect quantity is higher in 2014 than in 2013.

    [依月份和年度的瑕疵品總數] 圖表

  3. 瑕疵品多代表停工時間一定也更多嗎?Do more defects translate into more downtime? 在問與答方塊提問以找出答案。Ask questions in the Q&A box to find out.

  4. 選取頂端導覽窗格的 [供應商品質分析範例] ,以返回儀表板。Select Supplier Quality Analysis Sample in the top nav pane to return to the dashboard.

  5. 由於我們知道原料具有最高數量的瑕疵品,可在問題方塊中鍵入:show material types, year, and total defect qty (顯示物料類型、年度和瑕疵品總數)。Because we know that raw materials have the highest number of defects, type in the question box: 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.

    問與答的問題:顯示物料類型、年度和瑕疵品總數

  6. 接下來,將問題變更為:「顯示物料類型、年度和停工時間總分鐘數」Next, change the question to: show material types, year, and total downtime minutes.

    問與答的問題:顯示物料類型、年度和停工時間總分鐘數

    請注意,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。Notice that downtime for raw materials was about the same in 2013 and 2014, even though there were many more raw materials defects in 2014. 2014 年原料瑕疵品較多,似乎不會導致 2014 年的原料停工時間更長。It appears that more defects for raw materials in 2014 didn’t lead to much more downtime for raw materials 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. 選取左上角的 [結束問與答] 並返回儀表板。Select Exit Q&A in the upper-left corner to return to the dashboard.

    仔細查看 [依月份、年度的瑕疵品總數] 磚。Look more closely at the Total Defect Quantity by Month, Year tile. 其中顯示 2014 年上半年的瑕疵品數量與 2013 年非常接近,但 2014 年下半年的瑕疵品數量則大幅增加。It 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 increased significantly.

    [依月份、年度的瑕疵品總數] 磚

    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,鍵入「依月份和年度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.

    問與答的問題:依月份和年度的停工時間總分鐘數折線圖

    除了停工時間分鐘數在 6 月和 10 月大幅增加之外,瑕疵品數量並未明顯導致更長的停工時間。Other than a jump in downtime minutes during June and October, the number of defects didn’t result in significantly more downtime. 此結果意謂著我們將瑕疵品管理的很好。This result shows we’re managing defects well.

  3. 若要將此圖表釘選至儀表板,請選取問題方塊上方的釘選圖示To pin this chart to your dashboard, select the pin icon 釘選圖示 above the question box.

  4. 若要探索極端值月份,可提出「10 月工廠的停工時間總分鐘數」 等問題,以依物料類型、工廠地點、類別等查看 10 月的停工時間分鐘數。To explore the outlier months, check out the downtime minutes during October by material type, plant location, category, and so on, by asking questions such as total downtime minutes in October by plant.

  5. 選取左上角的 [結束問與答] 並返回儀表板。Select Exit Q&A in the upper-left corner to return to the dashboard.

後續步驟:連線到您的資料Next steps: Connect to your data

您可以在此環境盡情嘗試,因為您可以選擇不儲存您的變更。This environment is a safe one to play in, because you can choose not to save your changes. 但如果儲存了變更,您也可以隨時選取 [取得資料] 以取得此範例的新複本。But if you do save them, you can always select Get Data for a new copy of this sample.

希望此教學已讓您了解 Power BI 儀表板、問與答和報表能夠如何提供範例資料的見解。We hope this tour has shown how Power BI dashboards, Q&A, and reports can provide insights into sample data. 現在輪到您了,請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. 若要深入了解,請參閱開始使用 Power BI 服務To learn more, see Get started with the Power BI service.