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Production Gap
Can anyone help with the following - I want to measure the time difference between the LASTBOOKDATE and FIRSTBOOKDATE from one Works Order to the next (ie Production Gaps) on each Production...
The last two references need to be FirstBookDate.
MAXX = CALCULATE( MAXX(Table1,Table1[LASTBOOKDATE]), FILTER( ALL(Table1), Table1[PRODUCTION_LINE] = EARLIER(Table1[PRODUCTION_LINE]) && Table1[FIRSTBOOKDATE]< EARLIER(Table1[FIRSTBOOKDATE])))
Sorry - it would have helped if my SQL were correct - there should only be one line per Works Order
For consecutive orders (by FIRSTBOOKDATE) on the same production line I want the gap between last order finishing and this order starting
So in this case - 30/12/16 19:36 - 30/12/16 19:09 ie production gap of 27 minutes on L2
Hi andrewhann
This seems very much doable using a measure.
Please post sample data in a table format so i can copy it and write and test the measure.
Else you can share the file
Please find attached sample data
WORDNO_PPS PRODUCT_CODE PRODUCTION_LINE FIRSTBOOKDATE LASTBOOKDATE 706915 412985 M2 02/05/2017 13:47 02/05/2017 13:49 706917 412985 M2 02/05/2017 14:47 02/05/2017 15:05 708986 346490 L7 06/05/2017 00:27 06/05/2017 01:31 708987 346490 L7 06/05/2017 08:16 06/05/2017 08:18 709038 471838 L6 05/05/2017 11:42 09/05/2017 13:11 709337 392870 M3 02/05/2017 15:20 02/05/2017 18:18 709338 392870 M3 02/05/2017 19:17 02/05/2017 22:36 709342 392870 M3 06/05/2017 13:02 06/05/2017 13:45 709347 427140 L7 04/05/2017 04:42 04/05/2017 04:46 709720 193239 L2 05/05/2017 11:03 05/05/2017 13:14 709721 193239 L2 05/05/2017 10:43 05/05/2017 10:56 709722 193239 L2 05/05/2017 12:32 05/05/2017 14:32 709723 193239 L2 05/05/2017 14:46 05/05/2017 15:32 709851 392870 M3 02/05/2017 11:17 02/05/2017 15:06 709852 392870 M3 02/05/2017 22:49 02/05/2017 23:42 709853 392870 M3 01/05/2017 22:36 01/05/2017 23:19 709854 392870 M3 02/05/2017 07:53 02/05/2017 07:55 709867 211100 T30 03/05/2017 06:24 03/05/2017 06:27 709868 211100 T30 03/05/2017 12:22 03/05/2017 13:08 709869 211100 T30 03/05/2017 17:00 03/05/2017 18:14 709890 346340 L8 02/05/2017 01:44 02/05/2017 05:24 709893 347320 L4 05/05/2017 09:58 05/05/2017 10:43 709905 471322 T30 04/05/2017 01:26 04/05/2017 01:42 709906 471322 T30 04/05/2017 05:45 04/05/2017 07:09 709907 471322 T30 04/05/2017 11:06 04/05/2017 12:47 709912 471800 T30 02/05/2017 12:13 02/05/2017 14:02 709913 471800 T30 02/05/2017 19:07 02/05/2017 19:51 709919 471808 L6 02/05/2017 15:08 02/05/2017 16:30 709927 471808 L6 04/05/2017 16:34 04/05/2017 19:50 709940 473000 L7 02/05/2017 05:17 02/05/2017 10:47 709941 473000 L7 02/05/2017 12:24 02/05/2017 18:09 710020 194300 L2 06/05/2017 10:35 06/05/2017 10:37 710024 197460 L2 06/05/2017 11:27 06/05/2017 11:46 710026 218900 L2 05/05/2017 17:33 05/05/2017 18:18 710027 218900 L2 05/05/2017 18:36 05/05/2017 19:22 710029 297580 M2 05/05/2017 00:19 05/05/2017 01:47 710030 297580 M2 05/05/2017 01:49 05/05/2017 02:41 710057 382730 L1 03/05/2017 07:55 03/05/2017 08:38 710058 382730 L1 03/05/2017 10:28 03/05/2017 10:54 710059 382730 L1 03/05/2017 11:15 03/05/2017 11:51 710060 382730 L1 03/05/2017 13:28 03/05/2017 14:27 710063 391020 L1 03/05/2017 21:26 03/05/2017 21:27 710064 391020 L1 04/05/2017 07:56 04/05/2017 08:14 710065 391020 L1 03/05/2017 19:23 03/05/2017 19:24 710066 391020 L1 03/05/2017 15:56 03/05/2017 15:58 710067 391020 L1 03/05/2017 18:22 03/05/2017 18:24 710068 391020 L1 04/05/2017 00:06 04/05/2017 00:51 710069 391020 L1 04/05/2017 02:05 04/05/2017 02:25 710070 391020 L1 04/05/2017 05:08 04/05/2017 05:48 710071 391020 L1 03/05/2017 23:06 03/05/2017 23:48