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Na 20. februar 2026. 17:48:01 UTC, Dermot Kerr:

Updated description of Manufacturing Operations Dataset from
# **Manufacturing Operations Dataset Documentation** ## **Overview** This package contains anonymised manufacturing operations datasets extracted from an MES (Manufacturing Execution System). These files support the analysis of **cycle times**, **routing/operation durations**, **stoppage/downtime**, and **order due-date performance**. ## **Files Summary** | File | Rows | Columns | Approx Size (MB) | | :---- | :---- | :---- | :---- | | df\_unit\_level\_cycle\_downtime\_anonymised.csv | 165,384 | 6 | 6.34 | | order\_analysis\_anonymised.csv | 53,164 | 9 | 3.83 | | product\_cycle\_anonymised.csv | 952,730 | 17 | 156.75 | | stoppage\_all\_anonymised.csv | 10,891 | 14 | 1.93 | ## **Anonymisation & Standards** * **Anonymisation:** Company names are replaced with Company\_XX. Identifiers such as orderId, unitId, stockId, operationId, eventId, and stoppage id are anonymised tokens. No personally identifying information (PII) is present. * **Timezones:** Timestamp fields include a UTC offset (e.g., \+00:00). When loading into Pandas, it is recommended to use: pd.to\_datetime(col, utc=True, errors='coerce'). * **Negative Values:** Some duration fields contain negative values due to system clock issues. These should be filtered or investigated during the cleaning phase. ## **Data Dictionary** ### **1\. product\_cycle\_anonymised.csv** Used for unit-level and operation-level benchmarking, bottleneck identification, and variability analysis across routing steps. | Column | Type | Nullable | Description | Notes | | :---- | :---- | :---- | :---- | :---- | | **stockId** | object | No | Anonymised SKU identifier. | | | **avgEstimatedDurationMinutes** | float64 | No | Average estimated duration for this stock/route context. | Range: 1 to 6.66e+03 | | **avgActualDurationMinutes** | float64 | No | Average actual duration for this stock/route context. | | | **unitId** | object | No | Anonymised unit/item identifier. | | | **unitEstimatedDurationMinutes** | float64 | No | Estimated duration for the unit. | | | **unitActualDurationMinutes** | float64 | No | Actual duration for the unit. | | | **routingIndex** | int64 | No | Sequence index of the step within the route. | Range: 1 to 19 | | **routingEstimatedDurationMinutes** | float64 | No | Estimated duration for the routing step. | | | **routingActualDurationMinutes** | float64 | No | Actual duration for the routing step. | Contains 139 negative values. | | **operationId** | object | No | Anonymised operation identifier. | | | **operationEstimatedDurationMinutes** | float64 | No | Estimated duration for the operation. | | | **operationActualDurationMinutes** | float64 | No | Actual duration for the operation. | Contains 165 negative values. | | **itemRoutingOperationId** | object | No | Unique unit-operation instance ID. | **Primary key** for stoppage joins. | | **Date** | object | Yes | Production or extract date. | ISO timestamp; 3.35% missing. | | **Company** | object | No | Anonymised company identifier. | | ### **2\. df\_unit\_level\_cycle\_downtime\_anonymised.csv** Used for unit-level rollups to compare flow time against downtime contribution. | Column | Type | Nullable | Description | Notes | | :---- | :---- | :---- | :---- | :---- | | **Company** | object | No | Anonymised company identifier. | | | **unitId** | object | No | Anonymised unit/item identifier. | | | **unitActualMin** | float64 | No | Actual elapsed time for the unit (minutes). | | | **totalStopMinutes** | float64 | Yes | Total stoppage/downtime minutes for the unit. | 96% missing (treat as 0). | | **numEvents** | float64 | Yes | Number of stoppage events linked to the unit. | 96% missing (treat as 0). | | **numUnits** | int64 | No | Count of units represented (usually 1). | | ### **3\. order\_analysis\_anonymised.csv** Used for analysing on-time delivery performance and lateness patterns for completed vs open orders. | Column | Type | Nullable | Description | Notes | | :---- | :---- | :---- | :---- | :---- | | **orderId** | object | No | Anonymised sales/work order identifier. | | | **requiredByDate** | object | Yes | Required-by (due) date/time for the order. | ISO timestamp. | | **completedDate** | object | Yes | Completion date/time. | Null for open orders (81%). | | **lateByDays** | float64 | Yes | Order lateness in days (completed \- required). | | | **lateByDays\_raw** | float64 | Yes | Raw lateness (includes negative values). | | | **open\_days\_late** | float64 | Yes | Lateness relative to extract time for open orders. | | | **Is\_Perfect** | float64 | Yes | Perfect-order flag (1=on time, 0=late). | | | **combinedLateDays** | float64 | Yes | Single metric combining open and closed lateness. | | | **Company** | object | No | Anonymised company identifier. | | ### **4\. stoppage\_all\_anonymised.csv** Used for identifying top downtime reasons by operation or company. | Column | Type | Nullable | Description | Notes | | :---- | :---- | :---- | :---- | :---- | | **id** | object | No | Anonymised stoppage reason identifier. | | | **description** | object | No | Stoppage reason description (e.g. Machine Issue). | | | **operationId** | object | No | Anonymised operation identifier. | | | **operationName** | object | No | Human-readable operation name. | | | **eventId** | object | No | Anonymised stoppage event identifier. | | | **eventStartDate** | object | No | Stoppage event start timestamp. | | | **eventEndDate** | object | No | Stoppage event end timestamp. | | | **eventTimeTrackedInMinutes** | float64 | No | Tracked time as recorded by the source system. | | | **eventDurationMinutes** | float64 | No | Duration computed from end \- start. | | | **itemRoutingOperationId** | object | No | Unique unit-operation instance ID. | Link to product\_cycle. | | **itemUnit** | object | No | Anonymised unit/item identifier. | Link to unitId. | | **Company** | object | No | Anonymised company identifier. | | ## **Suggested Join Keys** * **Unit Tracking:** unitId ↔ itemUnit * **Operation Specifics:** itemRoutingOperationId (Best key to connect duration records to specific stoppage events). * **Organisation:** Company * **Process Step:** operationId ## **Data Quality Notes** * **Missing Data:** Many records in df\_unit\_level\_cycle\_downtime\_anonymised.csv have nulls for downtime. This typically indicates zero downtime events occurred for that unit. * **Open Orders:** A high percentage (81%) of orders are currently open. Analysis of these should focus on open\_days\_late rather than completedDate. * **Negatives:** Negative durations in product\_cycle\_anonymised.csv (specifically in actual duration columns) should be treated as data quality errors. **Provenance:** Please record the extract date, source system version, and any applied filters (date range, plant, or operation types) externally to ensure benchmarking is reproducible.
to
# **Manufacturing Operations Dataset Documentation** ## **Overview** This package contains anonymised manufacturing operations datasets extracted from an MES (Manufacturing Execution System). These files support the analysis of **cycle times**, **routing/operation durations**, **stoppage/downtime**, and **order due-date performance**. ## **Files Summary** | File | Rows | Columns | Approx Size (MB) | | :---- | :---- | :---- | :---- | | df\_unit\_level\_cycle\_downtime\_anonymised.csv | 165,384 | 6 | 6.34 | | order\_analysis\_anonymised.csv | 53,164 | 9 | 3.83 | | product\_cycle\_anonymised.csv | 952,730 | 17 | 156.75 | | stoppage\_all\_anonymised.csv | 10,891 | 14 | 1.93 | ## **Anonymisation & Standards** * **Anonymisation:** Company names are replaced with Company\_XX. Identifiers such as orderId, unitId, stockId, operationId, eventId, and stoppage id are anonymised tokens. No personally identifying information (PII) is present. * **Timezones:** Timestamp fields include a UTC offset (e.g., \+00:00). When loading into Pandas, it is recommended to use: pd.to\_datetime(col, utc=True, errors='coerce'). * **Negative Values:** Some duration fields contain negative values due to system clock issues. These should be filtered or investigated during the cleaning phase. ## **Data Quality Notes** * **Missing Data:** Many records in df\_unit\_level\_cycle\_downtime\_anonymised.csv have nulls for downtime. This typically indicates zero downtime events occurred for that unit. * **Open Orders:** A high percentage (81%) of orders are currently open. Analysis of these should focus on open\_days\_late rather than completedDate. * **Negatives:** Negative durations in product\_cycle\_anonymised.csv (specifically in actual duration columns) should be treated as data quality errors. **Provenance:** Please record the extract date, source system version, and any applied filters (date range, plant, or operation types) externally to ensure benchmarking is reproducible.

              
    
          
          
        
        
            f 1 { f 1 {
            2   "author": "SMDH Data Science Team", 2   "author": "SMDH Data Science Team",
            3   "author_email": "info@smdh.uk", 3   "author_email": "info@smdh.uk",
            4   "cloud_storage_key_segment": "manufacturing-operations-dataset", 4   "cloud_storage_key_segment": "manufacturing-operations-dataset",
            5   "creator_user_id": "06d04fb0-fe0e-4a6a-b958-061fb38a9f9c", 5   "creator_user_id": "06d04fb0-fe0e-4a6a-b958-061fb38a9f9c",
            6   "groups": [], 6   "groups": [],
            7   "id": "8ddb1432-fa3a-4173-a46c-915fe230e08e", 7   "id": "8ddb1432-fa3a-4173-a46c-915fe230e08e",
            8   "isopen": false, 8   "isopen": false,
            9   "license_id": "other-nc", 9   "license_id": "other-nc",
            10   "license_title": "Other (Non-Commercial)", 10   "license_title": "Other (Non-Commercial)",
            11   "maintainer": "Dermot Kerr", 11   "maintainer": "Dermot Kerr",
            12   "maintainer_email": "d.kerr@smdh.uk", 12   "maintainer_email": "d.kerr@smdh.uk",
            13   "metadata_created": "2026-02-20T17:42:37.166534", 13   "metadata_created": "2026-02-20T17:42:37.166534",
            n 14   "metadata_modified": "2026-02-20T17:46:32.480128", n 14   "metadata_modified": "2026-02-20T17:48:01.004764",
            15   "name": "ulster-university--manufacturing-operations-dataset", 15   "name": "ulster-university--manufacturing-operations-dataset",
            16   "notes": "# **Manufacturing Operations Dataset  16   "notes": "# **Manufacturing Operations Dataset 
            17 Documentation**\r\n\r\n## **Overview**\r\n\r\nThis package contains  17 Documentation**\r\n\r\n## **Overview**\r\n\r\nThis package contains 
            18 anonymised manufacturing operations datasets extracted from an MES  18 anonymised manufacturing operations datasets extracted from an MES 
            19 (Manufacturing Execution System). These files support the analysis of  19 (Manufacturing Execution System). These files support the analysis of 
            20 **cycle times**, **routing/operation durations**,  20 **cycle times**, **routing/operation durations**, 
            21 **stoppage/downtime**, and **order due-date performance**.\r\n\r\n##  21 **stoppage/downtime**, and **order due-date performance**.\r\n\r\n## 
            22 **Files Summary**\r\n\r\n| File | Rows | Columns | Approx Size (MB)  22 **Files Summary**\r\n\r\n| File | Rows | Columns | Approx Size (MB) 
            23 |\r\n| :---- | :---- | :---- | :---- |\r\n|  23 |\r\n| :---- | :---- | :---- | :---- |\r\n| 
            24 df\\_unit\\_level\\_cycle\\_downtime\\_anonymised.csv | 165,384 | 6 |  24 df\\_unit\\_level\\_cycle\\_downtime\\_anonymised.csv | 165,384 | 6 | 
            25 6.34 |\r\n| order\\_analysis\\_anonymised.csv | 53,164 | 9 | 3.83  25 6.34 |\r\n| order\\_analysis\\_anonymised.csv | 53,164 | 9 | 3.83 
            26 |\r\n| product\\_cycle\\_anonymised.csv | 952,730 | 17 | 156.75 |\r\n|  26 |\r\n| product\\_cycle\\_anonymised.csv | 952,730 | 17 | 156.75 |\r\n| 
            27 stoppage\\_all\\_anonymised.csv | 10,891 | 14 | 1.93 |\r\n\r\n##  27 stoppage\\_all\\_anonymised.csv | 10,891 | 14 | 1.93 |\r\n\r\n## 
            28 **Anonymisation & Standards**\r\n\r\n* **Anonymisation:** Company  28 **Anonymisation & Standards**\r\n\r\n* **Anonymisation:** Company 
            29 names are replaced with Company\\_XX. Identifiers such as orderId,  29 names are replaced with Company\\_XX. Identifiers such as orderId, 
            30 unitId, stockId, operationId, eventId, and stoppage id are anonymised  30 unitId, stockId, operationId, eventId, and stoppage id are anonymised 
            31 tokens. No personally identifying information (PII) is present.  \r\n*  31 tokens. No personally identifying information (PII) is present.  \r\n* 
            32 **Timezones:** Timestamp fields include a UTC offset (e.g., \\+00:00).  32 **Timezones:** Timestamp fields include a UTC offset (e.g., \\+00:00). 
            33 When loading into Pandas, it is recommended to use:  33 When loading into Pandas, it is recommended to use: 
            34 pd.to\\_datetime(col, utc=True, errors='coerce').  \r\n* **Negative  34 pd.to\\_datetime(col, utc=True, errors='coerce').  \r\n* **Negative 
            35 Values:** Some duration fields contain negative values due to system  35 Values:** Some duration fields contain negative values due to system 
            36 clock issues. These should be filtered or investigated during the  36 clock issues. These should be filtered or investigated during the 
            t 37 cleaning phase.\r\n\r\n## **Data Dictionary**\r\n\r\n### **1\\.  t 37 cleaning phase.\r\n\r\n\r\n## **Data Quality Notes**\r\n\r\n* 
            38 product\\_cycle\\_anonymised.csv**\r\n\r\nUsed for unit-level and  
            39 operation-level benchmarking, bottleneck identification, and  
            40 variability analysis across routing steps.\r\n\r\n| Column | Type |  
            41 Nullable | Description | Notes |\r\n| :---- | :---- | :---- | :---- |  
            42 :---- |\r\n| **stockId** | object | No | Anonymised SKU identifier. |   
            43 |\r\n| **avgEstimatedDurationMinutes** | float64 | No | Average  
            44 estimated duration for this stock/route context. | Range: 1 to  
            45 6.66e+03 |\r\n| **avgActualDurationMinutes** | float64 | No | Average  
            46 actual duration for this stock/route context. |  |\r\n| **unitId** |  
            47 object | No | Anonymised unit/item identifier. |  |\r\n|  
            48 **unitEstimatedDurationMinutes** | float64 | No | Estimated duration  
            49 for the unit. |  |\r\n| **unitActualDurationMinutes** | float64 | No |  
            50 Actual duration for the unit. |  |\r\n| **routingIndex** | int64 | No  
            51 | Sequence index of the step within the route. | Range: 1 to 19 |\r\n|  
            52 **routingEstimatedDurationMinutes** | float64 | No | Estimated  
            53 duration for the routing step. |  |\r\n|  
            54 **routingActualDurationMinutes** | float64 | No | Actual duration for  
            55 the routing step. | Contains 139 negative values. |\r\n|  
            56 **operationId** | object | No | Anonymised operation identifier. |   
            57 |\r\n| **operationEstimatedDurationMinutes** | float64 | No |  
            58 Estimated duration for the operation. |  |\r\n|  
            59 **operationActualDurationMinutes** | float64 | No | Actual duration  
            60 for the operation. | Contains 165 negative values. |\r\n|  
            61 **itemRoutingOperationId** | object | No | Unique unit-operation  
            62 instance ID. | **Primary key** for stoppage joins. |\r\n| **Date** |  
            63 object | Yes | Production or extract date. | ISO timestamp; 3.35%  
            64 missing. |\r\n| **Company** | object | No | Anonymised company  
            65 identifier. |  |\r\n\r\n### **2\\.  
            66 df\\_unit\\_level\\_cycle\\_downtime\\_anonymised.csv**\r\n\r\nUsed  
            67 for unit-level rollups to compare flow time against downtime  
            68 contribution.\r\n\r\n| Column | Type | Nullable | Description | Notes  
            69 |\r\n| :---- | :---- | :---- | :---- | :---- |\r\n| **Company** |  
            70 object | No | Anonymised company identifier. |  |\r\n| **unitId** |  
            71 object | No | Anonymised unit/item identifier. |  |\r\n|  
            72 **unitActualMin** | float64 | No | Actual elapsed time for the unit  
            73 (minutes). |  |\r\n| **totalStopMinutes** | float64 | Yes | Total  
            74 stoppage/downtime minutes for the unit. | 96% missing (treat as 0).  
            75 |\r\n| **numEvents** | float64 | Yes | Number of stoppage events  
            76 linked to the unit. | 96% missing (treat as 0). |\r\n| **numUnits** |  
            77 int64 | No | Count of units represented (usually 1). |  |\r\n\r\n###  
            78 **3\\. order\\_analysis\\_anonymised.csv**\r\n\r\nUsed for analysing  
            79 on-time delivery performance and lateness patterns for completed vs  
            80 open orders.\r\n\r\n| Column | Type | Nullable | Description | Notes  
            81 |\r\n| :---- | :---- | :---- | :---- | :---- |\r\n| **orderId** |  
            82 object | No | Anonymised sales/work order identifier. |  |\r\n|  
            83 **requiredByDate** | object | Yes | Required-by (due) date/time for  
            84 the order. | ISO timestamp. |\r\n| **completedDate** | object | Yes |  
            85 Completion date/time. | Null for open orders (81%). |\r\n|  
            86 **lateByDays** | float64 | Yes | Order lateness in days (completed \\-  
            87 required). |  |\r\n| **lateByDays\\_raw** | float64 | Yes | Raw  
            88 lateness (includes negative values). |  |\r\n| **open\\_days\\_late**  
            89 | float64 | Yes | Lateness relative to extract time for open orders. |   
            90 |\r\n| **Is\\_Perfect** | float64 | Yes | Perfect-order flag (1=on  
            91 time, 0=late). |  |\r\n| **combinedLateDays** | float64 | Yes | Single  
            92 metric combining open and closed lateness. |  |\r\n| **Company** |  
            93 object | No | Anonymised company identifier. |  |\r\n\r\n### **4\\.  
            94 stoppage\\_all\\_anonymised.csv**\r\n\r\nUsed for identifying top  
            95 downtime reasons by operation or company.\r\n\r\n| Column | Type |  
            96 Nullable | Description | Notes |\r\n| :---- | :---- | :---- | :---- |  
            97 :---- |\r\n| **id** | object | No | Anonymised stoppage reason  
            98 identifier. |  |\r\n| **description** | object | No | Stoppage reason  
            99 description (e.g. Machine Issue). |  |\r\n| **operationId** | object |  
            100 No | Anonymised operation identifier. |  |\r\n| **operationName** |  
            101 object | No | Human-readable operation name. |  |\r\n| **eventId** |  
            102 object | No | Anonymised stoppage event identifier. |  |\r\n|  
            103 **eventStartDate** | object | No | Stoppage event start timestamp. |   
            104 |\r\n| **eventEndDate** | object | No | Stoppage event end timestamp.  
            105 |  |\r\n| **eventTimeTrackedInMinutes** | float64 | No | Tracked time  
            106 as recorded by the source system. |  |\r\n| **eventDurationMinutes** |  
            107 float64 | No | Duration computed from end \\- start. |  |\r\n|  
            108 **itemRoutingOperationId** | object | No | Unique unit-operation  
            109 instance ID. | Link to product\\_cycle. |\r\n| **itemUnit** | object |  
            110 No | Anonymised unit/item identifier. | Link to unitId. |\r\n|  
            111 **Company** | object | No | Anonymised company identifier. |   
            112 |\r\n\r\n## **Suggested Join Keys**\r\n\r\n* **Unit Tracking:** unitId  
            113 \u2194 itemUnit  \r\n* **Operation Specifics:** itemRoutingOperationId  
            114 (Best key to connect duration records to specific stoppage events).   
            115 \r\n* **Organisation:** Company  \r\n* **Process Step:**  
            116 operationId\r\n\r\n## **Data Quality Notes**\r\n\r\n* **Missing  
            117 Data:** Many records in  38 **Missing Data:** Many records in 
            118 df\\_unit\\_level\\_cycle\\_downtime\\_anonymised.csv have nulls for  39 df\\_unit\\_level\\_cycle\\_downtime\\_anonymised.csv have nulls for 
            119 downtime. This typically indicates zero downtime events occurred for  40 downtime. This typically indicates zero downtime events occurred for 
            120 that unit.  \r\n* **Open Orders:** A high percentage (81%) of orders  41 that unit.  \r\n* **Open Orders:** A high percentage (81%) of orders 
            121 are currently open. Analysis of these should focus on  42 are currently open. Analysis of these should focus on 
            122 open\\_days\\_late rather than completedDate.  \r\n* **Negatives:**  43 open\\_days\\_late rather than completedDate.  \r\n* **Negatives:** 
            123 Negative durations in product\\_cycle\\_anonymised.csv (specifically  44 Negative durations in product\\_cycle\\_anonymised.csv (specifically 
            124 in actual duration columns) should be treated as data quality  45 in actual duration columns) should be treated as data quality 
            125 errors.\r\n\r\n**Provenance:** Please record the extract date, source  46 errors.\r\n\r\n**Provenance:** Please record the extract date, source 
            126 system version, and any applied filters (date range, plant, or  47 system version, and any applied filters (date range, plant, or 
            127 operation types) externally to ensure benchmarking is reproducible.", 48 operation types) externally to ensure benchmarking is reproducible.",
            128   "num_resources": 5, 49   "num_resources": 5,
            129   "num_tags": 0, 50   "num_tags": 0,
            130   "organization": { 51   "organization": {
            131     "approval_status": "approved", 52     "approval_status": "approved",
            132     "created": "2023-03-20T14:27:38.943709", 53     "created": "2023-03-20T14:27:38.943709",
            133     "description": "Ulster University has a sustained track record in  54     "description": "Ulster University has a sustained track record in 
            134 robotics, computer vision, and computational intelligence. Translating  55 robotics, computer vision, and computational intelligence. Translating 
            135 research into technologies that catalyse innovation in small and large  56 research into technologies that catalyse innovation in small and large 
            136 enterprises, we have been instrumental in attracting inward investment  57 enterprises, we have been instrumental in attracting inward investment 
            137 and developing the knowledge economy. Ulster lead SMDH, lead the  58 and developing the knowledge economy. Ulster lead SMDH, lead the 
            138 virtual manufacturing platform and contribute to data science,  59 virtual manufacturing platform and contribute to data science, 
            139 roll-out and marketing.", 60 roll-out and marketing.",
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