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Your Production Planning Data Template

Plex Smart Manufacturing

Production Planning Attributes (23) Production Planning Activities (16) Extraction Guides (2)

Your Production Planning Data Template

This template provides a comprehensive guide to collecting the right data for optimizing your production planning process. It outlines essential attributes to collect, key activities to track, and practical guidance on extracting this information from your source systems. Use this resource to ensure you capture all necessary data for effective process analysis and improvement.

Recommended attributes to collect
Key activities to track
Extraction guidance

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Production Planning Attributes

These are the recommended data fields to include in your event log for comprehensive production planning analysis and deep insights into your operations.

3 Required 8 Recommended 12 Optional

	Name	Description
	Activity Name ActivityName	The name of the specific event or step that occurred within the production planning process.
Description This attribute describes a single task or milestone in the production planning lifecycle, such as 'Production Order Created', 'Material Requirements Planned', or 'Production Order Completed'. These activities form the backbone of the process map, allowing analysts to visualize the process flow, identify bottlenecks between steps, and analyze the frequency and sequence of events. Each activity corresponds to a recorded event in the source system. Why it matters It defines the steps in the process map, which is the foundation for all process mining analysis, including bottleneck identification and variant analysis. Where to get Derived from event logs, transaction codes, or status change records within various Plex modules related to production planning and execution. Examples Production Order CreatedProduction Plan ApprovedProduction Order ReleasedOperation Completed
	Event Time EventTime	The timestamp indicating when the activity occurred.
Description This attribute records the precise date and time that a specific event or activity was logged in the system. It is the primary temporal element for process analysis. Accurate timestamps are critical for calculating cycle times, durations, and waiting times between activities. They enable the analysis of process performance over time, the identification of bottlenecks, and the measurement of adherence to schedules. Why it matters This timestamp is essential for calculating all time-based metrics, such as cycle times and durations, which are fundamental to performance analysis. Where to get Located in event logs or transaction records alongside the activity information in Plex. Look for fields like 'Creation Date', 'Timestamp', or 'Event Date'. Examples 2023-10-26T09:00:00Z2023-10-26T14:35:10Z2023-10-27T08:21:05Z
	Production Order ProductionOrder	The unique identifier for a production order, which serves as the primary case identifier for the production planning process.
Description The Production Order number uniquely identifies a request to produce a specific quantity of a part or product. It acts as the central case ID that links all related planning, scheduling, execution, and completion events. In process mining, analyzing events grouped by the Production Order allows for a complete end-to-end view of the production lifecycle. This helps in calculating overall cycle times, identifying common process paths, and understanding variations between different production runs. Why it matters This is the essential case identifier that connects all process steps, enabling a holistic analysis of each production run from start to finish. Where to get This identifier is typically found in core production or manufacturing execution modules within Plex. Consult documentation for tables related to Work Orders or Production Orders. Examples WO-2024-05123PROD-789001JN-456-A10034589
	Material Availability MaterialAvailabilityStatus	Indicates whether all required materials for the production order are available.
Description This attribute shows the status of material availability, for example 'Available', 'Shortage', or 'On Order'. This status is critical for determining if a production order can be released to the floor. A key use of this attribute is in the 'Material Shortage Impact Analysis' dashboard. It helps quantify the delays caused by material shortages by correlating a 'Shortage' status with longer wait times before the 'Production Order Released' or 'Production Started' activities. Why it matters Directly supports the analysis of delays caused by material shortages, a common and significant problem in manufacturing. Where to get Consult Plex Smart Manufacturing documentation. This might be a calculated status in the MRP or inventory modules, or a field on the production order itself. Examples All Materials AvailableComponent ShortageAwaiting Purchase OrderPartially Available
	Part Number PartNumber	The unique identifier for the product or material being manufactured.
Description The Part Number, also known as an item number or SKU, specifies the item that the production order is intended to produce. This is a critical piece of master data that links the production process to the product portfolio. Analyzing the process by part number allows for identifying product-specific manufacturing challenges, comparing cycle times for different products, and understanding how material requirements vary. It is fundamental for any product-centric process analysis. Why it matters Enables product-based analysis to compare process performance and identify issues related to specific parts or product families. Where to get Located in the production order line item or header details in Plex. This is a standard field linked to the item master. Examples PN-100-001A45-873-CFG-2023-WIDGETASM-BRKT-550
	Planned End Date PlannedEndDate	The scheduled completion date for the production order.
Description This attribute contains the date by which the production order is planned to be fully completed. This date is a key output of the scheduling process and serves as a baseline for performance measurement. The Planned End Date is critical for the 'Production Schedule Adherence' dashboard and KPI. By comparing this planned date with the actual completion timestamp, organizations can measure their ability to meet production targets and identify sources of delay. Why it matters Serves as the baseline for measuring schedule adherence and on-time performance, which are key indicators of planning and execution effectiveness. Where to get Consult Plex Smart Manufacturing documentation. This is typically found in the production order header and is often named 'Scheduled End Date', 'Due Date', or similar. Examples 2023-11-15T17:00:00Z2023-11-20T23:59:59Z2023-12-01T17:00:00Z
	Planned Quantity PlannedQuantity	The target quantity of the part or product to be produced in the order.
Description This attribute specifies the number of units that are scheduled for production as per the production order. This value is used for material requirements planning, capacity planning, and scheduling. Planned Quantity is essential for calculating the 'Demand Forecast Integration Variance' KPI by comparing it to original forecast numbers. It also provides context for cycle time analysis, as larger orders may naturally have longer lead times. Why it matters Provides the target production volume, which is essential for capacity analysis, scheduling, and understanding order-size-related process variations. Where to get Located in the production order header or line item details in Plex. Look for fields like 'Order Quantity' or 'Planned Quantity'. Examples 1005000751250
	Planner Planner	The employee responsible for planning or managing the production order.
Description This attribute identifies the production planner or scheduler assigned to a specific production order. It can be an individual's name or their employee ID. Analyzing the process by planner is essential for the 'Planner Performance Comparison' dashboard. It helps in identifying differences in efficiency, schedule adherence, and process variations among planners, highlighting opportunities for training or process standardization. Why it matters Allows for performance analysis by planner, helping to identify best practices, inconsistencies, and training needs. Where to get Consult Plex Smart Manufacturing documentation. Typically found in production order header tables, associated with fields like 'Planner Code', 'Scheduler', or 'Created By'. Examples John SmithJane DoePlanner Group AUser789
	Production Order Status ProductionOrderStatus	The current or final status of the production order.
Description This attribute reflects the state of the production order at a given time, such as 'Created', 'Released', 'In Progress', 'Completed', or 'Cancelled'. Status information provides a snapshot of the order's lifecycle and is crucial for outcome analysis. It helps in filtering for active versus completed orders, analyzing cancellation rates, and understanding the reasons for certain process paths. Why it matters It indicates the outcome and current state of a production order, which is essential for filtering, outcome analysis, and understanding process exceptions. Where to get Available in the production order header table in Plex. Look for a 'Status' or 'State' field. Examples PlannedReleasedCompletedClosedCancelled
	Production Priority ProductionPriority	A classification indicating the urgency of the production order.
Description This attribute assigns a priority level, such as 'High', 'Medium', or 'Low', to a production order. This helps planners and production staff prioritize work, especially when resources are constrained. Analyzing by priority is essential for the 'Production Priority Handling Metrics' dashboard. It allows for checking whether high-priority orders are truly being expedited through the process and completed faster than lower-priority ones, validating the effectiveness of the prioritization system. Why it matters Enables analysis of whether high-priority orders are processed faster, ensuring that the prioritization system is working effectively. Where to get Consult Plex Smart Manufacturing documentation. This may be a standard or custom field on the production order header. Examples HighMediumLow19
	Workcenter Workcenter	The specific machine, production line, or area where a manufacturing operation is scheduled to take place.
Description A workcenter represents a specific resource or group of resources where production activities are performed. It could be a single machine, a cell of machines, or a specific assembly line. This attribute is key for the 'Resource Allocation Delay Analysis' and for identifying resource-specific bottlenecks. By analyzing processing and wait times at different workcenters, managers can optimize resource utilization and improve production flow. Why it matters Helps pinpoint resource-specific bottlenecks and analyze capacity utilization, which is crucial for scheduling and throughput optimization. Where to get Consult Plex Smart Manufacturing documentation. This information is typically found in the routing or operations details associated with a production order. Examples CNC-MILL-05ASSEMBLY-LINE-3PACKAGING-STATION-BWC-FINISH-01
	Actual End Date ActualEndDate	The actual timestamp when the last unit of the production order was completed.
Description This attribute captures the time the final operation for the production order was finished and the total required quantity was produced. It marks the end of the execution phase. This is the definitive timestamp used to measure actual performance against the 'Planned End Date' for the 'Production Schedule Adherence' KPI. It is used to calculate the true end-to-end production cycle time. Why it matters Provides the actual completion time needed to accurately calculate schedule adherence and overall production lead times. Where to get This is the timestamp of the 'Production Order Completed' activity or the final operational confirmation in Plex. Examples 2023-11-14T16:55:43Z2023-11-21T11:30:00Z
	Actual Start Date ActualStartDate	The actual timestamp when production work began for the order.
Description This attribute captures the exact time the first physical operation of the production order started on the shop floor. It marks the transition from planning and preparation to execution. This timestamp is essential for analyzing the 'queue time' or delay between when an order is released and when it actually starts. It helps in calculating a more accurate production lead time and supports the 'Material Shortage Impact Analysis' by showing the real start of work. Why it matters Marks the true beginning of the production execution phase, allowing for precise measurement of scheduling delays and queue times. Where to get This is the timestamp of the 'Production Started' activity or the first operational step recorded in the MES component of Plex. Examples 2023-11-01T08:05:12Z2023-11-05T10:20:00Z
	Completed Quantity CompletedQuantity	The actual quantity of the part or product that was successfully produced.
Description This attribute records the final count of good units produced and confirmed for a production order. This value is compared against the Planned Quantity to determine yield and order fulfillment rates. Analyzing the Completed Quantity helps in assessing production efficiency and quality. Significant deviations from the Planned Quantity can indicate production problems, high scrap rates, or data entry errors, which can be investigated further. Why it matters Indicates the actual production output, which is used to analyze yield, scrap rates, and fulfillment accuracy against the planned quantity. Where to get Found in production reporting or confirmation records in Plex. Look for fields like 'Good Quantity', 'Yield Quantity', or 'Actual Quantity'. Examples 984950751250
	End Time EndTime	The timestamp indicating when an activity was completed.
Description The End Time marks the completion of a specific activity. When paired with the Start Time, it defines the processing time for that event. In process mining, having both Start and End Times for activities allows for a more detailed analysis of processing time versus waiting time. This helps differentiate time spent actively working on a task from idle time spent waiting for the next step, which is crucial for accurate bottleneck analysis. Why it matters Enables the calculation of precise activity processing times, distinguishing active work time from idle waiting time. Where to get This may be available directly in event logs or can be derived by using the Start Time of the subsequent event. Examples 2023-10-26T09:15:00Z2023-10-26T15:05:20Z2023-10-27T10:00:00Z
	Event Processing Time EventProcessingTime	The duration of time spent actively working on a specific activity.
Description This calculated attribute measures the time between the start and end of a single activity. It represents the actual 'touch time' or work performed during a process step. Analyzing processing time is fundamental to identifying which specific activities are consuming the most time and effort in the process. This is distinct from cycle time, which includes waiting periods, and is key to pinpointing inefficiencies within tasks themselves. Why it matters Measures the active work time for an activity, helping to isolate and analyze the most time-consuming tasks in the process. Where to get Calculated field, derived by subtracting the 'EventTime' (StartTime) from the 'EndTime' of an activity. Examples PT1H30MPT8HP2DT4H15M
	Is Late IsLate	A boolean flag indicating if the production order was completed after its planned end date.
Description This is a simple boolean (true/false) flag calculated for each production order. It is set to 'true' if the actual completion time is later than the planned end date, and 'false' otherwise. This attribute simplifies analysis and reporting for schedule adherence. It allows for easy filtering and aggregation to calculate the 'Production Schedule Adherence Rate' KPI and to quickly identify all orders that failed to meet their deadline. Why it matters Provides a simple, binary classification of on-time versus late orders, which is ideal for calculating adherence rates and high-level KPI dashboards. Where to get Calculated field, derived from a comparison: 'ActualEndDate' > 'PlannedEndDate'. Examples truefalse
	Last Data Update LastDataUpdate	The timestamp when the data was last refreshed from the source system.
Description This attribute indicates the last time the data was extracted and loaded into the process mining tool. It provides context for the recency of the analysis. Knowing the data's freshness is important for users to understand if they are viewing the most current process information. It helps manage expectations about the data's timeliness and is a key piece of metadata for any dashboard or report. Why it matters Informs users about the recency of the data, ensuring they understand the time frame of the current analysis. Where to get This is a metadata field generated and stored during the data ingestion process, recording the timestamp of the data load. Examples 2024-05-21T02:00:00Z2024-05-20T02:00:00Z
	Order Type OrderType	A category that classifies the production order, such as standard, rework, or prototype.
Description The Order Type is used to differentiate production orders based on their purpose. For example, a 'Standard' order is for regular production, a 'Rework' order is to fix defects, and a 'Prototype' order is for new product development. This attribute allows for more nuanced analysis by filtering or comparing the process flows for different types of orders. Rework orders, for instance, are expected to have different paths and cycle times than standard orders, and separating them is key to a clean analysis. Why it matters Enables segmentation of the analysis, as different order types like 'rework' or 'prototype' naturally have different process flows and performance expectations. Where to get Consult Plex Smart Manufacturing documentation. This is often a configurable field on the production order header. Examples Standard ProductionRework OrderEngineering SampleExternal Subcontract
	Plant Plant	The manufacturing facility or location where the production order is being executed.
Description The Plant attribute identifies the specific physical site, such as a factory or production facility. In multi-plant organizations, this is a key attribute for segmenting and comparing process performance. Analyzing by Plant allows for benchmarking processes across different locations. This can reveal site-specific issues, highlight best practices at high-performing plants, and inform decisions about process standardization. Why it matters Allows for comparing process performance across different manufacturing sites, which is vital for benchmarking and standardization in multi-plant operations. Where to get Typically available as a core organizing principle in Plex, often associated with the production order header. Look for 'Plant', 'Site', or 'Location' fields. Examples Detroit PlantAtlanta AssemblySite 007Mexico Facility
	Rework Reason Code ReworkReasonCode	A code indicating the reason for a production plan adjustment or rework loop.
Description When a production plan is adjusted or an order is sent for rework, this attribute provides a standardized reason for the deviation. Examples include 'Defective Material', 'Machine Downtime', or 'Specification Change'. This attribute provides the 'why' behind process deviations identified in variant analysis. It is crucial for root cause analysis of the 'Rework & Rerouting Rate' KPI, helping teams to address the underlying issues that cause costly rework and delays. Why it matters Provides critical context for rework and process deviations, enabling targeted root cause analysis to reduce waste and improve quality. Where to get Consult Plex Smart Manufacturing documentation. This data may be associated with non-conformance, quality, or production adjustment records. Examples QA_FAILMAT_SUBENG_CHGOPER_ERR
	Schedule Deviation ScheduleDeviation	The time difference between the planned end date and the actual completion date.
Description This calculated metric quantifies how early or late a production order was completed relative to its schedule. A positive value indicates a delay, a negative value indicates an early completion, and zero means it was on time. This attribute provides a more granular view of performance than a simple 'late' flag. It is used in the 'Production Schedule Adherence' dashboard to visualize the magnitude of delays, helping to prioritize improvement efforts on the most significant deviations. Why it matters Quantifies the exact amount of time an order deviated from its schedule, providing a precise measure of lateness or earliness. Where to get Calculated field, derived by subtracting the 'PlannedEndDate' from the 'ActualEndDate' at the case level. Examples P2DT3H15M-P1DT0H0MPT5H
	Source System SourceSystem	The system of record from which the data was extracted.
Description This attribute specifies the origin of the data, which in this case is Plex Smart Manufacturing. It is useful in environments where data might be merged from multiple systems, ensuring clarity on data provenance. Maintaining this information helps in data governance and troubleshooting, as it clearly identifies the source for any data validation or enrichment activities. Why it matters It provides crucial context about data origin, which is important for data governance, validation, and in multi-system environments. Where to get This is typically a static value added during the data extraction and transformation process to label the dataset. Examples Plex Smart ManufacturingPlex MESPlex ERP

Required Recommended Optional

Production Planning Activities

These are the key process steps and milestones to capture in your event log for accurate process discovery and a clear understanding of your production flow.

6 Recommended 10 Optional

	Activity	Description
	Demand Forecast Assessed	Represents the initial receipt and assessment of a demand forecast which precedes the creation of a production order. This event is often captured in a demand planning module and serves as the trigger for the entire production planning process.
Why it matters This activity marks the true start of the planning lifecycle. Analyzing the time from this point to order creation helps identify delays in translating demand into actionable production plans, supporting the 'Demand Forecast Integration Efficiency' dashboard. Where to get This information is typically found in demand planning or sales and operations planning modules within Plex, or an integrated system. It may need to be inferred from the creation date of a forecast record linked to the subsequent production order. Capture Inferred from the creation timestamp of a demand forecast record that is later linked to the production order. Event type inferred
	Production Order Completed	Marks the completion of all manufacturing operations for the entire production order. This is a final shop floor transaction indicating that the planned quantity has been produced. The event is explicitly captured when an operator or system process marks the order as complete.
Why it matters This activity is the primary 'end' event for the happy path of the process. It is the endpoint for calculating the 'Avg Production Order Lead Time' and is essential for measuring 'Production Schedule Adherence' and 'Production Throughput Volume'. Where to get This is an explicit status change on the production order, often triggered by the final quantity reporting transaction. The timestamp is recorded when the order status moves to 'Completed' or 'Finished'. Capture Use the timestamp associated with the transaction that changes the production order status to 'Completed'. Event type explicit
	Production Order Created	This is the formal creation of the Production Order record within the Plex system. This activity establishes the unique case identifier for the process mining analysis. The event is captured explicitly when a user or system process generates the new order.
Why it matters This activity serves as the official start of the production order's journey within the system. It is the anchor point for measuring overall lead times and understanding the volume of new production demand. Where to get This is captured from the creation timestamp of the production order record in the primary production order data table within Plex. Capture Use the 'creation_date' or equivalent timestamp field from the production order header table. Event type explicit
	Production Order Released	This is a critical milestone where the production order is formally released to the shop floor, making it visible and actionable for production staff. This is almost always an explicit user-driven action within the MES, triggering the creation of job packets or digital work instructions.
Why it matters Releasing the order is the key handoff from planning to execution. It is a vital milestone for tracking throughput and analyzing delays between planning approval and the start of actual production. Where to get This is typically an explicit transaction in Plex's production management module. The event is captured from the timestamp of the 'Release' action, often stored in a dedicated field or a transaction log. Capture Use the 'release_date' timestamp field on the production order or the timestamp from the release transaction log. Event type explicit
	Production Plan Approved	This activity signifies that the production plan has been formally approved and is ready to be released to the shop floor. This event is typically captured through an explicit approval action or an associated status change on the order.
Why it matters This marks the end of the planning and approval phase and is the endpoint for calculating the 'Production Plan Approval Time' KPI. Delays in approval are a common bottleneck that this activity helps to quantify and locate. Where to get Can be an explicit event from an approval transaction log or inferred from a status change on the production order, such as moving from 'Pending Approval' to 'Approved' or 'Ready to Release'. Capture Capture the timestamp when the production order status is updated to 'Approved' or an equivalent value. Event type inferred
	Production Started	This activity marks the beginning of physical work on the production order on the shop floor. In a system like Plex, this is typically an explicit event captured when an operator scans a barcode or manually starts a job at a work center terminal.
Why it matters This is a key milestone that signals the start of the value-adding process. It is essential for analyzing the gap between 'Order Released' and 'Production Started' to identify pre-production delays and for calculating actual production cycle times. Where to get Captured from shop floor data collection transactions in Plex. This event corresponds to the timestamp of the first 'job start' or 'operation start' transaction recorded against the production order. Capture Use the timestamp from the first labor ticket creation or machine start event associated with the production order. Event type explicit
	Master Production Schedule Created	This activity marks the creation of the Master Production Schedule (MPS) based on demand forecasts and existing orders. It is a high-level plan that dictates what will be produced, in what quantities, and when. This is likely recorded when a planner finalizes and saves an MPS version.
Why it matters Tracking this milestone is essential for measuring the efficiency of the initial planning phase. The duration between demand assessment and MPS creation is a key indicator of planning agility and is measured by the 'Master Schedule Creation Cycle Time' KPI. Where to get Recorded in the Master Production Scheduling module of Plex. The event can be captured from the creation timestamp of the MPS record or a log entry indicating its finalization. Capture Capture the creation timestamp of the MPS entry or a specific status change event in the scheduling module. Event type explicit
	Material Requirements Planned	Represents the execution of the Material Requirements Planning (MRP) process for the production order. This system job calculates the raw materials, components, and subassemblies needed. The event is typically captured when the MRP run completes for the relevant orders.
Why it matters Analyzing this step helps identify if material planning is a bottleneck. Delays here can impact the entire production timeline and are crucial for understanding the 'Material Shortage Impact Analysis' dashboard. Where to get This is usually captured in MRP or planning logs within Plex. Look for timestamps associated with MRP job completion or the population of material requirement data against the production order. Capture Timestamp of the MRP run completion log or the last updated timestamp on the order's bill of materials requirements. Event type explicit
	Operation Completed	Represents the completion of an individual manufacturing step or operation within the production order's routing. A production order will typically have multiple such events. This is captured explicitly through shop floor reporting.
Why it matters Tracking individual operations allows for a more granular analysis of where bottlenecks occur during the production phase. It enables comparison of planned versus actual operation times and helps identify problematic work centers. Where to get This is captured from shop floor transactions in Plex, specifically when an operator reports an operation as complete or logs the quantity produced for that step. Capture Use the timestamps from 'operation complete' or 'quantity reporting' transactions for each step in the order's routing. Event type explicit
	Production Order Cancelled	Represents the cancellation of a production order at any point before completion. This is an alternative, negative outcome for the process. The event is captured by a specific status change on the order.
Why it matters Tracking cancellations is crucial for understanding process failures. Analyzing when and why orders are cancelled can reveal issues with demand forecasting, planning accuracy, or material availability. Where to get This is inferred from a status change on the production order to a 'Cancelled' or voided state. The timestamp of this status change is the event time. Capture Capture the timestamp when the production order status field is updated to 'Cancelled'. Event type inferred
	Production Order Closed	This is the final administrative or financial closing of the production order. At this stage, all costs are settled, and the order is locked from further transactions. This is typically an explicit action performed by the finance or planning department.
Why it matters This activity marks the true administrative end of the production order's lifecycle. Analyzing the time between 'Production Completed' and 'Production Closed' can reveal lengthy delays in financial closing processes. Where to get This is captured by a status change on the production order to 'Closed'. The timestamp of this final status update provides the event time. Capture Use the timestamp of the status change transaction that moves the order to a 'Closed' state. Event type explicit
	Production Performance Analyzed	Represents a post-completion analysis step where production variances, costs, and quality metrics are reviewed. This might be a system-generated variance calculation or a manual review by a production controller or cost accountant.
Why it matters Including this activity provides insight into the post-production process. It helps understand the total time until the order is fully analyzed and its performance is understood, which can reveal administrative bottlenecks after production ends. Where to get This event may be inferred from the timestamp of variance calculation jobs or the creation date of a production performance report. It could also be a manual status change indicating 'Analysis Complete'. Capture Capture the run date of cost variance calculation jobs or a status change to 'Analysis Complete' on the production order. Event type inferred
	Production Plan Adjusted	This event signifies that a change was made to the production order after it was released, such as a change in quantity, routing, or bill of materials. This is typically captured in an audit trail or change log associated with the production order.
Why it matters This activity is critical for identifying rework, scope changes, and process instability. It directly supports the 'Rework & Rerouting Rate' KPI and helps uncover the root causes of production deviations and inefficiencies. Where to get This data is found in change logs or audit trail tables for the production order module in Plex. The event is the timestamp of any significant field modification after the 'Production Order Released' event. Capture Filter the production order's audit log for changes that occur after the order's release date. Event type explicit
	Production Plan Sent for Review	Indicates that the prepared production plan has been submitted for approval. This is often represented by a status change on the production order. This event marks the beginning of the approval sub-process.
Why it matters This activity is the starting point for measuring the 'Production Plan Approval Cycle Time'. Tracking it helps identify how long plans wait for review, which can be a significant source of administrative delay. Where to get This is likely inferred from a status change on the production order, for example, a status changing from 'In Planning' to 'Pending Approval'. The timestamp of this status change would be used. Capture Capture the timestamp when the production order status field changes to a value like 'Pending Approval' or 'In Review'. Event type inferred
	Production Schedule Created	This event signifies the creation of a detailed production schedule, assigning specific operations to work centers and time slots. It is the outcome of capacity planning and scheduling processes. This is likely logged when a schedule is saved or published.
Why it matters This is a critical milestone before releasing an order to the floor. It is a key event for the 'Scheduling Bottleneck Identification' dashboard, helping to analyze the efficiency of the detailed scheduling phase. Where to get Captured from the production scheduling module in Plex. The event can be identified by the creation or 'last saved' timestamp of the detailed schedule linked to the production order. Capture Use the timestamp when the detailed production schedule for the order is first saved or confirmed by a planner. Event type explicit
	Resource Allocation Confirmed	Represents the confirmation that specific resources, such as machines, tools, or personnel, have been assigned to the production order. This can be a separate step after release or part of the release process itself. The event is captured when resource assignments are finalized in the system.
Why it matters This activity is crucial for the 'Resource Allocation Delay Analysis' dashboard. It helps differentiate between delays caused by planning and those caused by resource unavailability on the shop floor. Where to get This information may be inferred from the population of resource-related fields on the production order or its associated routing steps. The timestamp would be when these fields are last updated before production starts. Capture Capture the timestamp when work center, machine, or employee fields are populated for the order's first operation. Event type inferred

Recommended Optional

Extraction Guides

How to get your data from Plex Smart Manufacturing

Steps

Access IntelliPlex: Log in to the Plex Smart Manufacturing Platform. Navigate to the IntelliPlex Analytic Applications module. You will need the appropriate permissions to create and edit analytic applications.
Create a New Analytic Application: Start a new report or analytic application. Give it a descriptive name, such as "ProcessMind Production Planning Event Log".
Define Data Sources: Identify and add the necessary Plex data sources (tables or views) to your application. This will include sources for production orders, status change logs, material planning runs, shop floor transactions, and potentially demand forecasts and scheduling logs. You may need assistance from a Plex administrator to identify the exact table names for your instance.
Construct the Base Queries: For each of the 16 required activities, you will create a separate query or data block. Each block will select the same set of columns (ProductionOrder, ActivityName, EventTime, etc.) from the relevant data source. For example, the 'Production Order Created' event will query the main production order table, while 'Operation Completed' events will query the shop floor transaction log.
Implement the UNION ALL Logic: Combine the 16 individual queries into a single dataset using the UNION ALL command. This is the critical step that transforms the data from different tables into a single, chronological event log format. You can do this in the SQL editor within IntelliPlex or by using the graphical data flow tools to merge the datasets.
Apply Filters: In the IntelliPlex application, create user-configurable filters. The most important filter is for the date range (EventTime). Also add filters for PartNumber, Workcenter, and ProductionOrderStatus to allow for focused analysis.
Format Columns: Ensure the EventTime column is in a consistent timestamp format (e.g., YYYY-MM-DD HH:MI:SS) and that other columns have the correct data type. Rename columns as needed to match the required attribute names, for instance, production_order_no should be aliased as ProductionOrder.
Save and Test: Save the analytic application. Run the report for a small, recent date range (e.g., the last week) to validate the results, check for errors, and ensure all 16 activity types are being generated correctly.
Schedule the Export: Once validated, navigate to the scheduling section of IntelliPlex. Create a new scheduled task to run the application automatically. Configure the schedule (e.g., daily at 2:00 AM) and the output format.
Configure Export Destination: Set the export destination for the scheduled task. Common options include saving to a network file share, FTP server, or sending via email. Configure the output file format as CSV with a UTF-8 encoding for maximum compatibility.
Prepare for Ingestion: Ensure the resulting CSV file has a header row that matches the attribute names required by your process mining tool. The file is now ready for upload and analysis.

Configuration

Prerequisites: A valid Plex Smart Manufacturing Platform license that includes the IntelliPlex module. User permissions are required to access IntelliPlex, create analytic applications, and view the underlying production and scheduling data tables.
Data Sources: The report will require joining data from multiple sources. Key sources include production order headers, production order routings, status or audit logs, MRP execution logs, shop floor transaction records, and scheduling tables. The exact names must be configured based on your system.
Date Range: A date range filter is essential for managing performance. It is recommended to extract data in batches, for example, 3 to 6 months at a time. The query should filter on the primary event timestamp column.
Key Filters: Beyond the date range, include filters for PartNumber, Planner, and Workcenter. This allows users to run the report for specific subsets of data without modifying the underlying query logic.
Performance Considerations: For high-volume manufacturing environments, running this extraction for a long period can be resource-intensive. Schedule the report to run during off-peak hours. If performance is an issue, consider creating indexed views in the database to pre-aggregate some of the required data.
Output Format: The export must be configured as a CSV (Comma Separated Values) file. Ensure the delimiter is a comma and that text qualifiers (double quotes) are used if any fields might contain commas.

a Sample Query config

/* Production Order Created */
SELECT
  po.order_no AS ProductionOrder,
  'Production Order Created' AS ActivityName,
  po.create_date AS EventTime,
  po.planner_id AS Planner,
  po.status AS ProductionOrderStatus,
  po.part_no AS PartNumber,
  NULL AS Workcenter,
  po.planned_quantity AS PlannedQuantity,
  po.planned_due_date AS PlannedEndDate,
  po.priority AS ProductionPriority,
  po.material_status AS MaterialAvailabilityStatus
FROM part_v_production_order AS po
WHERE po.create_date BETWEEN '[Your Start Date]' AND '[Your End Date]'

UNION ALL

/* Status Change Events: Review, Approved, Released, Closed, Cancelled */
SELECT
  sl.order_no AS ProductionOrder,
  CASE 
    WHEN sl.new_status = 'Review' THEN 'Production Plan Sent for Review'
    WHEN sl.new_status = 'Approved' THEN 'Production Plan Approved'
    WHEN sl.new_status = 'Released' THEN 'Production Order Released'
    WHEN sl.new_status = 'Closed' THEN 'Production Order Closed'
    WHEN sl.new_status = 'Cancelled' THEN 'Production Order Cancelled'
  END AS ActivityName,
  sl.change_timestamp AS EventTime,
  po.planner_id AS Planner,
  sl.new_status AS ProductionOrderStatus,
  po.part_no AS PartNumber,
  NULL AS Workcenter,
  po.planned_quantity AS PlannedQuantity,
  po.planned_due_date AS PlannedEndDate,
  po.priority AS ProductionPriority,
  po.material_status AS MaterialAvailabilityStatus
FROM production_order_status_log AS sl
JOIN part_v_production_order AS po ON sl.order_no = po.order_no
WHERE sl.change_timestamp BETWEEN '[Your Start Date]' AND '[Your End Date]'
  AND sl.new_status IN ('Review', 'Approved', 'Released', 'Closed', 'Cancelled')

UNION ALL

/* Production Started */
SELECT
  sft.order_no AS ProductionOrder,
  'Production Started' AS ActivityName,
  MIN(sft.transaction_time) AS EventTime, /* Use the first transaction time as the start time */
  po.planner_id AS Planner,
  po.status AS ProductionOrderStatus,
  po.part_no AS PartNumber,
  sft.workcenter_code AS Workcenter, 
  po.planned_quantity AS PlannedQuantity,
  po.planned_due_date AS PlannedEndDate,
  po.priority AS ProductionPriority,
  po.material_status AS MaterialAvailabilityStatus
FROM shop_floor_transaction AS sft
JOIN part_v_production_order AS po ON sft.order_no = po.order_no
WHERE sft.transaction_time BETWEEN '[Your Start Date]' AND '[Your EndDate]'
  AND sft.transaction_type = 'Start'
GROUP BY sft.order_no, po.planner_id, po.status, po.part_no, sft.workcenter_code, po.planned_quantity, po.planned_due_date, po.priority, po.material_status

UNION ALL

/* Operation Completed */
SELECT
  sft.order_no AS ProductionOrder,
  'Operation Completed' AS ActivityName,
  sft.transaction_time AS EventTime,
  po.planner_id AS Planner,
  po.status AS ProductionOrderStatus,
  po.part_no AS PartNumber,
  sft.workcenter_code AS Workcenter,
  po.planned_quantity AS PlannedQuantity,
  po.planned_due_date AS PlannedEndDate,
  po.priority AS ProductionPriority,
  po.material_status AS MaterialAvailabilityStatus
FROM shop_floor_transaction AS sft
JOIN part_v_production_order AS po ON sft.order_no = po.order_no
WHERE sft.transaction_time BETWEEN '[Your Start Date]' AND '[Your End Date]'
  AND sft.transaction_type = 'CompleteOperation'

UNION ALL

/* Production Order Completed */
SELECT
  sft.order_no AS ProductionOrder,
  'Production Order Completed' AS ActivityName,
  sft.transaction_time AS EventTime,
  po.planner_id AS Planner,
  po.status AS ProductionOrderStatus,
  po.part_no AS PartNumber,
  NULL AS Workcenter, 
  po.planned_quantity AS PlannedQuantity,
  po.planned_due_date AS PlannedEndDate,
  po.priority AS ProductionPriority,
  po.material_status AS MaterialAvailabilityStatus
FROM shop_floor_transaction AS sft
JOIN part_v_production_order AS po ON sft.order_no = po.order_no
WHERE sft.transaction_time BETWEEN '[Your Start Date]' AND '[Your End Date]'
  AND sft.transaction_type = 'CompleteOrder'

UNION ALL

/* Production Plan Adjusted */
SELECT
  cl.order_no AS ProductionOrder,
  'Production Plan Adjusted' AS ActivityName,
  cl.change_timestamp AS EventTime,
  po.planner_id AS Planner,
  po.status AS ProductionOrderStatus,
  po.part_no AS PartNumber,
  NULL AS Workcenter,
  po.planned_quantity AS PlannedQuantity,
  po.planned_due_date AS PlannedEndDate,
  po.priority AS ProductionPriority,
  po.material_status AS MaterialAvailabilityStatus
FROM production_order_change_log AS cl
JOIN part_v_production_order AS po ON cl.order_no = po.order_no
WHERE cl.change_timestamp BETWEEN '[Your Start Date]' AND '[Your End Date]'
  AND cl.change_timestamp > po.release_date /* Only count adjustments after release */

UNION ALL

/* Material Requirements Planned */
SELECT
  mrp.source_order_no AS ProductionOrder,
  'Material Requirements Planned' AS ActivityName,
  mrp.run_completion_time AS EventTime,
  po.planner_id AS Planner,
  po.status AS ProductionOrderStatus,
  po.part_no AS PartNumber,
  NULL AS Workcenter,
  po.planned_quantity AS PlannedQuantity,
  po.planned_due_date AS PlannedEndDate,
  po.priority AS ProductionPriority,
  po.material_status AS MaterialAvailabilityStatus
FROM mrp_execution_log AS mrp
JOIN part_v_production_order AS po ON mrp.source_order_no = po.order_no
WHERE mrp.run_completion_time BETWEEN '[Your Start Date]' AND '[Your End Date]'

UNION ALL

/* Production Schedule Created */
SELECT
  ps.order_no AS ProductionOrder,
  'Production Schedule Created' AS ActivityName,
  ps.schedule_creation_date AS EventTime,
  po.planner_id AS Planner,
  po.status AS ProductionOrderStatus,
  po.part_no AS PartNumber,
  ps.scheduled_workcenter AS Workcenter,
  po.planned_quantity AS PlannedQuantity,
  po.planned_due_date AS PlannedEndDate,
  po.priority AS ProductionPriority,
  po.material_status AS MaterialAvailabilityStatus
FROM production_schedule AS ps
JOIN part_v_production_order AS po ON ps.order_no = po.order_no
WHERE ps.schedule_creation_date BETWEEN '[Your Start Date]' AND '[Your End Date]'

UNION ALL

/* Other conceptual events - requires custom logic and tables */
/* The following queries are templates and highly dependent on specific Plex configurations */

/* Demand Forecast Assessed */
SELECT 
  po.order_no AS ProductionOrder,
  'Demand Forecast Assessed' AS ActivityName,
  df.assessment_date AS EventTime,
  po.planner_id AS Planner,
  po.status AS ProductionOrderStatus,
  po.part_no AS PartNumber,
  NULL AS Workcenter,
  po.planned_quantity AS PlannedQuantity,
  po.planned_due_date AS PlannedEndDate,
  po.priority AS ProductionPriority,
  po.material_status AS MaterialAvailabilityStatus
FROM demand_forecast AS df
JOIN part_v_production_order AS po ON df.part_no = po.part_no AND po.create_date > df.assessment_date
WHERE df.assessment_date BETWEEN '[Your Start Date]' AND '[Your End Date]'

UNION ALL

/* Master Production Schedule Created */
SELECT 
  po.order_no AS ProductionOrder,
  'Master Production Schedule Created' AS ActivityName,
  mps.creation_date AS EventTime,
  po.planner_id AS Planner,
  po.status AS ProductionOrderStatus,
  po.part_no AS PartNumber,
  NULL AS Workcenter,
  po.planned_quantity AS PlannedQuantity,
  po.planned_due_date AS PlannedEndDate,
  po.priority AS ProductionPriority,
  po.material_status AS MaterialAvailabilityStatus
FROM master_production_schedule AS mps
JOIN part_v_production_order AS po ON mps.part_no = po.part_no AND po.create_date > mps.creation_date
WHERE mps.creation_date BETWEEN '[Your Start Date]' AND '[Your End Date]'

UNION ALL

/* Resource Allocation Confirmed */
SELECT 
  ra.order_no AS ProductionOrder,
  'Resource Allocation Confirmed' AS ActivityName,
  ra.confirmation_timestamp AS EventTime,
  po.planner_id AS Planner,
  po.status AS ProductionOrderStatus,
  po.part_no AS PartNumber,
  ra.workcenter_code AS Workcenter,
  po.planned_quantity AS PlannedQuantity,
  po.planned_due_date AS PlannedEndDate,
  po.priority AS ProductionPriority,
  po.material_status AS MaterialAvailabilityStatus
FROM resource_allocation_log AS ra
JOIN part_v_production_order AS po ON ra.order_no = po.order_no
WHERE ra.confirmation_timestamp BETWEEN '[Your Start Date]' AND '[Your End Date]'

UNION ALL

/* Production Performance Analyzed */
SELECT 
  va.order_no AS ProductionOrder,
  'Production Performance Analyzed' AS ActivityName,
  va.analysis_date AS EventTime,
  po.planner_id AS Planner,
  po.status AS ProductionOrderStatus,
  po.part_no AS PartNumber,
  NULL AS Workcenter,
  po.planned_quantity AS PlannedQuantity,
  po.planned_due_date AS PlannedEndDate,
  po.priority AS ProductionPriority,
  po.material_status AS MaterialAvailabilityStatus
FROM variance_analysis_log AS va
JOIN part_v_production_order AS po ON va.order_no = po.order_no
WHERE va.analysis_date BETWEEN '[Your Start Date]' AND '[Your End Date]';

Steps

Prerequisites: Ensure you have Python 3.6 or newer installed on your system. Install the necessary libraries, pandas for data manipulation and requests for making API calls, by running pip install pandas requests in your terminal.
Obtain API Credentials: Secure API credentials from your Plex system administrator. This includes a dedicated user account, password, and your company's Plex Customer Number (PCN). The user account must have permissions to access the required data sources via the Plex Integration API.
Set Up Python Script: Create a new Python file (e.g., extract_plex_production.py) and copy the provided script into this file.
Configure Script Parameters: In the script, locate the configuration section. Replace the placeholder values for PLEX_API_BASE_URL, PLEX_USERNAME, PLEX_PASSWORD, and PLEX_PCN with your actual credentials. Adjust the START_DATE and END_DATE parameters to define the desired extraction window.
Identify Data Sources: The provided script uses several common Plex data source keys as examples, such as Production_v_Production_Order_Summary and Production_v_Job_Operation_Event_Log. Verify these data source keys with your Plex administrator or documentation and update them in the script if your configuration uses different names.
Execute the Script: Run the script from your terminal using the command python extract_plex_production.py. The script will authenticate with the Plex API, fetch data from the specified sources, and process it.
Monitor Execution: The script will print progress messages to the console, indicating which data source it is currently fetching and how many records have been processed. Monitor for any error messages that might indicate issues with credentials, permissions, or API availability.
Transform Data: The script automatically transforms the nested JSON responses from the Plex API into a flat tabular structure. It unnests the data and creates distinct rows for each of the 16 required activities based on timestamps and status changes found in the source records.
Review the Output: Once the script completes, it will generate a CSV file named plex_production_event_log.csv in the same directory. Open this file in a spreadsheet program to review the structure and content.
Prepare for Upload: The generated CSV file is formatted according to ProcessMind requirements, with columns for ProductionOrder, ActivityName, EventTime, and other recommended attributes. No further formatting is typically needed. The file is ready to be uploaded for process mining analysis.

Configuration

API Credentials: A valid Plex user account and password are required for authentication. The script uses basic authentication combined with the PCN for session management.
Permissions: The API user must have read access to all data sources referenced in the script. Key data sources include production orders, job operations, status history, MRP logs, and scheduling records. Consult your Plex administrator to ensure the necessary permissions are granted.
Date Range: The script requires a START_DATE and END_DATE to be defined. For initial analysis, a date range of 3 to 6 months is recommended to provide a representative dataset without being excessively large. For high-volume environments, start with a shorter period like 1 month.
Filtering: The primary filters are the start and end dates applied to a relevant date field, such as the production order create date. The script can be modified to include additional filters in the API request payload, for example, filtering by Part_Number or Workcenter to narrow down the scope of the extraction.
Pagination: The script handles API pagination automatically. It uses the PageSize parameter (set to 1000 by default) and iterates through pages until all records for the specified period are retrieved. Be aware that a smaller page size can increase the number of API calls but may reduce the risk of timeouts.
Data Source Keys: The script relies on specific data source keys to query the correct data. The accuracy of these keys is critical for the extraction to succeed. These keys are specific to your Plex implementation and may need to be confirmed and adjusted.

a Sample Query python

import requests
import pandas as pd
import json
import datetime
import time

class=class="hl-string">"hl-comment"># --- Configuration ---
PLEX_API_BASE_URL = class="hl-string">"[Your_Plex_API_Base_URL]" class=class="hl-string">"hl-comment"># e.g., https://api.plex.com
PLEX_USERNAME = class="hl-string">"[Your_Username]"
PLEX_PASSWORD = class="hl-string">"[Your_Password]"
PLEX_PCN = class="hl-string">"[Your_PCN]"

class=class="hl-string">"hl-comment"># Date range for the extraction
START_DATE = class="hl-string">"2023-01-01"
END_DATE = class="hl-string">"2023-12-31"

class=class="hl-string">"hl-comment"># --- Main Script ---

def get_plex_data(datasource_key, filter_payload):
    class="hl-string">"""Fetches and paginates data from a specific Plex API data source."""
    all_rows = []
    page = 1
    page_size = 1000

    auth_payload = (PLEX_USERNAME, PLEX_PASSWORD)
    headers = {
        class="hl-string">'Content-Type': class="hl-string">'application/json',
        class="hl-string">'Accept': class="hl-string">'application/json'
    }
    
    while True:
        print(fclass="hl-string">"Fetching page {page} for data source {datasource_key}...")
        request_body = {
            class="hl-string">"RequestHeader": {
                class="hl-string">"PlexusCustomerNo": PLEX_PCN
            },
            class="hl-string">"RequestData": {
                class="hl-string">"DataSourceKey": datasource_key,
                class="hl-string">"InputParameters": filter_payload,
                class="hl-string">"PageSize": page_size,
                class="hl-string">"PageNumber": page
            }
        }

        try:
            response = requests.post(PLEX_API_BASE_URL, headers=headers, auth=auth_payload, data=json.dumps(request_body), timeout=120)
            response.raise_for_status()
            data = response.json()

            rows = data.get(class="hl-string">'ResponseData', {}).get(class="hl-string">'Rows', [])
            if not rows:
                break
                
            all_rows.extend(rows)
            page += 1
            class=class="hl-string">"hl-comment"># Respect potential rate limits
            time.sleep(1)

        except requests.exceptions.HTTPError as err:
            print(fclass="hl-string">"HTTP Error fetching data for {datasource_key}: {err}")
            break
        except requests.exceptions.RequestException as e:
            print(fclass="hl-string">"Request Error fetching data for {datasource_key}: {e}")
            break

    return all_rows

def main():
    class="hl-string">"""Main extraction and transformation logic."""
    event_log = []
    
    class=class="hl-string">"hl-comment"># Define filters for core production order data
    po_filter = {
        class="hl-string">'Order_Create_Date_Start': START_DATE,
        class="hl-string">'Order_Create_Date_End': END_DATE
    }
    
    class=class="hl-string">"hl-comment"># 1. Fetch core Production Order data
    class=class="hl-string">"hl-comment"># This source is assumed to contain key dates and statuses for multiple activities
    class=class="hl-string">"hl-comment"># Placeholder names for data source and columns are used.
    production_orders = get_plex_data(class="hl-string">'Production_v_Production_Order_Summary', po_filter)
    print(fclass="hl-string">"Found {len(production_orders)} production orders.")

    for po in production_orders:
        case_id = po.get(class="hl-string">'Production_Order_No')
        if not case_id:
            continue

        common_attributes = {
            class="hl-string">'ProductionOrder': case_id,
            class="hl-string">'Planner': po.get(class="hl-string">'Planner_Name'),
            class="hl-string">'ProductionOrderStatus': po.get(class="hl-string">'Order_Status'),
            class="hl-string">'PartNumber': po.get(class="hl-string">'Part_No'),
            class="hl-string">'Workcenter': po.get(class="hl-string">'Primary_Workcenter'),
            class="hl-string">'PlannedQuantity': po.get(class="hl-string">'Planned_Quantity'),
            class="hl-string">'PlannedEndDate': po.get(class="hl-string">'Planned_End_Date'),
            class="hl-string">'ProductionPriority': po.get(class="hl-string">'Priority_Code'),
            class="hl-string">'MaterialAvailabilityStatus': po.get(class="hl-string">'Material_Status')
        }

        class=class="hl-string">"hl-comment"># Map date fields to activities
        activity_map = {
            class="hl-string">'Demand Forecast Assessed': po.get(class="hl-string">'Demand_Assessment_Date'),
            class="hl-string">'Master Production Schedule Created': po.get(class="hl-string">'MPS_Creation_Date'),
            class="hl-string">'Material Requirements Planned': po.get(class="hl-string">'MRP_Run_Date'),
            class="hl-string">'Production Schedule Created': po.get(class="hl-string">'Schedule_Creation_Date'),
            class="hl-string">'Production Order Created': po.get(class="hl-string">'Create_Date'),
            class="hl-string">'Production Plan Sent for Review': po.get(class="hl-string">'Review_Submit_Date'),
            class="hl-string">'Production Plan Approved': po.get(class="hl-string">'Approval_Date'),
            class="hl-string">'Production Order Released': po.get(class="hl-string">'Release_Date'),
            class="hl-string">'Resource Allocation Confirmed': po.get(class="hl-string">'Resource_Confirmation_Date'),
            class="hl-string">'Production Order Completed': po.get(class="hl-string">'Order_Complete_Date'),
            class="hl-string">'Production Performance Analyzed': po.get(class="hl-string">'Variance_Analysis_Date'),
            class="hl-string">'Production Order Closed': po.get(class="hl-string">'Close_Date')
        }

        for activity, timestamp in activity_map.items():
            if timestamp:
                event_log.append({
                    **common_attributes,
                    class="hl-string">'ActivityName': activity,
                    class="hl-string">'EventTime': timestamp
                })
        
        class=class="hl-string">"hl-comment"># Handle status-based activities
        if po.get(class="hl-string">'Order_Status') == class="hl-string">'Cancelled':
            event_log.append({
                **common_attributes,
                class="hl-string">'ActivityName': class="hl-string">'Production Order Cancelled',
                class="hl-string">'EventTime': po.get(class="hl-string">'Status_Change_Date') class=class="hl-string">"hl-comment"># Assumes a general status change date is available
            })

    class=class="hl-string">"hl-comment"># 2. Fetch detailed shop floor events (start, operations, adjustments)
    op_log_filter = {
        class="hl-string">'Event_Date_Start': START_DATE,
        class="hl-string">'Event_Date_End': END_DATE
    }
    job_events = get_plex_data(class="hl-string">'Production_v_Job_Operation_Event_Log', op_log_filter)
    print(fclass="hl-string">"Found {len(job_events)} job operation events.")

    for event in job_events:
        case_id = event.get(class="hl-string">'Production_Order_No')
        if not case_id:
            continue

        event_type = event.get(class="hl-string">'Event_Type')
        activity_name = None

        if event_type == class="hl-string">'JOB_START':
            activity_name = class="hl-string">'Production Started'
        elif event_type == class="hl-string">'OPERATION_COMPLETE':
            activity_name = class="hl-string">'Operation Completed'
        elif event_type == class="hl-string">'PLAN_ADJUSTMENT':
            activity_name = class="hl-string">'Production Plan Adjusted'

        if activity_name:
            event_log.append({
                class="hl-string">'ProductionOrder': case_id,
                class="hl-string">'ActivityName': activity_name,
                class="hl-string">'EventTime': event.get(class="hl-string">'Event_Timestamp'),
                class="hl-string">'Planner': event.get(class="hl-string">'Planner_Name'),
                class="hl-string">'ProductionOrderStatus': event.get(class="hl-string">'Order_Status'),
                class="hl-string">'PartNumber': event.get(class="hl-string">'Part_No'),
                class="hl-string">'Workcenter': event.get(class="hl-string">'Workcenter'),
                class="hl-string">'PlannedQuantity': event.get(class="hl-string">'Planned_Quantity'),
                class="hl-string">'PlannedEndDate': event.get(class="hl-string">'Planned_End_Date'),
                class="hl-string">'ProductionPriority': event.get(class="hl-string">'Priority_Code'),
                class="hl-string">'MaterialAvailabilityStatus': None class=class="hl-string">"hl-comment"># Might not be available at event level
            })

    class=class="hl-string">"hl-comment"># 3. Create DataFrame and save to CSV
    if not event_log:
        print(class="hl-string">"No events were extracted. The output file will be empty.")
        return

    df = pd.DataFrame(event_log)
    df[class="hl-string">'EventTime'] = pd.to_datetime(df[class="hl-string">'EventTime'])
    df = df.sort_values(by=[class="hl-string">'ProductionOrder', class="hl-string">'EventTime'])
    
    class=class="hl-string">"hl-comment"># Reorder columns to match requirements
    final_columns = [
        class="hl-string">'ProductionOrder', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'Planner', 
        class="hl-string">'ProductionOrderStatus', class="hl-string">'PartNumber', class="hl-string">'Workcenter', class="hl-string">'PlannedQuantity',
        class="hl-string">'PlannedEndDate', class="hl-string">'ProductionPriority', class="hl-string">'MaterialAvailabilityStatus'
    ]
    df = df.reindex(columns=final_columns)

    df.to_csv(class="hl-string">'plex_production_event_log.csv', index=False, date_format=class="hl-string">'%Y-%m-%d %H:%M:%S')
    print(class="hl-string">"Extraction complete. Event log saved to plex_production_event_log.csv")

if __name__ == class="hl-string">"__main__":
    main()

Your Production Planning Data Template

Your Production Planning Data Template

Production Planning Attributes

Production Planning Activities

Extraction Guides

Plex IntelliPlex Analytic Application Export

Steps

Configuration

a Sample Query config

Python Script Extraction via Plex Integration APIs

Steps

Configuration

a Sample Query python

Ready to Get Started?

Optimize Production Planning: Reduce Cycle Time Now

Your Production Planning Data Template

Your Production Planning Data Template

Production Planning Attributes

Production Planning Activities

Extraction Guides

Plex IntelliPlex Analytic Application Export

Steps

Configuration

a Sample Query config

Python Script Extraction via Plex Integration APIs

Steps

Configuration

a Sample Query python

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Ready to Get Started?

Optimize Production Planning: Reduce Cycle Time Now